Archive of digitized analog boomer seismic reflection data collected during U.S. Geological S cruises Erda 90-1_HC, Erda 90-1_PBP, and Erda 91-3 in Mississippi Sound, June 1990 and September 1991
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic-reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. A large portion of this data resides in a single repository with minimal metadata. As part of the ... |
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AllScenarios_Bin1thru18_SSC: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output
The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ... |
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U.S. Geological Survey calculated 95th percentile of wave-current bottom shear stress for the South Atlantic Bight for May 2010 to May 2011 (SAB_95th_perc, polygon shapefile, Geographic, WGS84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ... |
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U.S. Geological Survey calculated half interpercentile range (half of the difference between the 16th and 84th percentiles) of wave-current bottom shear stress in the South Atlantic Bight from May 2010 to May 2011 (SAB_hIPR.shp, polygon shapefile, Geographic, WGS84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ... |
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U.S. Geological Survey calculated median of wave-current bottom shear stress in the South Atlantic Bight from May 2010 to May 2011 (SAB_median, polygon shapefile, Geographic, WGS84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ... |
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U.S. Geological Survey calculated recurrence interval of sediment mobility at select points in the South Atlantic Bight for May 2010 to May 2011 (SAB_mobile_freq, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ... |
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U.S. Geological Survey calculated percentage of time sediment is mobile for May 2010 to May 2011 at select points in the South Atlantic Bight (SAB_mobile_perc, point shapefile, Geographic, WGS84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ... |
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Documentation of the U.S. Geological Survey Oceanographic Time-Series Measurement Database
The U.S. Geological Survey (USGS) Oceanographic Time-Series Measurements Database contains oceanographic observations made as part of studies designed to increase understanding of sediment transport processes and associated ocean dynamics. This report describes the instrumentation and platforms used to make the measurements; the methods used to process and apply quality-control criteria and archive the data; and the data storage format. The report also includes instructions on how to access the data from ... |
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Archive of Digitized Analog Boomer Seismic-Reflection Data Collected During U.S. Geological Survey Cruises Erda 92-2 and Erda 92-4 in Mississippi Sound, June and August 1992
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (NGGDPP) (https:/ ... |
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AllScenarios_Initial_and_Final_Bed_Elevations: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output
The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ... |
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AllScenarios_Sediment_Fluxes: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output
The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ... |
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AllScenarios_Spatial_Flow: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output
The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ... |
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AllScenarios_Spatial_Waves: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output
The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ... |
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Revised (v. 1.1) Interpretation of Sedimentary Environments Based on National Oceanic and Atmospheric Administration (NOAA) Surveys H12009, H12010, H12011, H12015, H12033, H12137, and H12139, the adjacent 2011 NOAA survey H12299, and Verification Data from U.S. Geological Survey (USGS) Cruise 2011-006-FA Offshore in Block Island Sound (BISOUND_SEDENV_v1.1.SHP, Geographic, WGS 84)
The USGS, in cooperation with NOAA, is producing detailed maps of the seafloor off southern New England. The current phase of this cooperative research program is directed toward analyzing how bathymetric relief relates to the distribution of sedimentary environments and benthic communities. As part of this program, digital terrain models (DTMs) from bathymetry collected as part of NOAA's hydrographic charting activities are converted into ESRI raster grids and imagery, verified with bottom sampling and ... |
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Interpretation of sea floor geologic units for offshore of western and southern Martha's Vineyard and north of Nantucket, Massachusetts
Geologic, sediment texture, and physiographic zone maps characterize the sea floor south and west of Martha's Vineyard and north of Nantucket, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This ... |
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GrandBayModel_InputBathymetry: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output
The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ... |
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GrandBay_ValidationPeriod_Wave_WaterLevel: Modeling the Effects of Interior Headland Restoration on Estuarine Sediment Transport Processes in a Marine-Dominant Estuary: Delft3D Model Output
The effects of interior headland restoration on estuarine sediment transport processes are assessed through process-based numerical modeling. Three proposed interior headland restoration scenarios in the Grand Bay estuary (Mississippi/Alabama) are modeled using Delft3D (developed by Deltares) to understand impacts on suspended sediment concentrations, bed level morphology and sediment fluxes under present-day conditions and a sea level rise of 0.5 meters (m). Delft3D model output of suspended sediment ... |
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Archive of digitized analog boomer seismic reflection data collected during U.S. Geological Survey cruise Acadiana 87-2 in the northern Gulf of Mexico, June 1987
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic-reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. A large portion of this data resides in a single repository with minimal metadata. As part of the ... |
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Interpretation of the New York Bight Fault Zone on the inner-continental shelf within the New York Bight, derived from seismic data collected by the U.S. Geological Survey, 1995 - 1999 (Esri polyline shapefile, Geographic, WGS84)
The New York Bight fault (Hutchinson, 1984) was clearly evident within the high-resolution seismic records acquired with a CHIRP, boomer, and 15 cubic inch water gun systems. This fault was mapped from these data. Thus, yeilding a more complete picture of the inner-shelf geologic framework of the area. |
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Unprocessed aerial imagery from 12 May 2017 coastal survey of Central California.
This is a set of 628 oblique aerial photogrammetric images and their derivatives, collected from SeaCliff Beach to Fort Ord with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 17 May 2017 coastal survey of Central California.
This is a set of 3045 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 19 May 2017 coastal survey of Central California.
This is a set of 3164 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 27 May 2017 coastal survey of Central California.
This is a set of 642 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 31 May 2017 coastal survey of Central California.
This is a set of 410 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 13 June 2017 coastal survey of Central California.
This is a set of 757 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 26 June 2017 coastal survey of Central California.
This is a set of 5069 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 18 December 2017 coastal survey of Central California.
This is a set of 2948 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 21 December 2017 coastal survey of Central California.
This is a set of 2072 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 29 January 2018 coastal survey of Central California.
This is a set of 5365 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 7 March 2018 coastal survey of Central California.
This is a set of 5355 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 28 May 2018 coastal survey of Central California.
This is a set of 3550 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 June 2018 coastal survey of Central California.
This is a set of 1533 oblique aerial photogrammetric images and their derivatives, collected from Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 10 September 2018 coastal survey of Central California.
This is a set of 5846 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 February 2019 coastal survey of Central California.
This is a set of 4734 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 4 March 2019 coastal survey of Central California.
This is a set of 2541 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 11 March 2019 coastal survey of Central California.
This is a set of 1967 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 10 June 2019 coastal survey of Central California.
This is a set of 5042 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 15 October 2019 coastal survey of Central California.
This is a set of 3777 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 31 October 2019 coastal survey of Central California.
This is a set of 1911 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 29 November 2019 coastal survey of Central California.
This is a set of 1782 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Davenport with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 30 November 2019 coastal survey of Central California.
This is a set of 1444 oblique aerial photogrammetric images and their derivatives, collected from Davenport to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 20 January 2020 coastal survey of Central California.
This is a set of 3072 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 25 January 2020 coastal survey of Central California.
This is a set of 1880 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 9 March 2020 coastal survey of Central California.
This is a set of 1979 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 19 March 2020 coastal survey of Central California.
This is a set of 4835 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 19 April 2020 coastal survey of Central California.
This is a set of 2889 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 July 2020 coastal survey of Central California.
This is a set of 1890 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 30 September 2020 coastal survey of Central California.
This is a set of 3862 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 15 October 2020 coastal survey of Central California.
This is a set of 1982 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 10 January 2021 coastal survey of Central California.
This is a set of 1896 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 11 January 2021 coastal survey of Central California.
This is a set of 3796 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 29 January 2021 coastal survey of Central California.
This is a set of 4919 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 3 March 2021 coastal survey of Central California.
This is a set of 2049 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 26 March 2021 coastal survey of Central California.
This is a set of 5626 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 September 2021 coastal survey of Central California.
This is a set of 2678 oblique aerial photogrammetric images and their derivatives, collected from PigeonPt to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 18 December 2021 coastal survey of Central California.
This is a set of 4722 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 20 January 2022 coastal survey of Central California.
This is a set of 2066 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 4 February 2022 coastal survey of Central California.
This is a set of 2269 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12 March 2022 coastal survey of Central California.
This is a set of 2098 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 9 June 2022 coastal survey of Central California.
This is a set of 4595 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12-13 September 2022 coastal survey of Central California.
This is a set of 3661 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 1 January 2023 coastal survey of Central California.
This is a set of 2076 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 January 2023 coastal survey of Central California.
This is a set of 2105 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 16 January 2023 coastal survey of Central California.
This is a set of 2763 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 January 2023 coastal survey of Central California.
This is a set of 5039 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 February 2023 coastal survey of Central California.
This is a set of 2943 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 February 2023 coastal survey of Central California.
This is a set of 1939 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 2 March 2023 coastal survey of Central California.
This is a set of 1839 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 3 March 2023 coastal survey of Central California.
This is a set of 2758 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 13 March 2023 coastal survey of Central California.
This is a set of 2195 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 16 March 2023 coastal survey of Central California.
This is a set of 2915 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 17 March 2023 coastal survey of Central California.
This is a set of 2077 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 April 2023 coastal survey of Central California.
This is a set of 2374 vertical aerial photogrammetric images and their derivatives, collected from Half Moon Bay to Santa Cruz with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 June 2023 coastal survey of Central California.
This is a set of 2123 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 10 October 2023 coastal survey of Central California.
This is a set of 3929 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 11 October 2023 coastal survey of Central California.
This is a set of 4930 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 October 2023 coastal survey of Central California.
This is a set of 2869 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 December 2023 coastal survey of Central California.
This is a set of 4772 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 29 December 2023 coastal survey of Central California.
This is a set of 1821 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 January 2024 coastal survey of Central California.
This is a set of 2876 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12 January 2024 coastal survey of Central California.
This is a set of 1965 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 9 February 2024 coastal survey of Central California.
This is a set of 4787 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 February 2024 coastal survey of Central California.
This is a set of 2323 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 24 February 2024 coastal survey of Central California.
This is a set of 3059 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 7 March 2024 coastal survey of Central California.
This is a set of 2161 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 April 2024 coastal survey of Central California.
This is a set of 2286 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 17 June 2024 coastal survey of Central California.
This is a set of 5140 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 18 August 2024 coastal survey of Central California.
This is a set of 2003 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 January 2023 coastal-landslides survey of Central California.
This is a set of 8762 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 12 January 2023 coastal-landslides survey of Central California.
This is a set of 11207 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 4-5 November 2020 CZU-fire survey of Central California.
This is a set of 11776 near-nadir aerial photogrammetric images and their derivatives, collected from CZU fire with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 26 January 2017 landslides survey of Central California.
This is a set of 4889 oblique aerial photogrammetric images and their derivatives, collected from San Francisco Bay area with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 23 February 2017 landslides survey of Central California.
This is a set of 5954 oblique aerial photogrammetric images and their derivatives, collected from San Francisco Bay area with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 29 March 2018 coastal survey of Central and southern California.
This is a set of 1160 oblique aerial photogrammetric images and their derivatives, collected from Mud Creek Slide to Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera ... |
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Unprocessed aerial imagery from 13 October 2018 coastal survey of Northern California to Washington.
This is a set of 11805 oblique aerial photogrammetric images and their derivatives, collected from OR-WA border to Mussel Rock CA with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 19 April 2024 coastal survey of Northern California to Washington.
This is a set of 14032 oblique aerial photogrammetric images and their derivatives, collected from Hoh Head to Cape Mendocino with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 25 September 2016 coastal survey of Oregon and Washington.
This is a set of 1712 oblique aerial photogrammetric images and their derivatives, collected from Cape Falcon to Cascade Head with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 28 September 2017 coastal survey of Oregon and Washington.
This is a set of 2060 oblique aerial photogrammetric images and their derivatives, collected from OR-WA border to Nestucca River OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 3 August 2020 coastal survey of Oregon and Washington.
This is a set of 2324 oblique aerial photogrammetric images and their derivatives, collected from Taholah WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 3 September 2020 coastal survey of Oregon and Washington.
This is a set of 2158 oblique aerial photogrammetric images and their derivatives, collected from NW WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ... |
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Unprocessed aerial imagery from 29 August 2022 coastal survey of Oregon and Washington.
This is a set of 2413 oblique aerial photogrammetric images and their derivatives, collected from Taholah WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 June 2023 coastal survey of Oregon and Washington.
This is a set of 10139 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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PCMSC PlaneCam – Field data from periodic and event-response surveys of the U.S. West Coast.
This is an ongoing collection of aerial oblique and near-nadir images, ancillary data, and derivatives, from aerial surveys of coastal and near-coastal environments with a crewed light aircraft using the "PCMSC PlaneCam," a mounted fixed-lens DSLR camera with an attached consumer-grade GPS for time-keeping and approximate position, and a Global Navigation Satellite System (GNSS) for precise positioning. Data are collected and produced primarily for coastal monitoring using structure-from-motion ... |
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Unprocessed aerial imagery from 28 September 2016 coastal survey of Southern California.
This is a set of 2671 oblique aerial photogrammetric images and their derivatives, collected from ptConception to Ventura with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 March 2017 coastal survey of Southern California.
This is a set of 2979 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Ventura with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 27 December 2017 coastal survey of Southern California.
This is a set of 2392 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Santa Barbara with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 13 September 2018 coastal survey of Southern California.
This is a set of 2062 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 6 May 2020 coastal survey of Southern California.
This is a set of 2167 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 18 September 2020 coastal survey of Southern California.
This is a set of 1968 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 2 March 2022 coastal survey of Southern California.
This is a set of 2212 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 28 September 2022 coastal survey of Southern California.
This is a set of 2032 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 2 October 2022 coastal survey of Southern California.
This is a set of 1108 oblique aerial photogrammetric images and their derivatives, collected from Santa Rosa Island with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by ... |
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Unprocessed aerial imagery from 8 March 2023 coastal survey of Southern California.
This is a set of 2006 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 12 October 2023 coastal survey of Southern California.
This is a set of 2013 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Port Hueneme with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 5 January 2024 coastal survey of Southern California.
This is a set of 2061 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 12 February 2024 coastal survey of Southern California.
This is a set of 2032 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 23 February 2024 coastal survey of Southern California.
This is a set of 2371 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 18 March 2024 coastal survey of Southern California.
This is a set of 2076 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ... |
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Unprocessed aerial imagery from 23 January 2018 Thomas-fire survey of Southern California.
This is a set of 4838 oblique aerial photogrammetric images and their derivatives, collected from Montecito with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 19 April 2023 thomas-fire survey of Southern California.
This is a set of 3086 vertical aerial photogrammetric images and their derivatives, collected from Montecito with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 4 August 2020 coastal survey of Washington.
This is a set of 645 oblique aerial photogrammetric images and their derivatives, collected from Elwha river mouth to Ediz Hook CG with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 28 August 2022 coastal survey of Washington.
This is a set of 4116 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 29 August 2022 coastal survey of Washington.
This is a set of 4281 oblique and near nadir aerial photogrammetric images and their derivatives, collected from Elwha river mouth to Ediz Hook CG with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the ... |
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Unprocessed aerial imagery from 6 July 2024 coastal survey of Washington.
This is a set of 7809 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ... |
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Unprocessed aerial imagery from 31 August 2024 coastal survey of Washington.
This is a set of 6976 oblique aerial photogrammetric images and their derivatives, collected from Juan de Fuca Strait to Grays Harbor with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Quaternary faults offshore of California
A comprehensive map of Quaternary faults has been generated for offshore of California. The Quaternary fault map includes mapped geometries and attribute information for offshore fault systems located in California State and Federal waters. The polyline shapefile has been compiled from previously published mapping where relatively dense, high-resolution marine geophysical data exist. The data are also available in kml format and are accompanied by a pdf containing citations for the compiled source data. In ... |
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Locations of sediment cores collected from Montague Island, AK
This dataset includes locations of sediment cores collected from coastal environments on Montague Island, Alaska. The cores were collected with hand driven peat augers to assess environmental changes related to tectonic uplift caused by historic and prehistoric earthquakes. |
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Computed Tomography (CT) scans of sediment cores collected from Montague Island, AK
This dataset includes computed tomography (CT) scans of sediment cores collected from coastal environments on Montague Island, Alaska. The cores were collected with hand driven peat augers to assess environmental changes related to tectonic uplift caused by historic and prehistoric earthquakes. |
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Hydrodynamic and sediment transport tsunami models at the Salmon River estuary, Oregon
This portion of the USGS data release describes the Delft3D-FLOW model application for propagating simulated tsunamis from 15 hypothetical earthquake sources of the Cascadia Subduction Zone through a series of nested grids to modeling tsunami sediment transport in the Salmon River estuary, OR. Input files necessary to run the Delft3D-FLOW model are provided. The model application was constructed using Delft3D-FLOW. Zip files containing model setup data are provided for each of the nested hydrodynamic grids ... |
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hawaii_vol - Volcanic and Seismic Hazard Intensity Level in the coastal zone of Hawaii, Hawaii
Volcanic and Seismic Hazard Intensity Level in the coastal zone of Hawaii, Hawaii |
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kauai_vol - Volcanic and Seismic Hazard Intensity Level in the coastal zone of Kauai, Hawaii
Volcanic and Seismic Hazard Intensity Level in the coastal zone of Kauai, Hawaii |
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lanai_vol - Volcanic and Seismic Hazard Intensity Level in the coastal zone of Lanai, Hawaii
Volcanic and Seismic Hazard Intensity Level in the coastal zone of Lanai, Hawaii |
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maui_vol - Volcanic and Seismic Hazard Intensity Level in the coastal zone of Maui, Hawaii
Volcanic and Seismic Hazard Intensity Level in the coastal zone of Maui, Hawaii |
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molo_vol - Volcanic and Seismic Hazard Intensity Level in the coastal zone of Molokai, Hawaii
Volcanic and Seismic Hazard Intensity Level in the coastal zone of Molokai, Hawaii |
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oahu_vol - Volcanic and Seismic Hazard Intensity Level in the coastal zone of Oahu, Hawaii
Volcanic and Seismic Hazard Intensity Level in the coastal zone of Oahu, Hawaii |
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sand_vol - Volcanic and Seismic Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii
Volcanic and Seismic Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii |
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National Assessment of Hurricane-Induced Coastal Erosion Hazards: Puerto Rico
This dataset contains information on the probabilities of hurricane-induced erosion (collision, inundation and overwash) for each 100-meter (m) section of the Puerto Rico coast for category 1-5 hurricanes. The analysis is based on a storm-impact scaling model that uses observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to the direct landfall of category 1-5 hurricanes. Hurricane-induced water levels, due to both surge and waves, are ... |
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Reef-census data from Buck Island Reef
In July of 2016, Florida Institute of Technology researchers, in collaboration with the U.S. Geological Survey (USGS), conducted reef-census surveys at 54 sites around Buck Island Reef National Monument, St. Croix, U.S. Virgin Islands. The sites are divided across two reef sectors (North and South) and three reef habitats (fore reef, reef crest, and back reef). The surveys provided data on the percent coverage of corals and other benthic taxa, and abundance of bioeroding parrotfishes and urchins. |
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Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2008
Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. To re-establish a population at Assateague Island National Seashore (ASIS), seabeach amaranth cultivars were planted by ASIS natural resources staff for three growing seasons from 1999 to 2001 and have been monitored since 2001. Characteristics of favorable seabeach amaranth locations were assessed by sampling barrier island and habitat characteristics at sites ... |
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Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2010
Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. To re-establish a population at Assateague Island National Seashore (ASIS), seabeach amaranth cultivars were planted by ASIS natural resources staff for three growing seasons from 1999 to 2001 and have been monitored since 2001. Characteristics of favorable seabeach amaranth locations were assessed by sampling barrier island and habitat characteristics at sites ... |
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Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2014
Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. To re-establish a population at Assateague Island National Seashore (ASIS), seabeach amaranth cultivars were planted by ASIS natural resources staff for three growing seasons from 1999 to 2001 and have been monitored since 2001. Characteristics of favorable seabeach amaranth locations were assessed by sampling barrier island and habitat characteristics at sites ... |
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Barrier island geomorphology and seabeach amaranth metrics at 50-m alongshore transects, and 5-m cross-shore points for 2008 — Assateague Island, MD and VA.
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for developing approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the effects of sea-level rise on shoreline change, barrier island geomorphology, and habitat availability for species such as piping plover ... |
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SC Bias Feature – Feature class containing South Carolina proxy-datum bias information to be used in the Digital Shoreline Analysis System
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Intersects for the coastal region of South Carolina generated to calculate long-term shoreline change rates using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Intersects for coastal region of South Carolina generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Long-term shoreline change rate transects for the South Carolina coastal region, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Short-term shoreline change rate transects for the South Carolina coastal region using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the central coast of North Carolina from Cape Hatteras to Cape Lookout (NCcentral)
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Long and short-term shoreline intersect points for the central coast of North Carolina (NCcentral), calculated using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Long and short-term shoreline change rate transects for the central North Carolina coastal region (NCcentral), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the northern coast of North Carolina from the Virginia border to Cape Hatteras (NCnorth)
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Long and short-term shoreline intersect points for the northern coast of North Carolina (NCnorth), calculated using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Long and short-term shoreline change rate transects for the northern North Carolina coastal region (NCnorth), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the southern coast of North Carolina from Cape Lookout to Cape Fear (NCsouth)
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Long and short-term shoreline intersect points for the southern coast of North Carolina (NCsouth), calculated using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Long and short-term shoreline change rate transects for the southern North Carolina coastal region (NCsouth), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Bias feature containing proxy-datum bias information to be used in the Digital Shoreline Analysis System for the western coast of North Carolina from Cape Fear to the South Carolina border (NCwest)
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Long and short-term shoreline intersect points for the western coast of North Carolina (NCwest), calculated using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Long and short-term shoreline change rate transects for the western North Carolina coastal region (NCwest), calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Point shapefile of probability of shoreline change along the U.S. Atlantic Coast (ProbSLC_AtlanticData.shp)
During the 21st century, sea-level rise will have a wide range of effects on coastal environments, human development and infrastructure in coastal areas. Consequently there is a need to develop modeling or other analytical approaches that can be used to evaluate potential impacts to inform coastal management. This shapefile provides the data that were used to develop and evaluate the performance of a Bayesian network (BN) that was developed to predict long-term shoreline change associated with sea-level ... |
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Offshore baseline for Cape Cod coastal region generated to calculate shoreline change rates from Provincetown to the southern end of Monomoy Island, Massachusetts (CapeCod_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Cape Cod region from Provincetown to the southern end of Monomoy Island, Massachusetts (CapeCod_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Shorelines of the Cape Cod coastal region from Provincetown to the southern end of Monomoy Island, Massachusetts, used in shoreline change analysis (CapeCod_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Cape Cod region from Provincetown to the southern end of Monomoy Island, Massachusetts (CapeCod_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Offshore baseline for Delmarva North coastal region generated to calculate shoreline change rates from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia (DelmarvaN_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Delmarva North region from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia (DelmarvaN_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Shorelines of the Delmarva North coastal region from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia, used in shoreline change analysis (DelmarvaN_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Delmarva North region from Cape Henlopen, Delaware to the southern end of Assateague Island, Virginia (DelmarvaN_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Offshore baseline for the Delmarva South/Southern Virginia region generated to calculate shoreline change rates from Wallops Island, Virginia to the Virginia/North Carolina border (DelmarvaS_SVA_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Delmarva South/Southern Virginia region from Wallops Island, Virginia to the Virginia/North Carolina border (DelmarvaS_SVA_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Shorelines of the Delmarva South and Southern Virginia coastal region from Wallops Island, Virginia to the Virginia/North Carolina border, used in shoreline change analysis (DelmarvaS_SVA_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Delmarva South/Southern Virginia region from Wallops Island, Virginia to the Virginia/North Carolina border (DelmarvaS_SVA_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Offshore baseline for Greater Boston coastal region from the southern side of Cape Ann, Massachusetts to Sandy Neck Beach in Sandwich, Massachusetts, generated to calculate shoreline change rates (GreaterBoston_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Greater Boston region from the southern side of Cape Ann, Massachusetts to Sandy Neck Beach in Sandwich, Massachusetts (GreaterBoston_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Shorelines of the Greater Boston coastal region from the southern side of Cape Ann, Massachusetts to Sandy Neck Beach in Sandwich, Massachusetts, used in shoreline change analysis (GreaterBoston_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Greater Boston region from the southern side of Cape Ann, Massachusetts to Sandy Neck Beach in Sandwich, Massachusetts (GreaterBoston_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Offshore baseline for Long Island coastal region generated to calculate shoreline change rates for the Long Island region from Montauk Point to the entrance of Raritan Bay, New York (LongIsland_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Long Island region from Montauk Point to the entrance of Raritan Bay, New York (LongIsland_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
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Shorelines of the Long Island coastal region used in shoreline change analysis for the Long Island region from Montauk Point to the entrance of Raritan Bay, New York (LongIsland_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Rate Calculations for the Long Island region from Montauk Point to the entrance of Raritan Bay, New York (LongIsland_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for Massachusetts Islands coastal region generated to calculate shoreline change rates for Martha's Vineyard and Nantucket (MA_Islands_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the Massachusetts Islands Region including Martha's Vineyard and Nantucket (MA_Islands_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Massachusetts Islands coastal region including Martha's Vineyard and Nantucket, used in shoreline change analysis (MA_Islands_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the Massachusetts Islands Region including Martha's Vineyard and Nantucket (MA_Islands_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for New England North coastal region from Popham Beach, Maine to the northern side of Cape Ann, Massachusetts, generated to calculate shoreline change rates (NE_North_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New England North region from Popham Beach, Maine to the northern side of Cape Ann, Massachusetts (NewEnglandN_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the New England North coastal region from Popham Beach, Maine to the northern side of Cape Ann, Massachusetts, used in shoreline change analysis (NewEnglandN_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New England North region from Popham Beach, Maine to the northern side of Cape Ann, Massachusetts (NewEnglandN_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for New England South coastal region from Dartmouth, Massachusetts to Napatree Point, Rhode Island, generated to calculate shoreline change rates (NE_South_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New England South region from Dartmouth, Massachusetts to Napatree Point, Rhode Island (NewEnglandS_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the New England South coastal region used in shoreline change analysis from Dartmouth, Massachusetts to Napatree Point, Rhode Island (NewEnglandS_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New England South region from Dartmouth, Massachusetts to Napatree Point, Rhode Island (NewEnglandS_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for New Jersey North coastal region generated to calculate shoreline change rates from Sandy Hook to Little Egg Inlet, New Jersey (NJN_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New Jersey North region from Sandy Hook to Little Egg Inlet, New Jersey (NewJerseyN_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the New Jersey North coastal region used in shoreline change analysis from Sandy Hook to Little Egg Inlet, New Jersey (NewJerseyN_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New Jersey North region from Sandy Hook to Little Egg Inlet, New Jersey (NewJerseyN_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for New Jersey South coastal region generated to calculate shoreline change rates from Little Egg Inlet to Cape May, New Jersey (NJS_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Long-Term Rate Calculations for the New Jersey South region from Little Egg Inlet to Cape, May, New Jersey (NewJerseyS_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the New Jersey South coastal region used in shoreline change analysis from Little Egg Inlet to Cape May, New Jersey (NewJerseyS_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.1 Transects with Short-Term Rate Calculations for the New Jersey South region from Little Egg Inlet to Cape, May, New Jersey (NewJerseyS_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiE_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along East Kauai, Hawaii (Papaa to Nawiliwili)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiE_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Kauai east region from Papaa to Nawiliwili, Hawaii
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiE_shorelines - Shorelines of the eastern coastal region of Kauai, Hawaii, from Papaa to Nawiliwili, used in shoreline change analysis.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiE_ST- Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Kauai east region from Papaa to Nawiliwili, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiN_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along North Kauai, Hawaii (Haena to Moloaa)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiN_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Kauai north region from Haena to Moloaa, Hawaii
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiN_shorelines - Shorelines of the northern coastal region of Kauai, Hawaii, from Haena to Moloaa, used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiN_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with weighted linear regression short-term rate calculations for the Kauai north region from Haena to Moloaa, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiS_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along South Kauai, Hawaii (Waimea to Kipu Kai)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiS_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Kauai south region from Waimea to Kipu Kai, Hawaii
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiS_shorelines - Shorelines of the southern coastal region of Kauai, Hawaii, from Waimea to Kipu Kai, used in shoreline change analysis.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiS_ST- Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Kauai south region from Waimea to Kipu Kai, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiW_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along West Kauai, Hawaii (Oomano to Polihale)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiW_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Kauai west region from Oomano to Polihale, Hawaii
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiW_shorelines - Shorelines of the western coastal region of Kauai, Hawaii, from Oomano to Polihale, used in shoreline change analysis.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
KauaiW_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Kauai west region from Oomano to Polihale, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiK_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along the Kihei Coast of Maui, Hawaii (Maalaea to Makena)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiK_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Maui Kihei region from Maalaea to Makena, Hawaii
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiK_shorelines - Shorelines of the Kihei coastal region of Maui, Hawaii, from Maalaea to Makena, used in shoreline change analysis.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiK_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Maui Kihei region from Maalaea to Makena, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiN_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along the North Coast of Maui, Hawaii (Waihee to Kuau)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiN_LT- Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Maui North region from Waihee to Kuau, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiN_shorelines - Shorelines of the northern coastal region of Maui, Hawaii, from Waihee to Kuau, used in shoreline change analysis.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiN_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Maui North region from Waihee to Kuau, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiW_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along the West Coast of Maui, Hawaii (Ukumehame to Honolua)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiW_LT- Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Maui West region from Ukumehame to Honolua, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiW_shorelines - Shorelines of the western coastal region of Maui, Hawaii, from Ukumehame to Honolua, used in shoreline change analysis.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
MauiW_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Maui West region from Ukumehame to Honolua, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuE_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along East Oahu, Hawaii (Kahuku to Makapuu)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuE_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Oahu East region from Kahuku to Makapuu, Hawaii
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuE_shorelines - Shorelines of the eastern coastal region of Oahu, Hawaii, from Kahuku to Makapuu, used in shoreline change analysis.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuE_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Oahu East region from Kahuku to Makapuu, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuN_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along North Oahu, Hawaii (Camp Erdman to Kahuku)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuN_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Oahu north region from Camp Erdman to Kahuku, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuN_shorelines - Shorelines of the northern coastal region of Oahu, Hawaii, from Camp Erdman to Kahuku, used in shoreline change analysis.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuN_ST - Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Oahu North region from Camp Erdman to Kahuku, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuS_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along South Oahu, Hawaii (Barbers Point to Sandy Beach)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuS_LT - Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Oahu south region from Barbers Point to Sandy Beach, Hawaii
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuS_shorelines - Shorelines of the southern coastal region of Oahu, Hawaii, from Barbers Point to Sandy Beach, used in shoreline change analysis.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuS_ST- Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Oahu south region from Barbers Point to Sandy Beach, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuW_baseline - Offshore baseline used to cast shore-perpendicular transects for measurement of historical shoreline positions along West Oahu, Hawaii (Yokohama to Tracks Beach)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuW_LT- Digital Shoreline Analysis System (DSAS) version 4.2 transects with long-term weighted linear regression rate calculations for the Oahu west region from Yokohama to Tracks Beach, Hawaii
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuW_shorelines - Shorelines of the western coastal region of Oahu, Hawaii, from Yokohama to Tracks Beach, used in shoreline change analysis.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
OahuW_ST- Digital Shoreline Analysis System (DSAS) version 4.2 transects with short-term weighted linear regression rate calculations for the Oahu west region from Yokohama to Tracks Beach, Hawaii.
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the Oregon coastal region generated to calculate shoreline change rates (OR_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Oregon (OR_shorelines_uncertainty.dbf)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Oregon coastal region used in shoreline change analysis (OR_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.2 Transects with Long-Term Linear Regression Rate Calculations for Oregon (OR_transects_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.2 Transects with Short-Term End Point Rate Calculations for Oregon (OR_transects_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the Washington coastal region generated to calculate shoreline change rates (WA_baseline.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Washington (WA_shorelines_uncertainty.dbf)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Washington coastal region used in shoreline change analysis (WA_shorelines.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.2 Transects with Long-Term Linear Regression Rate Calculations for Washington (WA_transects_LT.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.2 Transects with Short-Term End Point Rate Calculations for Washington (WA_transects_ST.shp)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the northeastern Florida (FLne) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the northeastern Florida (FLne) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for northeastern Florida (FLne)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for northeastern Florida (FLne)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for northeastern Florida (FLne)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for northeastern Florida (FLne)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the southeastern Florida (FLse) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the southeastern Florida (FLse) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for southeastern Florida (FLse)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for southeastern Florida (FLse)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for southeastern Florida (FLse)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for southeastern Florida (FLse)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the Georgia (GA) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Georgia (GA) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Georgia (GA)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Georgia (GA)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Georgia (GA)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Georgia (GA)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the central North Carolina (NCcentral) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the central North Carolina (NCcentral) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for central North Carolina (NCcentral)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for central North Carolina (NCcentral)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for central North Carolina (NCcentral)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for central North Carolina (NCcentral)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the northern North Carolina (NCnorth) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the northern North Carolina (NCnorth) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for northern North Carolina (NCnorth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for northern North Carolina (NCnorth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for northern North Carolina (NCnorth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for northern North Carolina (NCnorth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the southern North Carolina (NCsouth) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the southern North Carolina (NCsouth) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for southern North Carolina (NCsouth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for southern North Carolina (NCsouth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for southern North Carolina (NCsouth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for southern North Carolina (NCsouth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the western North Carolina (NCwest) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the western North Carolina (NCwest) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for western North Carolina (NCwest)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for western North Carolina (NCwest)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for western North Carolina (NCwest)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the South Carolina (SC) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the South Carolina (SC) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for South Carolina (SC)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for South Carolina (SC)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for South Carolina (SC)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for South Carolina (SC)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the Alabama coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Alabama
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Alabama coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Alabama
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Alabama
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Alabama
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the Florida north (FLnorth) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Florida north (FLnorth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Florida north (FLnorth) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Florida north (FLnorth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Florida north (FLnorth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Florida north (FLnorth)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the Florida west (FLwest) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Florida west (FLwest)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Florida west (FLwest) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Florida west (FLwest)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Florida west (FLwest)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Florida west (FLwest)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the Louisiana coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Louisiana
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Louisiana coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Louisiana
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Louisiana
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Louisiana
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the Mississippi coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Mississippi
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Mississippi coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Mississippi
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term End Point Rate Calculations for Mississippi
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Mississippi
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the Texas east (TXeast) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Texas east (TXeast)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Texas east (TXeast) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Texas east (TXeast)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Texas east (TXeast)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Offshore baseline for the Texas west (TXwest) coastal region generated to calculate shoreline change rates
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Long-Term Linear Regression Rate Calculations for Texas west (TXwest)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Shorelines of the Texas west (TXwest) coastal region used in shoreline change analysis
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Texas west (TXwest)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
Digital Shoreline Analysis System version 4.3 Transects with Short-Term Linear Regression Rate Calculations for Texas west (TXwest)
Sandy ocean beaches are a popular recreational destination, often surrounded by communities containing valuable real estate. Development is on the rise despite the fact that coastal infrastructure is subjected to flooding and erosion. As a result, there is an increased demand for accurate information regarding past and present shoreline changes. To meet these national needs, the Coastal and Marine Geology Program of the U.S. Geological Survey (USGS) is compiling existing reliable historical shoreline ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2010–2011
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2012–2013
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2013–2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Edwin B. Forsythe NWR, NJ, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Edwin B. Forsythe NWR, NJ, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Edwin B. Forsythe NWR, NJ, 2013–2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2010–2011
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2014–2015
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2010–2011
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2013–2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
Info |
VA Bias_Feature – Feature class containing Virginia proxy-datum bias information to be used in the Digital Shoreline Analysis System.
Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release ... |
Info |
Intersects for coastal region of Virginia generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
Info |
Long-term shoreline change rates for the Virginia coastal region, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
Info |
Short-term shoreline change rates for the Virginia coastal region using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Mean High Water Shorelines for the Outer Cape of Massachusetts from Nauset Inlet to Race Point (1998-2005)
This data release contains mean high water (MHW) shorelines for the Outer Cape of Cape Cod, Massachusetts, from Nauset Inlet to Race Point. From 1998-2005, the U.S. Geological Survey surveyed 45 kilometers of coastline 111 times using a ground-based system called Surveying Wide-Area Shorelines (SWASH). The SWASH system used a six-wheeled amphibious all-terrain vehicle as a platform for an array of Global Positioning System sensors. High-accuracy measurements of horizontal position, vertical position, and ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Assateague Island, MD & VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Assateague Island, MD & VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Assawoman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Assawoman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cape Hatteras, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Cape Hatteras, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cape Lookout, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Cape Lookout, NC, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Coast Guard Beach, MA, 2013-2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Coast Guard Beach, MA, 2013-2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cobb Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Cobb Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fisherman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Fisherman Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Metompkin Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Metompkin Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Monomoy Island, MA, 2013-2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Monomoy Island, MA, 2013-2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Myrtle Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Myrtle Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parramore Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Parramore Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parker River, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Parker River, MA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rhode Island National Wildlife Refuge, RI, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Rhode Island National Wildlife Refuge, RI, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Ship Shoal Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Ship Shoal Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Smith Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Smith Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Wreck Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Wreck Island, VA, 2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Intersects for the coastal region of Virginia generated to calculate long-term shoreline change rates using the Digital Shoreline Analysis System version 5.1
The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This ... |
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Geographic data defining watersheds less than 45 square kilometers burned in all California wildfires greater than 100 square kilometers, 1984—2021
This table contains geographic information defining watersheds that were burned in large wildfires (greater than 100 square kilometers) that occurred in California or California-draining regions (i.e., upper Klamath watershed) between the years 1984 and 2021. Each wildfire was broken into tens to thousands of small watersheds, and each row of this table contains geographic information defining a single watershed. |
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Postfire erosion modeling results using the Water Erosion Prediction Project (WEPP) model for all large wildfires in California, 1984–2021
This is a shapefile containing polygons of watersheds that were burned in wildfires that occurred in California between 1984 and 2021. The Water Erosion Prediction Project (WEPP) model for postfire erosion was run on all watersheds for the first year following wildfire and the results of this modeling effort are included as attributes of each watershed polygon. |
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Model estimates of the probability and volume of debris flows that may be produced by a storm following recent wildfire; re-release of ten wildfires across California, 1997—2015
These data show model estimates of debris flow likelihood and volume that may be produced by a storm in a recently burned landscape. The scientific methods used by the U.S. Geological Survey Emergency Assessment of Post-Fire Debris-Flow Hazards were changed following 2015, and these shapefiles are a re-release of ten fires that occurred between 1997 and 2015 fires, using the updated methods. These ten fires were re-run to provide estimates of debris flow volumes as post-fire debris flows were documented but ... |
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Summary by wildfire of all postfire erosion modeled estimates and field-based observation for large fires 1984—2021
These data show all the postfire erosion results affiliated with this data release summed by wildfire and attached to a polygon of each fire perimeter, as defined by Monitoring Trends in Burn Severity (MTBS). The results are shown as attributes for each polygon of wildfire perimeter. Some of the original MTBS data (name, ignition date, and ID) were preserved to allow for joining to other MTBS data. Results include WEPP modeling results of hillslope and channel erosion, a sum of postfire debris flow modeling ... |
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Postfire debris-flow volumes and their associated observation, location, and volume sources
This table contains measured and modeled postfire debris flow volumes alongside the associated sources for debris flow documentation, locations, and volumes. We conducted a search of scientific literature and news media reports to find documentation of debris flows that may have followed all wildfires greater than 100 square kilometers that occurred between 1984 and 2021 in California. The wildfires listed are all the fires we found that had documented postfire debris flows. Some fires had field ... |
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Bathymetric change analyses of the Sacramento River near Rio Vista, California, and the junction of Cache and Steamboat sloughs, from 1992 to 2004
Bathymetric change grids covering the periods of time from 1992 to 1998 and from 1994 to 2004 are presented. The grids cover a portion of the Sacramento River near Rio Vista, California, extending partially upstream on Cache and Steamboat sloughs by the Ryer Island Ferry, as well as continuing up the Sacramento River towards Isleton. Positive grid values indicate accretion, or a shallowing of the surface bathymetric surface, and negative grid values indicate erosion, or a deepening of the bathymetric ... |
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Modeled extreme total water levels along the U.S. west coast
This dataset contains information on the probabilities of storm-induced erosion (collision, inundation and overwash) for each 100-meter (m) section of the United States Pacific coast for return period storm scenarios. The analysis is based on a storm-impact scaling model that uses observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to the hydrodynamic forcing. Storm-induced water levels, due to both surge and waves, are compared to coastal ... |
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Bathymetric change analyses of the southernmost portion of the Mokelumne River, California, from 1934 to 2018
Bathymetric change grids covering the periods of time from 1934 to 2011, from 2011 to 2018, and from 1934 to 2018 are presented. The grids cover a portion of the Mokelumne River, California, starting at its terminus at the San Joaquin River and moving upriver to the confluences of the north and south branches of the Mokelumne. Positive grid values indicate accretion, or a shallowing of the surface bathymetric surface, and negative grid values indicate erosion, or a deepening of the bathymetric surface. ... |
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hawaii_ero - Erosion Hazard Intensity Level in the coastal zone of Hawaii, Hawaii
Erosion Hazard Intensity Level in the coastal zone of Hawaii, Hawaii |
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kauai_ero - Erosion Hazard Intensity Level in the coastal zone of Kauai, Hawaii
Erosion Hazard Intensity Level in the coastal zone of Kauai, Hawaii |
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lanai_ero - Erosion Hazard Intensity Level in the coastal zone of Lanai, Hawaii
Erosion Hazard Intensity Level in the coastal zone of Lanai, Hawaii |
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maui_ero - Erosion Hazard Intensity Level in the coastal zone of Maui, Hawaii
Erosion Hazard Intensity Level in the coastal zone of Maui, Hawaii |
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molo_ero - Erosion Hazard Intensity Level in the coastal zone of Molokai, Hawaii
Erosion Hazard Intensity Level in the coastal zone of Molokai, Hawaii |
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oahu_ero - Erosion Hazard Intensity Level in the coastal zone of Oahu, Hawaii
Erosion Hazard Intensity Level in the coastal zone of Oahu, Hawaii |
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sand_ero - Erosion Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii
Erosion Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii |
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Offshore baseline for the northern Alaska coastal region generated to calculate shoreline change rates along exposed coastlines between the Okpilak-Hulahula River Delta and the Colville River Deltas for the time period 1947 to 2007
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for exposed shorelines between the Okpilak-Hulahula River Delta and Colville River Delta for the time period 1947 to 2007
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Offshore baseline for the northern Alaska coastal region generated to calculate shoreline change rates along sheltered coastlines between the Okpilak-Hulahula River Delta and the Colville River Delta for the time period 1947 to 2007
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for sheltered shorelines between the Okpilak-Hulahula River Delta and Colville River Delta for the time period 1947 to 2007
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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CentralBeaufort_shorelines.shp - Shorelines for the northern Alaska coastal region used in shoreline change analysis, 1947 to 2007
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Offshore baseline for the northern Alaska coastal region generated to calculate shoreline change rates along exposed coastlines between the U.S.-Canadian border and the Okpilak-Hulahula River Delta for the time period 1947 to 2003
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for exposed shorelines between the U.S.-Canadian border and the Okpilak-Hulahula river delta for the time period 1947 to 2003
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Offshore baseline for the northern Alaska coastal region generated to calculate shoreline change rates along sheltered coastlines between the U.S.-Canadian border and the Okpilak-Hulahula River Delta for the time period 1947 to 2003
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for sheltered shorelines between the U.S.-Canadian border and the Okpilak-Hulahula River Delta for the time period 1947 to 2003
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Shorelines for the northern Alaska coastal region used in shoreline change analysis, 1947 to 2003
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Offshore baseline for the northern Alaska coastal region generated to calculate shoreline change rates along exposed coastlines between Point Barrow and Icy Cape for the time period 1947 to 2012
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for exposed shorelines between Point Barrow and Icy Cape for the time period 1947 to 2012
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
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Offshore baseline for the northern Alaska coastal region generated to calculate shoreline change rates along sheltered coastlines between Point Barrow and Icy Cape for the time period 1947 to 2012
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
Info |
Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for sheltered shorelines between Point Barrow and Icy Cape for the time period 1947 to 2012
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
Info |
Shorelines for the northern Alaska coastal region used in shoreline change analysis, 1947 to 2012
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
Info |
Offshore baseline for the northern Alaska coastal region generated to calculate shoreline change rates along exposed coastlines between the Colville River Delta and Point Barrow for the time period 1947 to 2005
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
Info |
Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for exposed shorelines between the Colville River Delta and Point Barrow for the time period 1947 to 2005
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
Info |
WestBeaufort_sheltered_baselines.shp - Offshore baseline for the northern Alaska coastal region generated to calculate shoreline change rates along sheltered coastlines between the Colville River Delta and Point Barrow for the time period 1947 to 2005
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
Info |
Digital Shoreline Analysis System (DSAS) version 4.3 transects with end-point rate calculations for sheltered shorelines between the Colville River Delta and Point Barrow for the time period 1947 to 2005
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
Info |
Shorelines for the northern Alaska coastal region used in shoreline change analysis, 1947 to 2005
The Arctic Coastal Plain of northern Alaska is an area of strategic economic importance to the United States, is home to remote Native American communities, and encompasses unique habitats of global significance. Coastal erosion along the north coast of Alaska is chronic, widespread, may be accelerating, and is threatening defense and energy-related infrastructure, natural shoreline habitats, and Native communities. There is an increased demand for accurate information regarding past and present shoreline ... |
Info |
CENCAL1853_1910 - Vectorized Shoreline of Central California Derived from 1853-1910 Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
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CENCAL1929_1942 - Vectorized Shoreline of Central Califonia Derived from 1929-1942 Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
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CENCAL1945_1976 - Vectorized Shoreline of Central California Derived from 1945-1976 Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
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CENCAL_1998_2002 - Vectorized Shoreline of Central California Derived from 1998-2002 Lidar Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
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CENCAL_BASELINE - Offshore Baseline for Central California Generated to Calculate Shoreline Change Rates
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
CENCAL_BIASVALUES - Central California Shoreline Bias Values
The USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. These shorelines were used to calculate long-term and short-term change rates in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS ... |
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CENCAL_INTERSECTS_LT - Long-Term Transect-Shoreline Intersection Points for Central California Generated to Calculate Shoreline Change Rates
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
CENCAL_INTERSECTS_ST - Short-Term Transect-Shoreline Intersection Points for Central California Generated to Calculate Shoreline Change Rates
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
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CENCAL_TRANSECTS_LT - Long-Term Shoreline Change Rates for Central California Generated at a 50 m Transect Spacing, 1853-2002
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
CENCAL_TRANSECTS_ST - Short-Term Shoreline Change Rates for Central California Generated at a 50m Transect Spacing, 1971-1998
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
NORCAL1854_1880 - Vectorized Shoreline of Northern California from 1854-1880 Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
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NORCAL1928_1936 - Vectorized Shoreline of Northern California Derived from 1928-1936 Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a compilation of data from one or ... |
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NORCAL1952_1971 - Vectorized Shoreline of Northern California Derived from 1952-1971 Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
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NORCAL2002 - Vectorized Shoreline of Northern California Derived from 2002 Lidar Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
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NORCAL_BASELINES - Offshore Baseline for Northern California Generated to Calculate Shoreline Change Rates
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
NORCAL_BIASVALUES - Northern California Shoreline Bias Values
The USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. These shorelines were used to calculate long-term and short-term change rates in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS ... |
Info |
NORCAL_INTERSECTS_LT - Long-Term Transect-Shoreline Intersection Points for Northern California Generated to Calculate Shoreline Change Rates
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
NORCAL_INTERSECTS_ST - Short-Term Transect-Shoreline Intersection Points for Northern California Generated to Calculate Shoreline Change Rates
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
NORCAL_TRANSECTS_LT - Long-Term Shoreline Change Rates for Northern California Generated at a 50 m Transect Spacing, 1854-2002
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
NORCAL_TRANSECTS_ST - Short-Term Shoreline Change Rates for Northern California Generated at a 50m Transect Spacing, 1952-2002
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
SOCAL1852_1889 - Vectorized Shoreline of Southern California Derived from 1852-1889 Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
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SOCAL1920_1934 - Vectorized Shoreline of Southern California Derived from 1920-1934 Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
Info |
SOCAL_1971_1976 - Vectorized Shoreline of Southern California Derived from 1971-1976 Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
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SOCAL_1998 - Vectorized Shoreline of Southern California Derived from 1998 Lidar Source Data
There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ... |
Info |
SOCAL_BASELINE - Offshore Baseline for Southern California Generated to Calculate Shoreline Change Rates
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
SOCAL_BIASVALUES - Southern California Shoreline Bias Values
The USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. These shorelines were used to calculate long-term and short-term change rates in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS ... |
Info |
SOCAL_INTERSECTS_LT - Long-Term Transect-Shoreline Intersection Points for Southern California Generated to Calculate Shoreline Change Rates
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
SOCAL_INTERSECTS_ST - Short-Term Transect-Shoreline Intersection Points for Southern California Generated to Calculate Shoreline Change Rates
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
SOCAL_TRANSECTS_LT - Long-Term Shoreline Change Rates for Southern California Generated at a 50m Transect Spacing, 1852-1998
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
SOCAL_TRANSECTS_ST - Short-Term Shoreline Change Rates for Southern California Generated at a 50m Transect Spacing, 1971-1998
Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ... |
Info |
Baseline coastal oblique aerial photographs collected from Navarre, Florida, to the Chandeleur Islands, Louisiana, and from Grand Point, Alabama, to St. Joseph Point, Mississippi, June 6, 2006
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 6, 2006, the USGS conducted an oblique aerial photographic survey from Navarre, Florida, to the Chandeleur Islands, Louisiana, and from Grand Point, Alabama, to St. Joseph Point, Mississippi, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore ... |
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Baseline coastal oblique aerial photographs collected from Dauphin Island, Alabama, to Breton Island, Louisiana, September 26–27, 2006
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 26-27, 2006, the USGS conducted an oblique aerial photographic survey from Dauphin Island, Alabama, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ... |
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Baseline coastal oblique aerial photographs collected from the Harney River, Everglades National Park, Florida to Anclote Key, Florida, November 14, 2006
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On November 14, 2006, the USGS conducted an oblique aerial photographic survey from the Harney River, Everglades National Park, Florida to Anclote Key, Florida, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect ... |
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Baseline coastal oblique aerial photographs collected from Dauphin Island, Alabama, to Breton Island, Louisiana, July 26–27, 2007
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On July 26-27, 2007, the USGS conducted an oblique aerial photographic survey from Dauphin Island, Alabama, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ... |
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Baseline coastal oblique aerial photographs collected from False Cape State Park, Virginia, to Myrtle Beach, South Carolina, May 6, 2008
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On May 6, 2008, the USGS conducted an oblique aerial photographic survey from False Cape State Park, Virginia, to Myrtle Beach, South Carolina, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission (08CH01) was conducted to collect data ... |
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Baseline coastal oblique aerial photographs collected from Dog Island, Florida, to Breton Island, Louisiana, June 24–25, 2008
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 24–25, 2008, the USGS conducted an oblique aerial photographic survey from Dog Island, Florida, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental ... |
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Post-Hurricane Gustav coastal oblique aerial photographs collected from the Chandeleur Islands, Louisiana, to Isles Dernieres Barrier Islands Refuge, Louisiana, September 4, 2008
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 4, 2008, the USGS conducted an oblique aerial photographic survey from the Chandeleur Islands, Louisiana, to Isles Dernieres Barrier Islands Refuge, Louisiana, aboard a Beechcraft Super King Air 200 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted ... |
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Baseline coastal oblique aerial photographs collected at the Chandeleur Islands, Louisiana, and Dauphin Island, Alabama, July 24, 2010
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On July 24, 2010, the USGS conducted an oblique aerial photographic survey at the Chandeleur Islands, Louisiana, and Dauphin Island, Alabama, aboard a Beechcraft BE90 King Air aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ... |
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Baseline coastal oblique aerial photographs collected from Breton Island to the Chandeleur Islands, Louisiana, September 3, 2010
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 3, 2010, the USGS conducted an oblique aerial photographic survey from Breton Island to the Chandeleur Islands, Louisiana, aboard a Cessna 210 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the ... |
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Baseline Coastal oblique aerial photographs collected from Horseshoe Beach, Florida, to East Cape, Florida, May 19-20, 2010
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On May 19-20, 2010, the USGS conducted an oblique aerial photographic survey from Horseshoe Beach, Florida, to East Cape, Florida, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes ... |
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Baseline coastal oblique aerial photographs collected from Tampa Bay to the Marquesas Keys, Florida, June 22–23, 2010
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 22–23, 2010, the USGS conducted an oblique aerial photographic survey from Tampa Bay to the Marquesas Keys, Florida, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in ... |
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Baseline coastal oblique aerial photographs collected at Breton Island and the Chandeleur Islands, Louisiana, January 22, 2011
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On January 22, 2011, the USGS conducted an oblique aerial photographic survey at Breton Island and the Chandeleur Islands, LA, aboard a Cessna 210 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the beach and ... |
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Baseline coastal oblique aerial photographs collected from Ponte Vedra, Florida, to the South Carolina/North Carolina border, August 24, 2011
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On August 24, 2011, the USGS conducted an oblique aerial photographic survey from Ponte Vedra, Florida, to the South Carolina/North Carolina border, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ... |
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Baseline coastal oblique aerial photographs collected from Navarre Beach, Florida, to Breton Island, Louisiana, September 7, 2016
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 7, 2016, the USGS conducted an oblique aerial photographic survey from Navarre Beach, Florida, to Breton Island, Louisiana, aboard a Maule MT57 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the ... |
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Post-Hurricane Matthew coastal oblique aerial photographs collected from Port St. Lucie, Florida, to Kitty Hawk, North Carolina, October 13–15, 2016
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On October 13–15, 2016, the USGS conducted an oblique aerial photographic survey from Port St. Lucie, Florida, to Kitty Hawk, North Carolina, aboard a Cessna 182 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes ... |
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Baseline coastal oblique aerial photographs collected U.S. Army Corps of Engineers Field Research Facility, Duck, North Carolina, June 9, 2017
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 09, 2017, the USGS conducted an oblique aerial photographic survey of the U.S. Army Corps of Engineers Field Research Facility (USACE FRF), located in Duck, North Carolina, aboard a Cessna 182 aircraft at an altitude of approximately 1000 feet (ft). This mission was conducted to collect data for USACE FRF ... |
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Baseline coastal oblique aerial photographs collected from Fenwick Island State Park, Delaware, to Corolla, North Carolina, March 27, 1998
The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On March 27, 1998, the USGS conducted an oblique aerial photographic survey from Fenwick Island State Park, Delaware, to Corolla, North Carolina, aboard a U.S. Coast Guard HH60 Helicopter at an altitude of 500 feet (ft) and approximately 1,000 ft offshore. This mission was conducted to collect data for assessing ... |
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Subtropical Storm Alberto Assessment of Potential Coastal Change Impacts: NHC Advisory 8, 0800 AM EDT SUN MAY 27 2018
This dataset defines storm-induced coastal erosion hazards for the Louisiana, Mississippi, Alabama and Florida coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Subtropical Storm Alberto in May 2018. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the ... |
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Tropical Storm Bill Assessment of Potential Coastal-Change Impacts: NHC Advisory 2, 0900 AM UTC MON JUN 16 2015
This dataset defines storm-induced coastal erosion hazards for the Texas and Louisiana coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Tropical Storm Bill in June 2015. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the three types of coastal change: ... |
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1869 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
1869 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83) consists of vector shoreline data that were derived from a set of National Ocean Service (NOS) raster shoreline maps (often called T-sheet or TP-sheet maps) created for Breton Island in 1869. In 2002, NOAA published digitized shorelines for T-sheet (T-1097), which were subsequently edited by USGS staff for input into the Digital Shoreline Analysis System (DSAS) Version 4.0, where area and shoreline change analyses could be conducted. |
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1922 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
1922 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83) consists of vector shoreline data that were derived from a set of National Ocean Service (NOS) raster shoreline maps (often called T-sheet or TP-sheet maps) created for Breton Island in 1922. In 2002, NOAA published digitized shorelines for T-sheet (T-3920), which were subsequently edited by USGS staff for input into the Digital Shoreline Analysis System (DSAS) Version 4.0, where area and shoreline change analyses could be conducted. |
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1950 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
1950 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83) consists of vector shoreline data that were derived from a set of National Ocean Service (NOS) raster shoreline maps (often called T-sheet or TP-sheet maps) created for Breton Island in 1950. In 2002, NOAA published digitized shorelines for T-sheet (T-9393), which were subsequently edited by USGS staff for input into the Digital Shoreline Analysis System (DSAS) Version 4.0, where area and shoreline change analyses could be conducted. |
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1983 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
Shorelines were derived from the National High Altitude Photography (NHAP) program. The NHAP was coordinated by the U.S. Geological Survey as an interagency project to acquire cloud-free aerial photographs at a specific altitude above mean terrain elevation. Two different camera systems were used to obtain simultaneous coverage of black-and-white (BW) and color infrared (CIR) aerial photographs over the conterminous United States. Black-and-white aerial photographs were obtained on 9-inch film from an ... |
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1998 Digitized Shoreline for Breton Island, Louisiana(Geographic, NAD83)
Shorelines were derived from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center's Digital Orthophoto Quarter Quads (DOQQ) images collected on January 24, 1998. This dataset contains digitized shorelines created from the USGS imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis using the Digital Shoreline Analysis System (DSAS) Version 4.0. |
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2001 Vectorized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
A first-surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements collected by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA) on September 07-09, 2001. Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft ... |
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2004 Digitized Shoreline for Breton Island, Louisiana(Geographic, NAD83)
Shorelines were derived from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center’s Digital Orthophoto Quarter Quads (DOQQ) images collected on January 20, 2004. This dataset contains digitized shorelines created from the USGS imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis, using the Digital Shoreline Analysis System (DSAS) version 4.0. |
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2005 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
Shorelines were derived from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center’s Digital Orthophoto Quadrangle (DOQ) images collected on November 17, 2005. This dataset contains digitized shorelines created from the USGS imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis, using the Digital Shoreline Analysis System (DSAS) version 4.0. |
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2007 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
Shorelines were derived from the National Agriculture Imagery Program (NAIP) digital ortho imagery collected on October 11, 2007. This dataset contains digitized shorelines created from the NAIP imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis using the Digital Shoreline Analysis System (DSAS) Version 4.0. |
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2008 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
Shorelines were derived from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center high-resolution orthorectified images collected on October 01, 2008. This dataset contains digitized shorelines created from the USGS imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis, using the Digital Shoreline Analysis System (DSAS) Version 4.0. |
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2010 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
Shorelines were derived from the National Agriculture Imagery Program (NAIP) digital ortho imagery collected on May 10, 2010. This dataset contains digitized shorelines created from the NAIP imagery for Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis using the Digital Shoreline Analysis System (DSAS) version 4.0. |
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2012 Digitized Shoreline for Breton Island, Louisiana(Geographic, NAD83)
Shorelines were derived from a U.S. Geological Survey Earth Resources Observations and Science Center (EROS) high-resolution orthorectified image that was collected on October 20, 2012 over Breton Island, Louisiana. Shorelines were digitized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis using the Digital Shoreline Analysis System (DSAS) version 4.0. |
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2013 Vectorized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
Shorelines were derived from a U.S. Geological Survey topographic lidar survey that was conducted on July 12-14, 2013 over Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana and published in USGS Data Series 838. Photo Science, Inc., was contracted by the USGS to collect and process these data. Lidar data were acquired around portions of both the Alabama and Louisiana barrier islands; however, this dataset only contains shorelines created from data acquired from ... |
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2014 Vectorized Shoreline for Breton Island, Louisiana (Geographic, NAD83)
Shorelines were derived from a U.S. Geological Survey topographic lidar survey that was conducted on January 16-18, 2014 over Breton Island, Louisiana and released under USGS field activity number 14LGC01. Quantum Spatial was contracted by the USGS to collect and process these data. This dataset contains vectorized shorelines created from data acquired from Breton Island, Louisiana. Shorelines were vectorized in ArcMap 10.2.2 so they could be used for area and shoreline change analysis, using the Digital ... |
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Tropical Storm Colin Assessment of Potential Coastal Change Impacts: NHC Advisory 4, 0500 AM EDT MON JUN 06 2016
This dataset defines storm-induced coastal erosion hazards for the Florida coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Tropical Storm Colin in June 2016. Storm-induced water levels, due to both surge and waves, are compared to beach and dune elevations to determine the probabilities of the three types of coastal change: collision ... |
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P07_Oct2012_Oct2014: Hurricane Sandy Beach Response and Recovery at Fire Island, New York: Shoreline and Beach Profile Data, October 2012 to October 2014.
This spreadsheet consists of Fire Island, NY pre- and post- storm cross-shore profiles collected from October 2012 to October 2014. This dataset contains a set of cross-shore profiles covering 16 dates from October 28 2012 to October 07 2014. As part of the assessment of beach and dune morphologic change associated with Hurricane Sandy and the series of winter storms that followed, DGPS elevation data were collected along ten shore-perpendicular profiles extending from just inland of the crest of the dune ... |
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P08_Oct2012_Oct2014: Hurricane Sandy Beach Response and Recovery at Fire Island, New York: Shoreline and Beach Profile Data, October 2012 to October 2014.
This spreadsheet consists of Fire Island, NY pre- and post- storm cross-shore profiles collected from October 2012 to October 2014. This dataset contains a set if cross-shore profiles covering 16 dates from October 28 2012 to October 07 2014. As part of the assessment of beach and dune morphologic change associated with Hurricane Sandy and the series of winter storms that followed, DGPS elevation data were collected along ten shore-perpendicular profiles extending from just inland of the crest of the dune ... |
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P09_Oct2012_Oct2014: Hurricane Sandy Beach Response and Recovery at Fire Island, New York: Shoreline and Beach Profile Data, October 2012 to October 2014.
This spreadsheet consists of Fire Island, NY pre- and post- storm cross-shore profiles collected from October 2012 to October 2014. This dataset contains a set of cross-shore profiles covering 16 dates from October 28 2012 to October 07 2014. As part of the assessment of beach and dune morphologic change associated with Hurricane Sandy and the series of winter storms that followed, DGPS elevation data were collected along ten shore-perpendicular profiles extending from just inland of the crest of the dune ... |
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P10_Nov2012_Oct2014: Fire Island, NY pre- and post- storm cross-shore profiles from November 2012 to October 2014.
This spreadsheet consists of Fire Island, NY pre- and post- storm cross-shore profiles collected from November 2012 to October 2014. This dataset contains a set of cross-shore profiles covering 14 dates from November 04 2012 to October 07 2014. As part of the assessment of beach and dune morphologic change associated with Hurricane Sandy and the series of winter storms that followed, DGPS elevation data were collected along ten shore-perpendicular profiles extending from just inland of the crest of the dune ... |
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P11_Oct2012_Oct2014: Hurricane Sandy Beach Response and Recovery at Fire Island, New York: Shoreline and Beach Profile Data, October 2012 to October 2014.
This spreadsheet consists of Fire Island, NY pre- and post- storm cross-shore profiles collected from October 2012 to October 2014. This dataset contains a set of cross-shore profiles covering 15 dates from October 28 2012 to October 07 2014. As part of the assessment of beach and dune morphologic change associated with Hurricane Sandy and the series of winter storms that followed, DGPS elevation data were collected along ten shore-perpendicular profiles extending from just inland of the crest of the dune ... |
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P22_Oct2012_Oct2014: Hurricane Sandy Beach Response and Recovery at Fire Island, New York: Shoreline and Beach Profile Data, October 2012 to October 2014.
This spreadsheet consists of Fire Island, NY pre- and post- storm cross-shore profiles collected from October 2012 to October 2014. This dataset contains a set of cross-shore profiles covering 16 dates from October 28 2012 to October 07 2014. As part of the assessment of beach and dune morphologic change associated with Hurricane Sandy and the series of winter storms that followed, DGPS elevation data were collected along ten shore-perpendicular profiles extending from just inland of the crest of the dune ... |
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P23_Oct2012_Oct2014: Hurricane Sandy Beach Response and Recovery at Fire Island, New York: Shoreline and Beach Profile Data, October 2012 to October 2014.
This spreadsheet consists of Fire Island, NY pre- and post- storm cross-shore profiles collected from October 2012 to October 2014. This dataset contains a set of cross-shore profiles covering 16 dates from October 28 2012 to October 07 2014. As part of the assessment of beach and dune morphologic change associated with Hurricane Sandy and the series of winter storms that followed, DGPS elevation data were collected along ten shore-perpendicular profiles extending from just inland of the crest of the dune ... |
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P24_Oct2012_Oct2014: Hurricane Sandy Beach Response and Recovery at Fire Island, New York: Shoreline and Beach Profile Data, October 2012 to October 2014.
This spreadsheet consists of Fire Island, NY pre- and post- storm cross-shore profiles collected from October 2012 to October 2014. This dataset contains a set of cross-shore profiles covering 16 dates from October 28 2012 to October 07 2014. As part of the assessment of beach and dune morphologic change associated with Hurricane Sandy and the series of winter storms that followed, DGPS elevation data were collected along ten shore-perpendicular profiles extending from just inland of the crest of the dune ... |
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P25_Oct2012_Oct2014: Hurricane Sandy Beach Response and Recovery at Fire Island, New York: Shoreline and Beach Profile Data, October 2012 to October 2014.
This spreadsheet consists of Fire Island, NY pre- and post- storm cross-shore profiles collected from October 2012 to October 2014. This dataset contains a set of cross-shore profiles covering 16 dates from October 28 2012 to October 07 2014. As part of the assessment of beach and dune morphologic change associated with Hurricane Sandy and the series of winter storms that followed, DGPS elevation data were collected along ten shore-perpendicular profiles extending from just inland of the crest of the dune ... |
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P26_Oct2012_Oct2014: Hurricane Sandy Beach Response and Recovery at Fire Island, New York: Shoreline and Beach Profile Data, October 2012 to October 2014.
This spreadsheet consists of Fire Island, NY pre- and post- storm cross-shore profiles collected from October 2012 to October 2014. This dataset contains a set of cross-shore profiles covering 16 dates from October 28 2012 to October 07 2014. As part of the assessment of beach and dune morphologic change associated with Hurricane Sandy and the series of winter storms that followed, DGPS elevation data were collected along ten shore-perpendicular profiles extending from just inland of the crest of the dune ... |
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Shorelines_Oct2012_Sept2014: Hurricane Sandy Beach Response and Recovery at Fire Island, New York: Shoreline and Beach Profile Data, October 2012 to October 2014.
This shapefile consists of Fire Island, NY pre- and post-storm shoreline data collected from October 2012 to September 2014. This dataset contains 13 Mean High Water (MHW) shorelines for Fire Island, NY (A total of 15 dates, where two shorelines were collected over multiple days). Prior to and following Hurricane Sandy in October, 2012, continuous alongshore DGPS data were collected to assess the positional changes of the shoreline (MHW - 0.46 m NAVD88) and the upper portion of the beach. Over the course of ... |
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Hurricane Florence Assessment of Potential Coastal Change Impacts: NHC Advisory 57, 1100 AM EDT THU SEP 13 2018
This dataset defines storm-induced coastal erosion hazards for the Georgia, South Carolina, North Carolina, Virginia, Maryland, Delaware, New Jersey and New York coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Florence in September 2018. Storm-induced water levels, due to both surge and waves, were compared to beach and dune ... |
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Tropical Storm Gordon Assessment of Potential Coastal Change Impacts: NHC Advisory 8, 0700 AM CDT TUE SEP 04 2018
This dataset defines storm-induced coastal erosion hazards for the Louisiana, Mississippi, Alabama and Florida coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Tropical Storm Gordon in September 2018. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the ... |
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Hurricane Harvey Assessment of Potential Coastal Change Impacts: NHC Advisory 020, 700 AM CDT FRI AUG 25 2017
This dataset defines storm-induced coastal erosion hazards for the Texas and Louisiana coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Harvey in August 2017. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the three types of coastal change: ... |
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Tropical Storm Hermine Assessment of Potential Coastal Change Impacts: NHC Advisory 20, 0500 AM EDT FRI SEP 02 2016
This dataset defines storm-induced coastal erosion hazards for the Florida coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Tropical Storm Hermine in September 2016. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the three types of coastal change: ... |
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iCoast - Did the Coast Change? Crowd-sourced Coastal Classifications
On October 29, 2012, Hurricane Sandy made landfall as a post-tropical storm near Brigantine, New Jersey, with sustained winds of 70 knots (80 miles per hour) and tropical-storm-force winds extending 870 nautical miles in diameter (Blake and others, 2013). The effects of Hurricane Sandy’s winds and storm surge included erosion of the beaches and dunes as well as breaching of barrier islands in both natural and heavily developed areas of the coast (Spokin et. al., 2014). On November 4-6, 2012, the U.S. ... |
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Hurricane Irma Assessment of Potential Coastal Change Impacts: NHC Advisory 41, 800 AM EDT SAT SEPT 9 2017
This dataset defines storm-induced coastal erosion hazards for the Florida, Georgia and South Carolina coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Irma in September 2017. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the three types of ... |
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Extratropical Storm Jan2016 Assessment of Potential Coastal Change Impacts: 1200 PM EST FRI JAN 22 2016
This dataset defines storm-induced coastal erosion hazards for the Virginia, Maryland, Delaware, New Jersey and New York coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct impact of the Extratropical Storm in January 2016. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities ... |
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Hurricane Joaquin Assessment of Potential Coastal Change Impacts: NHC Advisory 27, 0800 AM EDT SUN OCT 04 2015
This dataset defines storm-induced coastal erosion hazards for the North Carolina, Virginia, Maryland, Delaware, New Jersey, New York, Rhode Island and Massachusetts coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Joaquin in October 2015. Storm-induced water levels, due to both surge and waves, were compared to beach and dune ... |
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Extratropical Storm March 2018 Assessment of Potential Coastal Change Impacts: 0800 AM EST FRI MAR 02 2018
This dataset defines storm-induced coastal erosion hazards for the North Carolina, Virginia, Maryland, Delaware, New Jersey, New York, Rhode Island, Massachusetts, New Hampshire and Maine coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of an Extratropical Storm in March 2018. Storm-induced water levels, due to both surge and waves, were ... |
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Hurricane Maria Assessment of Potential Coastal Change Impacts: NHC Advisory 41, 0800 AM EDT TUE SEPT 26 2017
This dataset defines storm-induced coastal erosion hazards for the North Carolina, Virginia, Maryland and Delaware coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Maria in September 2017. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the ... |
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Hurricane Matthew Assessment of Potential Coastal Change Impacts: NHC Advisory 037, 800 AM EDT FRI OCT 07 2016
This dataset defines storm-induced coastal erosion hazards for the Florida, Georgia, South Carolina and North Carolina coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Matthew in October 2016. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polyline: Combined Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polyline: Combined Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (dates_meta.txt)
Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polygon: Combined Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polygon: Combined Dates) is a polygon shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polygon: Individual Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polygon: Individual Dates) is a dataset consisting of 268 polygon shapefiles representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polyline: Combined Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polyline: Combined Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polyline: Individual Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polygon: Combined Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polygon: Combined Dates) is a polygon shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polygon: Individual Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polygon: Individual Dates) is a dataset consisting of 223 polygon shapefiles representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polyline: Combined Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polyline: Combined Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polyline: Individual Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polygon: Combined Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polygon: Combined Dates) is a polygon shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polygon: Individual Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polygon: Individual Dates) is a dataset consisting of 254 polygon shapefiles representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polyline: Combined Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polyline: Combined Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polyline: Individual Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polygon: Combined Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polygon: Combined Dates) is a polygon shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polygon: Individual Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polygon: Individual Dates) is a dataset consisting of 271 polygon shapefiles representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polyline: Combined Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polyline: Combined Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polyline: Individual Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polygon: Combined Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polygon: Combined Dates) is a polygon shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ... |
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Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polygon: Individual Dates)
Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polygon: Individual Dates) is a dataset consisting of 280 polygon shapefiles representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from ... |
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Hurricane Michael Assessment of Potential Coastal Change Impacts: NHC Advisory 15, 0400 AM CDT WED OCT 10 2018
This dataset defines storm-induced coastal erosion hazards for the Alabama and Florida coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Michael in October 2018. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the three types of coastal change: ... |
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Hurricane Nate Assessment of Potential Coastal Change Impacts: NHC Advisory 12, 0800 AM EDT SAT OCT 07 2017
This dataset defines storm-induced coastal erosion hazards for the Louisiana, Mississippi, Alabama and Florida coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Nate in October 2017. Storm-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the probabilities of the three ... |
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Experimental coral-growth rate, reef survey, and time-series imagery data collected between 1998 and 2017 to investigate construction and erosion of Orbicella coral reefs in the Florida Keys, U.S.A.
The USGS Coral Reef Ecosystems Studies project (https://coastal.er.usgs.gov/crest/) provides science that helps resource managers tasked with the stewardship of coral reef resources. This data release contains data on coral-growth rates for Orbicella sp. coral colonies grown at five sites on the Florida Keys reef tract from 2013 to 2015, survey data for census-based carbonate budgeting at Hen and Chickens Reef (Islamorada, Florida) collected in 2017, and time-series photographs taken of permanent markers ... |
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Hurricane Sandy Assessment of Potential Coastal Change Impacts: NHC Advisory 29, 1100 AM EDT MON OCT 29 2012
This dataset defines hurricane-induced coastal erosion hazards for the Delaware, Maryland, New Jersey, New York, and Virginia coastline. The analysis was based on a storm-impact scaling model that used observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast would respond to the direct landfall of Hurricane Sandy in October 2012. Hurricane-induced water levels, due to both surge and waves, were compared to beach and dune elevations to determine the ... |
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Transects_BackBarrier.shp - Digital Shoreline Analysis System version 4.3 Transects with Linear Regression Rate Calculations for the Back-Barrier (North-Facing) coast of Dauphin Island, Alabama.
Rates of shoreline change for Dauphin Island, Alabama were generated for three analysis periods, using two different shoreline proxy datasets. Mean High Water line (MHW) shorelines were generated from 14 lidar datasets (1998-2014) and Wet Dry Line (WDL) shorelines were digitized from ten sets of georeferenced aerial images (1940-2015). Rates of change were generated for three groups of shorelines: MHW (lidar), WDL (aerial) and MHW and WDL shorelines combined. These data will aid in developing an ... |
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National Assessment of Hurricane-Induced Coastal Erosion Hazards: 2021 Update
This dataset contains information on the probabilities of hurricane-induced erosion (collision, inundation and overwash) for each 1-kilometer (km) section of the United States [Gulf of Mexico and Atlantic] coast for category 1-5 hurricanes. The analysis is based on a storm-impact scaling model that uses observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to the direct landfall of category 1-5 hurricanes. Hurricane-induced water levels, due ... |
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Long-term shoreline change rates for Rincon, Puerto Rico 1936-2006 (lt_transects.shp)
The 8 km of shoreline from Punta Higüero to Punta Cadena in Rincón, Puerto Rico is experiencing long-term coastal erosion. This study documents historical shoreline changes at Rincón for the period 1936-2006. Thirteen historical shoreline positions were compiled from existing data, new orthophotography, and GPS field surveys. Shoreline vectors represent the high water line at the time of the survey. |
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Short-term shoreline change rates for Rincon, Puerto Rico 1994-2006 (st_transects.shp)
The 8 km of shoreline from Punta Higüero to Punta Cadena in Rincón, Puerto Rico is experiencing long-term coastal erosion. This study documents historical shoreline changes at Rincón for the period 1936-2006. Thirteen historical shoreline positions were compiled from existing data, new orthophotography, and GPS field surveys. Shoreline vectors represent the high water line at the time of the survey. |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cedar Island, VA, 2012–2013
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cedar Island, VA, 2013–2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2013–2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fire Island, NY, 2010–2011
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fire Island, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fire Island, NY, 2014–2015
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rockaway Peninsula, NY, 2010–2011
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rockaway Peninsula, NY, 2012
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rockaway Peninsula, NY, 2013–2014
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ... |
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Faults--Offshore of Bodega Head Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Bodega Head map area, California. The vector data file is included in "Faults_OffshoreBodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., ... |
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Folds--Offshore of Bodega Head Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Bodega Head map area, California. The vector data file is included in "Folds_OffshoreBodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., ... |
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Faults--Offshore of Bolinas Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Bolinas map area, California. The vector data file is included in "Faults_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., ... |
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Faults--Offshore of Half Moon Bay Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Half Moon Bay map area, California. The vector data file is included in "Faults_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L. ... |
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Faults--Offshore of Pacifica map area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Pacifica map area, California. The vector data file is included in "Faults_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, ... |
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Faults--Offshore of Salt Point Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Salt Point map area, California. The vector data file is included in "Faults_OffshoreSaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter ... |
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Faults--Offshore of San Francisco Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore San Francisco map area, California. The vector data file is included in "Faults_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W ... |
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Faults--Offshore of San Gregorio Map Area, California
This part of SIM 3306 presents data for the faults for the geologic and geomorphic map of the Offshore of San Gregorio map area, California. The vector data file is included in "Faults_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., ... |
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Faults--Offshore of Fort Ross Map Area, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Fort Ross map area, California. The vector data file is included in "Faults_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., ... |
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Faults--Offshore of Point Reyes Map Area, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Point Reyes map area, California. The vector data file is included in "Faults_OffshorePointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C ... |
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Faults--Offshore of Carpinteria, California
This part of DS 781 presents data for fault data for the Offshore of Carpinteria map area, California. The vector data file is included in "Faults_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., ... |
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Faults--Offshore of Coal Oil Point, California
This part of DS 781 presents fault data for the Offshore of Coal Oil Point map area, California. The vector data file is included in "Faults_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., ... |
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Faults--Offshore Refugio Beach, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Refugio Beach map area, California. The vector data file is included in "Faults_OffshoreRefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H ... |
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Faults--Offshore of Santa Barbara, California
This part of DS 781 presents fault data for the Offshore of Santa Barbara map area, California. The vector data file is included in "Faults_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., ... |
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Faults--Offshore of Tomales Point Map Area, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Offshore of Tomales Point map area, California. The vector data file is included in "Faults_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M ... |
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Faults--Offshore of Ventura, California
This part of SA 781 presents fault data for the Offshore of Ventura map area, California. The vector data file is included in "Faults_OffshoreVentura.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M ... |
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Faults--Punta Gorda to Point Arena, California
This part of DS 781 presents data for the faults of the Punta Gorda to Point Arena, California, region. The vector data file is included in the "Faults_PuntaGordaToPointArena.zip," which is accessible from https://doi.org/10.5066/P9PNNI9H. Faults in the Punta Gorda and Point Arena region are identified on seismic-reflection data based on abrupt truncation or warping of reflections and (or) juxtaposition of reflection panels with different seismic parameters such as reflection presence, amplitude, frequency, ... |
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Faults--Punta Gorda to Point Arena, California
This part of DS 781 presents data for the faults of the Punta Gorda to Point Arena, California, region. The vector data file is included in the "Faults_PuntaGordaToPointArena.zip," which is accessible from https://doi.org/10.5066/P9PNNI9H. Faults in the Punta Gorda and Point Arena region are identified on seismic-reflection data based on abrupt truncation or warping of reflections and (or) juxtaposition of reflection panels with different seismic parameters such as reflection presence, amplitude, frequency, ... |
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Faults--Drakes Bay and Vicinity, California
This part of DS 781 presents data of faults for the geologic and geomorphologic map of the Drakes Bay and Vicinity map area, California. The vector data file is included in "Faults_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., ... |
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Faults--Hueneme Canyon and Vicinity, California
This part of DS 781 presents data for faults for the geologic and geomorphic map of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Faults_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K ... |
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Faults--Offshore of Monterey, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Monterey map area, California. The vector data file is included in "Faults_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, ... |
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Faults--Offshore Pigeon Point, California
This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore Pigeon Point map area, California. The vector data file is included in "Faults_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., ... |
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Faults--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore of Scott Creek map area, California. The vector data file is included in "Faults_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., ... |
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Faults--Offshore of Aptos Map Area, California
This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore Aptos map area, California. The vector data file is included in "Faults_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, ... |
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Faults--Offshore of Point Conception Map Area, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Faults_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series� ... |
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Faults--Offshore of Gaviota Map Area, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Gaviota map area, California. The vector data file is included in "Faults_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota ... |
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Faults--Offshore Santa Cruz, California
This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore of Santa Cruz map area, California. The vector data file is included in "Faults_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., ... |
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Faults--Monterey Canyon and Vicinity Map Area, California
This part of DS 781 presents fault data for the geologic and geomorphic map of the Monterey Canyon and Vicinity map area, California. The vector data file is included in "Faults_MontereyCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/MontereyCanyon/data_catalog_MontereyCanyon.html. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G. ... |
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Faults—Point Sur to Point Arguello, California
This part of DS 781 presents data for the faults of the Point Sur to Point Arguello, California, region. The vector data file is included in the “Faults_PointSurToPointArguello.zip,” which is accessible from https://doi.org/10.5066/P97CZ0T7. Faults in the Point Sur to Point Arguello region are identified on seismic-reflection data based on abrupt truncation or warping of reflections and (or) juxtaposition of reflection panels with different seismic parameters such as reflection presence, amplitude, ... |
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Lifespan of marsh units in New York salt marshes
Lifespan of salt marshes in New York are calculated using conceptual marsh units defined by Defne and Ganju (2018) and Welk and others (2019, 2020a, 2020b, 2020c). The lifespan calculation is based on estimated sediment supply and sea-level rise (SLR) predictions after Ganju and others (2020). Sea level predictions are local estimates which correspond to the 0.3, 0.5, and 1.0 meter increase in Global Mean Sea Level (GMSL) scenarios by 2100 from Sweet and others (2022). The U.S. Geological Survey has been ... |
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Computed tomography (CT) scans of sediment cores collected offshore southern Cascadia, during field activity 2019-643-FA
This dataset includes computed tomography (CT) scan imagery of sediment cores collected in southern Cascadia (offshore northern California) aboard the M/V Bold Horizon in September-October 2019. |
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Information on sediment cores collected offshore southern Cascadia, during field activity 2019-643-FA
This dataset presents core information such as core IDs, section numbers, lengths, depth intervals, and locations from sediment cores collected in southern Cascadia (offshore northern California) aboard the M/V Bold Horizon in September-October 2019. An inventory of core section CT, MSCL, and photograph scan files available in this data release are listed here. |
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Photographs of sediment cores collected offshore southern Cascadia, during field activity 2019-643-FA
This dataset includes photographs (linescan images) of sediment cores collected in southern Cascadia (offshore northern California) aboard the MV Bold Horizon in September-October 2019. |
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Radiocarbon age data from sediment cores collected offshore southern Cascadia, during field activity 2019-643-FA
This dataset presents radiocarbon data from 87 samples from sediment cores collected in southern Cascadia (offshore northern California) aboard the M/V Bold Horizon in September-October 2019. Sample ages were determined by the National Ocean Sciences Accelerator Mass Spectrometry (NOSAMS) facility and the W.M. Keck Carbon Cycle Accelerator Mass Spectrometry (KCCAMS) facility at the University of California, Irvine (UCI). |
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Elemental chemistry, radionuclides, and charcoal in watershed soil and reef sediment at Olowalu, Maui, 2022
Fine-sediment elemental chemistry, short-lived cosmogenic radionuclides (Beryllium-7, Cesium-137, and Lead-210), charcoal counts, and total organic carbon contents were quantified to describe urban and wildfire effects and land-based sediment sources and runoff to Olowalu Reef in February 2022. |
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Parent and alkylated polycyclic aromatic hydrocarbons (PAHs) in watershed soil and reef sediment at Olowalu, Maui, 2022
Seventy six parent and alkylated polycyclic aromatic compounds, including polycyclic aromatic hydrocarbons (PAHs), were quantified in watershed and reef sediment from Olowalu, Maui, in February 2022 to explore urban and wildfire effects. Sample locations and total organic carbon contents (OC) are available in the accompanying file OlowaluWatershedReef2022_compositions.csv. |
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Sediment grain-size distributions from cores collected in the Salmon River estuary, Oregon
This portion of the data release presents sediment grain-size data from cores and surface samples collected from the Salmon River estuary in 2017 and 2018. In total, 60 samples were collected from 18 sites containing sandy sediment from the circa 1700 CE tsunami deposit, two sites with post-1700 CE silt, and eight modern surface sample sites. The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. The ... |
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Thickness distribution of the most recent sandy tsunami deposit in the Salmon River estuary, Oregon
This portion of the data release provides the spatial thickness distribution of sandy deposits inferred to have been deposited at the Salmon River, OR by a circa 1700 CE tsunami. Data were collected by describing hand-operated gouge cores at 129 sites in 2017 and 2018, and supplemented by 114 core descriptions from 1987 (Nelson and others, 2004). |
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Lifespan of Chesapeake Bay salt marsh units
Lifespan distribution in the Chesapeake Bay (CB) salt marsh complex is presented in terms of lifespan of conceptual marsh units defined by Ackerman and others (2022). The lifespan calculation is based on estimated sediment supply and sea-level rise (SLR) predictions after Ganju and others (2020). Sea level predictions are present day estimates at the prescribed rate of SLR, which correspond to the 0.3, 0.5, and 1.0 meter increase in Global Mean Sea Level (GMSL) scenarios by 2100 from Sweet and others (2022) ... |
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Sediment grain-size distributions from vibracores collected in Searsville Lake, Jasper Ridge Biological Preserve, Stanford, California
This portion of the data release presents sediment grain-size data from vibracores collected from Searsville Lake, Jasper Ridge Biological Preserve, Stanford, California in October 2018 (USGS Field Activity 2018-682-FA). In total, 36 samples were subsampled from two vibracores: JRBP2018-VC01A and JRBP2018-VC01B. The grain-size distributions of samples were determined using standard techniques developed by the USGS Pacific Coastal and Marine Science Center sediment lab. The grain-size data are provided in a ... |
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St. Petersburg Coastal and Marine Science Center Geoscience Data Viewer Metadata
This web mapping application is a compilation of geoscientific data collected and published by the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC). This application does not serve as a complete archive of all the geoscientific data collected by the center, but highlights frequently published data types. Data within this web application include: seismic data extents, seismic survey tracklines (boomer, chirp, and minisparker), bathymetric footprints, bathymetric ... |
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SandSnap grain-size analysis and photos from North Core Banks, NC in October 2022
These data map in high detail surficial cross-sections of North Core Banks, a barrier island in Cape Lookout National Seashore, NC, in October 2022. U.S. Geological Survey field efforts are part of an interagency agreement with the National Park Service to monitor the recovery of the island from Hurricanes Florence (2018) and Dorian (2019). Three sites of outwash, overwash, and pond formation were targeted for extensive vegetation ground-truthing, sediment samples, bathymetric mapping with a remote ... |
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Lifespan of Massachusetts salt marsh units
Lifespan of salt marshes in Massachusetts (MA) are calculated using conceptual marsh units defined by Ackerman and others (2022). The lifespan calculation is based on estimated sediment supply and sea-level rise (SLR) predictions after Ganju and others (2020). Sea level predictions are local estimates which correspond to the 0.3, 0.5, and 1.0 meter increase in Global Mean Sea Level (GMSL) scenarios by 2100 from Sweet and others (2022). The U.S. Geological Survey has been expanding national assessment of ... |
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Percent sand and fines in suspended sediment from water samples from South San Francisco Bay, California, 2021
Water samples were collected in South San Francisco Bay adjacent to Whale’s Tail South marsh on three days from June through December 2021 to analyze for suspended-sediment concentration and the percent of sand and fines in suspended sediment. |
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Grain size and bulk density from Little Holland Tract and Liberty Island, Sacramento-San Joaquin Delta, California, 2015 to 2019 (ver. 3.0, April 2023)
Grain size distribution and bulk density are reported for sediment samples from two flooded agricultural tracts, Little Holland Tract and Liberty Island, in the Sacramento-San Joaquin Delta, California. Samples were repeatedly collected at 8 sites using a Ponar grab or push core samplers during 19 visits to the study area from 2015 to 2019. The long-term time series data collection stations (sites LWA, HVB, HWC, and LVB) were sampled on almost every field survey, and the remaining sites were sampled 6 or ... |
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Attendee Survey Results from the April and May 2020 Gulf Islands National Seashore Workshop
In early 2020, scientists gathered to advance sediment budget modeling efforts by conducting a “Needs Assessment Workshop” for the Gulf Island National Seashore (GINS) to understand the coastal processes affecting island resiliency. The “Gulf Islands Sediment Budget Needs Assessment Workshop” was held, virtually, April 23–24 and May 27–28, 2020. The workshop series was organized by researchers from North Carolina State University in collaboration with National Park Service (NPS) and U.S. ... |
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Sedimentary Environment Map of Long Island Sound
Long Island Sound is one of the largest estuaries along the Atlantic coast of the United States. It is a glacially produced, semi-enclosed, northeast-southwest-trending embayment, which is 150 km long and 30 km across at its widest point. Its mean water depth is approximately 24 m. The eastern end of the Sound opens to the Atlantic Ocean through several large passages between islands, whereas the western end is connected to New York Harbor through a narrow tidal strait. Long Island Sound abuts the New York ... |
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Surface-sediment grain-size distributions of the Elwha River delta, Washington, August 2022
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in August 2022 (USGS Field Activity 2022-638-FA). Surface sediment was collected from 67 locations using a small ponar, or 'grab', sampler from the R/V Frontier in water depths between about 1 and 17 m around the delta. An additional 44 samples were collected by hand at low tide. A hand-held global satellite navigation system (GNSS) receiver was used to determine the locations of ... |
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Sediment size distributions from San Pablo Bay and China Camp Marsh, California
As part of the hydrodynamic and sediment transport investigations in San Pablo Bay and China Camp Marsh, California, particle size distributions of bed sediments were measured at most instrumented stations and are presented in a comma-delimited values spreadsheet. This portion of the data release presents San Pablo Bay and China Camp Marsh sediment particle size distributions from samples collected during multiple instrument deployments. Users are advised to check the data carefully for sampling time, ... |
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Sediment grain-size distributions of three carbonate sand layers in Anahola Valley, Kaua'i, Hawai'i (ver. 2.0, July 2023)
This portion of the data release presents sediment grain-size data from samples collected from Anahola Valley, Kaua`i, Hawai`i in November, 2015 (USGS Field Activity 2015-671-FA). 63 sand and mud samples were taken from sediment cores that were collected using a Russian corer (a hand-held, side-filling peat auger) from two site locations. Site locations were determined using a hand-held global navigation satellite system, GNSS. The grain-size distributions of samples were determined using standard ... |
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In situ seafloor images from the lower Columbia River, Washington and Oregon, 2021
In situ seafloor images were acquired at four sites (SKM, SLG, LDB, WLW) in the lower Columbia River, Washington and Oregon, with an underwater camera system between June 5 and June 8, 2021. Between 248 and 427 digital images of the sediment surface were collected at each site with an underwater camera system that was repeatedly lowered to the seabed along a series of 1 km-long transects oriented along the main navigation channel and spaced about 60 m apart. The camera consisted of a FLIR Blackfly BFS-PGE ... |
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Surface sediment grain size distributions derived from automated image processing of in situ seafloor images from the lower Columbia River, Washington and Oregon, 2021
This dataset contains surface sediment grain size distributions derived from automated image processing of in situ seafloor images obtained with an underwater camera system at four sites (SKM, SLG, LDB, WLW) in the lower Columbia River, Washington and Oregon, in 2021. The surface sediment grain size distribution data are provided in comma-separated text (.csv) format for each site and for data used in calibration and validation of the automated image processing technique. |
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Surface sediment grain size distributions derived from manual point counts of in situ seafloor images from the lower Columbia River, Washington and Oregon, 2021
This dataset contains surface sediment grain size distributions derived from manual point counts of in situ seafloor images obtained with an underwater camera system in the lower Columbia River, Washington and Oregon, in 2021. The distributions derived from manual point counts were compared with results from an automated image processing technique to calibrate and validate the automated method used to quantify surface sediment grain size distributions in objective images. The surface sediment grain size ... |
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Surface sediment grain diameter measurements from point counts of in situ seafloor images collected in the lower Columbia River, Washington and Oregon, 2021
This dataset contains surface sediment grain diameter measurements from in situ seafloor images collected in the lower Columbia River, Washington and Oregon, in 2021. Surface sediment grain diameters were derived from manual measurements (or "point counts") in a subset of images used to calibrate and validate an automated image processing algorithm to determine surface sediment grain size distributions. For each calibration and validation image that was selected, the long and short axis of 100 grains were ... |
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Vessel-mounted acoustic Doppler current profiler (ADCP) data from the lower Columbia River, Washington and Oregon, 2021
This dataset contains water velocity data derived from spatial surveys performed with a vessel-mounted acoustic Doppler current profiler at four sites (SKM, SLG, LDB, WLW) in the lower Columbia River, Washington and Oregon, in 2021. The data are provided in netCDF (.nc) format and compressed into .zip archives for each site. |
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Time-series measurements of oceanographic and water quality data collected in the Herring River, Wellfleet, Massachusetts, USA, November 2018 to November 2019
Restoration in the tidally restricted Herring River Estuary in Wellfleet, MA benefits from understanding pre-restoration sediment transport conditions. Submerged sensors were deployed at four sites landward and seaward of the Herring River restriction to measure water velocity, water quality, water level, waves, and seabed elevation. These data will be used to evaluate sediment dynamics and geomorphic change and inform marsh modeling efforts over tidal and seasonal timescales. |
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Water quality data from a multiparameter sonde collected in the Herring River during November 2018 to November 2019 in Wellfleet, MA
Management efforts of the tidally-restricted Herring River in Wellfleet, MA include research to understand pre-restoration sediment conditions. Submerged multiparameter sondes that measure optical turbidity were deployed at one site landward and three sites seaward of the Herring River restriction. Periodically, the sites were visited and additional turbidity measurements were collected with a handheld multiparameter sonde, and water samples were collected for determination of suspended-sediment ... |
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Grain size, bulk density, and carbon content of sediment collected from Whale's Tail South marsh and adjacent bay floor, South San Francisco Bay, California, 2021-2022
Sediment samples were collected on and adjacent to the Whale's Tail South marsh. Short push-cores of bed sediment were collected in South San Francisco Bay adjacent to Whale's Tail South marsh on five days from June through August 2021 and 3 days from November 2021 to January 2022. Additional samples were taken from sediment deposited on ceramic tiles attached to the marsh surface and from rip-up clasts deposited on the marsh edge. Samples were analyzed for sediment properties including bulk density, ... |
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Sediment sample analysis data from ponds to the beach on North Core Banks, NC in October 2022
These data map in high detail surficial cross-sections of North Core Banks, a barrier island in Cape Lookout National Seashore, NC, in October 2022. U.S. Geological Survey field efforts are part of an interagency agreement with the National Park Service to monitor the recovery of the island from Hurricanes Florence (2018) and Dorian (2019). Three sites of outwash, overwash, and pond formation were targeted for extensive vegetation ground-truthing, sediment samples, bathymetric mapping with a remote ... |
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Time-series measurements of oceanographic and water quality data collected at Thompsons Beach and Stone Harbor, New Jersey, USA, September 2018 to September 2019 and March 2022 to May 2023
In October 2012, Hurricane Sandy made landfall in the Northeastern U.S., affecting ecosystems and communities of 12 states. In response, the National Fish and Wildlife Federation (NFWF) and the U.S. Department of Interior (DOI) implemented the Hurricane Sandy Coastal Resiliency Program, which funded various projects designed to reduce future impacts of coastal hazards. These projects included marsh, beach, and dune restoration, aquatic connectivity, and living shoreline installation, among others. To ... |
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Lifespan of marsh units in Maine salt marshes
This data release contains coastal wetland synthesis products for the state of Maine. Metrics for resiliency, including the unvegetated to vegetated ratio (UVVR), marsh elevation, tidal range, and lifespan, are calculated for smaller units delineated from a digital elevation model, providing the spatial variability of physical factors that influence wetland health. The U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the ... |
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Water quality data from a multiparameter sonde from Thompsons Beach and Stone Harbor, New Jersey, collected between September 2018 and December 2022
In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science ... |
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Grain-size analysis data from sediment samples in support of oceanographic and water-quality measurements at Thompsons Beach and Stone Harbor, New Jersey, collected in September 2018 and March 2022
In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science ... |
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Suspended-sediment concentration and loss-on-ignition from water samples at Thompsons Beach and Stone Harbor, New Jersey, collected between September 2018 and December 2022
In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science ... |
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Grain-Size Analysis Data from Sediment Samples in Support of Oceanographic and Water-Quality Measurements in the Nearshore Zone of Matanzas Inlet, Florida, 2018
The interactions of waves and currents near an inlet influence sediment and alter sea-floor bedforms, especially during winter storms. As part of the Cross-Shore and Inlets Processes project to improve our understanding of cross-shore processes that control sediment budgets, the U.S. Geological Survey deployed instrumented platforms at two sites near Matanzas Inlet between January 24 and April 13, 2018. Matanzas Inlet is a natural, unmaintained inlet on the Florida Atlantic coast that is well suited for ... |
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Grain-size analysis data from sediment samples in support of oceanographic and water-quality measurements in the nearshore zone of Sandy Neck Beach, Cape Cod Bay, Massachusetts, collected in March and April, 2021
The U.S. Geological Survey Woods Hole Coastal and Marine Science Center collected data to assess cross-shore sediment transport prediction techniques in coastal models for a wave-dominated sandy coast. A quadpod was deployed on the seafloor in the nearshore zone of Sandy Neck Beach, Cape Cod Bay, MA in March 2021 to analyze water velocities near the seabed and the response of the seabed to these forces. The quadpod was mounted with upward- and downward-looking Nortek Signatures to measure velocity ... |
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Suspended-sediment concentration data from water samples collected in 2016-17 in Grand Bay, Alabama and Mississippi
Suspended-sediment transport is a critical element governing the geomorphology of tidal marshes and estuaries. Marsh elevation, relative to sea level, is maintained by both organic material and the deposition of inorganic sediment. Additionally, horizontal marsh extent is altered by lateral erosion and accretion. In wetlands within and near Grand Bay National Estuarine Research Reserve, parts of the salt marsh are eroding relatively rapidly. To understand the connection between sediment fluxes and these ... |
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Lifespan of marsh units in Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia
The sediment-based lifespan of salt marsh units in Assateague Island National Seashore (ASIS) and Chincoteague Bay is shown for conceptual marsh units defined by Defne and Ganju (2018). The lifespan represents the timescale by which the current sediment mass within a marsh parcel can no longer compensate for sediment export and deficits induced by sea-level rise. The lifespan calculation is based on vegetated cover, marsh elevation, sediment supply, and sea-level rise (SLR) predictions after Ganju and ... |
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Suspended-sediment concentrations and loss-on-ignition from water samples collected in the Herring River during 2018-19 in Wellfleet, MA (ver 1.1, March 2023)
The Herring River in Wellfleet, MA is a tidally-restricted estuary system. Management options including potential restoration of unrestricted tidal flows require an understanding of pre-restoration sediment conditions. Altering future tidal flows may cause changes in net sediment flux and direction, which could affect marsh restoration and aquaculture in Wellfleet Harbor. This research aims to measure sediment fluxes seaward of the Herring River restriction and sediment concentrations landward of the ... |
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Grain-size analysis data of sediment samples from the beach and nearshore environments at the Pea Island National Wildlife Refuge DUNEX site, North Carolina in 2021
These data provide grain-size measurements from sediment samples collected as part of the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study nearshore coastal processes during storm events. USGS participation in DUNEX will contribute new measurements and models that will increase our understanding of storm impacts to coastal environments, ... |
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Information on sediment cores collected from Cargill Marsh, South San Francisco Bay, California during field activities 2022-643-FA and 2023-681-FA
This dataset presents core information such as core IDs, core lengths, depth intervals, and locations from sediment cores collected from Cargill Marsh, South San Francisco Bay, California on June 21, 2022, and December 14, 2023. The cores were collected with hand driven push cores to assess sediment accumulation on the marsh. |
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Cesium-137 isotope activity measured in sediment cores collected from Cargill Marsh, South San Francisco Bay, California during field activities 2022-643-FA and 2023-681-FA
This dataset presents specific activities of cesium-137 in picoCuries per gram from sediment cores collected from Cargill Marsh, South San Francisco Bay, California on June 21, 2022, and December 14, 2023. The cores were collected with hand driven push cores to assess sediment accumulation on the marsh. |
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Computed Tomography (CT) scans of sediment cores collected from Cargill Marsh, South San Francisco Bay, California during field activities 2022-643-FA and 2023-681-FA
This dataset includes computed tomography (CT) scans of sediment cores collected from Cargill Marsh, South San Francisco Bay, California on June 21, 2022, and December 14, 2023. The cores were collected with hand driven push cores to assess sediment accumulation on the marsh. CT images are provided in the original 16-bit grayscale TIFF format. |
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Photographs of sediment cores collected from Cargill Marsh, South San Francisco Bay, California during field activities 2022-643-FA and 2023-681-FA
This dataset includes photographs (linescan images) of sediment cores collected from Cargill Marsh, South San Francisco Bay, California on June 21, 2022, and December 14, 2023. The cores were collected with hand driven push cores to assess sediment accumulation on the marsh. |
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Lifespan of marsh units in Eastern Shore of Virginia salt marshes
The lifespans of salt marshes in Atlantic-facing Eastern Shore of Virginia are calculated based on estimated sediment supply and sea-level rise (SLR) predictions, following the methodology of Ganju and others (2020). The salt marsh delineations are from Ackerman and others (2023). The SLR predictions are local estimates corresponding to increases of 0.3, 0.5 and 1.0 meter in global mean sea level (GMSL) by 2100, as projected by Sweet and others (2022). This work has been a part of the USGS’s effort to ... |
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Lifespan of marsh units in Connecticut salt marshes
The lifespans of salt marshes in Connecticut are calculated based on estimated sediment supply and sea-level rise (SLR) predictions, following the methodology of Ganju and others (2020). The salt marsh delineations are from Ackerman and others (2023). The SLR predictions are local estimates corresponding to increases of 0.3, 0.5 and 1.0 meter in global mean sea level (GMSL) by 2100, as projected by Sweet and others (2022). This work has been a part of the USGS’s effort to expand the national assessment of ... |
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Properties of sediment collected from two marshes and adjacent shallows in Northern San Francisco Bay, California, 2022-2023
Bed sediment samples were collected from the intertidal, and subtidal shallows of San Pablo Bay National Wildlife Refuge and Corte Madera Bay near stations where instrumented platforms that were collecting hydrographic time-series were deployed. Sediment sediments were collected with push cores, either manually or by subsampling a Gomex box corer. Cores, which ranged in length from 5 to 18 centimeters (cm), were sectioned by depth. The top two sections from each core were 0.5 cm thick, the following ... |
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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Ivan Initial Elevations
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Katrina Initial Elevations
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 2010 Simulation With 0.5-meter of Sea Level Rise
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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ST1_Final_DEM_metadata: Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration alternative for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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ST2_Final_DEM_metadata: Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration measures for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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ST3_Final_DEM_metadata: Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration alternative for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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ST4_Final_DEM_metadata: Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs without restoration alternative for storminess bins (ST1-ST4) and sea level rise scenarios (SL1-SL3).
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Multi-sensor core logger (MSCL) scans of sediment cores collected offshore southern Cascadia, during field activity 2019-643-FA
This dataset includes multi-sensor core logger (MSCL) data of sediment cores collected in southern Cascadia (offshore northern California) aboard the M/V Bold Horizon in September-October 2019. |
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Sediment grain size in the Elwha River estuary, Washington, from 2013 and 2014.
This portion of the data release presents sediment grain-size data from samples collected in the Elwha River estuary, Washington, in July 2013 and June 2014 (USGS Field Activities L-15-13-PS and 2014-628-FA). Surface sediment was collected from one location in 2013 and five locations in 2014 using a using a push core. The locations of grab samples were determined with a hand-held global positioning system (GPS). The cores were split into one- to three-centimeter sections. The grain-size distributions of ... |
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Sediment grain size from the Elwha River, Washington, 2006 to 2017
The grain size of sediment on the riverbed was measured during 20 surveys on the Elwha River, Washington, between 2006 and 2017. Most data were collected along the same transects where channel topography was measured (see related child item in this data release: https://www.sciencebase.gov/catalog/item/5a989288e4b06990606de04b). Measurements of sediment ranging from medium sand to boulders were made using the CobbleCam digital photographic technique (Warrick and others, 2009), which uses a calibrated ... |
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Surface-sediment grain-size distributions from the Elwha River delta, Washington, May 2014
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in May 2014 (USGS Field Activity 2014-620-FA). Surface sediment was collected from 43 locations using a small ponar, or 'grab', sampler from a small boat on May 12, 2014 in depths between about 1 and 12 m around the delta. The locations of grab samples were determined with a hand-held global navigation satellite system (GNSS). The grain-size distributions of samples were determined ... |
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Raw computed tomography (CT) images of sediment cores collected in 2009 offshore from Palos Verdes, California
This part of the data release includes raw computed tomography (CT) images of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan_info ... |
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Graphical representations of data from sediment cores collected in 2009 offshore from Palos Verdes, California
This part of the data release includes graphical representation (figures) of data from sediment cores collected in 2009 offshore of Palos Verdes, California. This file graphically presents combined data for each core (one core per page). Data on each figure are continuous core photograph, CT scan (where available), graphic diagram core description (graphic legend included at right; visual grain size scale of clay, silt, very fine sand [vf], fine sand [f], medium sand [med], coarse sand [c], and very coarse ... |
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Grain-size analysis of sediment cores collected in 2009 offshore from Palos Verdes, California
This part of the data release includes grain-size analysis of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan_info.php?fan=SI209SC), ... |
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Name, location, and length of sediment cores collected in 2009 offshore from Palos Verdes, California
This part of the data release is a spreadsheet including the name, location, and length of sediment cores collected in 2009 offshore from Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs ... |
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Multi-Sensor Core Logger (MSCL) P-wave velocity, gamma-ray density, and magnetic susceptibility whole-core logs of sediment cores collected in 2009 offshore from Palos Verdes, California
This part of the data release includes Multi-Sensor Core Logger (MSCL) P-wave velocity, gamma-ray density, and magnetic susceptibility whole-core logs of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the ... |
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Continuous core photographs of sediment cores collected in 2009 offshore from Palos Verdes, California
This part of the data release includes continuous core photographs in bmp format of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http://cmgds.marine.usgs.gov/fan ... |
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Radiocarbon sample data and calibrated ages of sediment core collected in 2009 offshore from Palos Verdes, California
This part of the data release is a spreadsheet including radiocarbon sample information and calibrated ages of sediment cores collected in 2009 offshore of Palos Verdes, California. It is one of seven files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, offshore Los Angeles and the Palos Verdes Peninsula, adjacent to the Palos Verdes Fault. Gravity cores were collected by the USGS in 2009 (cruise ID S-I2-09-SC; http:/ ... |
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Surface-sediment grain-size distributions of the Elwha River delta, Washington, July 2016
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in July 2016 (USGS Field Activity 2016-653-FA). Surface sediment was collected from 67 locations using a small ponar, or 'grab', sampler from the R/V Frontier in water depths between about 1 and 17 m around the delta. An additional 38 samples were collected by hand at low tide. A hand-held global satellite navigation system (GNSS) receiver was used to determine the locations of ... |
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Graphical representations of data from sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California
This part of the data release includes graphical representation (figures) of data of sediment cores collected in 2014 in Monterey Canyon. It is one of five files included in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium Research Institute’s (MBARI’s) remotely operated vehicle (ROV) Doc Ricketts in ... |
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Name, location, and length of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California
This part of the data release is a spreadsheet including the name, location, and length of sediment cores collected in 2014 in Monterey Canyon. It is one of five files in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium Research Institute’s (MBARI’s) remotely operated vehicle (ROV) Doc Ricketts in 2014 ... |
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Multi-Sensor Core Logger (MSCL) P-wave velocity and gamma-ray density whole-core logs of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California
This part of the data release includes Multi-Sensor Core Logger (MSCL) P-wave velocity and gamma-ray density whole-core logs of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California. It is one of five files in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium ... |
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Continuous core photographs of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California
This part of the data release includes continuous core photographs in bmp format of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California. It is one of five files in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium Research Institute’s (MBARI’s) remotely ... |
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Radiocarbon sample data and calibrated ages of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California
This part of the data release is a spreadsheet including radiocarbon sample information and calibrated ages of sediment cores collected in 2014 from the northern flank of Monterey Canyon, offshore California. It is one of five files in this U.S. Geological Survey data release that include data from a set of sediment cores acquired from the continental slope, north of Monterey Canyon, offshore central California. Vibracores and push cores were collected with the Monterey Bay Aquarium Research Institute’s ... |
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Sediment grain size and digital image calibration parameters from the mouth of the Columbia River, Oregon and Washington, 2014
This dataset includes 63 still images extracted from digital video imagery of sediment grab samples, along with laboratory grain size analysis of the sediment grab samples, taken from the mouth of the Columbia River, OR and WA, USA. Digital video was collected in September 2014 in the mouth of the Columbia River, USA, as part of the U.S. Geological Survey Coastal and Marine Geology Program contribution to the Office of Naval Research funded River and Inlets Dynamics experiment (RIVET II). Still images were ... |
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Digital seafloor images and sediment grain size from the mouth of the Columbia River, Oregon and Washington, 2014
This dataset includes 2,523 still images extracted from geo-referenced digital video imagery of the seafloor at the mouth of the Columbia River, OR and WA, USA, along with grain size analysis of the surface sediment. Underwater digital video was collected in September 2014 in the mouth of the Columbia River, USA, as part of the U.S. Geological Survey Coastal and Marine Geology Program contribution to the Office of Naval Research funded River and Inlets Dynamics experiment (RIVET II). Still images were ... |
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Surface-sediment grain-size data from the mouth of the Columbia River, Oregon and Washington, 2013
This portion of the USGS data release presents sediment grain-size data from samples collected from the mouth of the Columbia River, Oregon and Washington, in 2013. Surface sediment was sampled using a small ponar, or 'grab', sampler on May 9, 2013 from the F/V Cape Windy at 3 locations. A handheld global navigation satellite system (GNSS) receiver was used to determine the locations of sediment samples. The grain size distributions of samples were determined using standard techniques developed by the USGS ... |
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Surface-sediment grain-size distributions from the Elwha River delta, Washington, September 2014
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in September 2014 (USGS Field Activity 2014-649-FA). Surface sediment was collected from 63 locations using a small ponar, or 'grab', sampler from the R/V Frontier on September 5, 2014 in depths between about 1 and 17 m around the delta. The locations of grab samples were determined with a hand-held global navigation satellite system (GNSS). The grain-size distributions of samples ... |
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Daily sediment loads during and after dam removal in the Elwha River, Washington, 2011 to 2016
Daily values of discharge and sediment loads were measured and estimated at U.S. Geological Survey gaging station 12046260, on the Elwha River at the diversion near Port Angeles, Washington. Daily data are reported from September 15, 2011 to September 30, 2016. Specific data include (1) date; (2) discharge; (3) suspended-sediment concentration and one standard-deviation bounds; (4) percentage of fine-grained particles (silts and clays) in suspension; (5) loads of total suspended-sediment, fine-grained ... |
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Monthly bedload estimates, Elwha River, Washington, October 2015 to September 2016
Bedload sediment transport was calculated on the Elwha River, Washington to measure the amount of sediment transported along the riverbed during the 2016 water year. Bedload was measured using the Elwha bedload impact plate system (Hilldale and others, 2015). Physical bedload sampling by the U.S. Bureau of Reclamation for system calibration took place during November, 2012; March, May, and June 2013; and April 2014 at the Diversion Weir gauge (Magirl and others, 2015). Early in water year 2016 (year 5) the ... |
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Upstream sediment contributions to Lake Mills on the Elwha River, Washington, 1926 to 2016
Sediment inputs to Lake Mills, on the Elwha River, Washington, were measured from 1927 to 2016. These measurements represent the annual total sediment load, in tonnes per year, that were input into Lake Mills and partially trapped by Glines Canyon dam. The sediment was allowed to erode and be transported down-river by the removal of the Glines Canyon and Elwha dams during 2011 to 2014. The measurements were taken as part of a study investigating the river channel's morphological responses to the removal of ... |
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Suspended sediment concentration data in the Elwha River, Washington, September 2011 to September 2016
This data release provides 15-minute data of suspended-sediment concentration and fine (less than 0.0625 mm) suspended-sediment concentration during the removal of 2 large dams on the Elwha River from September 2011 to September 2016. Data are derived from regression relations with turbidity at the USGS gaging station Elwha River at the Diversion (no.12046260). |
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Surface-sediment grain-size distributions from the Elwha River delta, Washington, August 2012
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in August 2012 (USGS Field Activity W-05-12-PS). Surface sediment was sampled using a small ponar, or 'grab', sampler between August 28 and August 30, 2012 from the R/V Frontier at a total of 57 locations in water depths between about 1 and 9 m around the delta. The locations of grab samples were determined with a hand-held global navigation satellite system (GNSS). The grain-size ... |
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Surface-sediment grain-size distributions from the Elwha River delta, Washington, March 2013
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in March 2013 (USGS Field Activity W-01-13-PS). Surface sediment was sampled using a small ponar, or 'grab', sampler on March 4, 2013 from the R/V Frontier at a total of 48 locations in water depths between about 1 and 12 m around the delta. An additional 7 sediment samples were collected between March 6 and March 7, 2013 at low tide from intertidal locations on the delta. The ... |
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Surface-sediment grain-size distributions from the Elwha River delta, Washington, July 2015
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, between July and August 2015 (USGS Field Activities 2015-648-FA and 2015-652-FA). Surface sediment was collected from 70 locations using a small ponar, or 'grab', sampler from the R/V Frontier on July 28, 2015. An additional 17 sediment samples were collected between July 22 and August 23, 2015 by scuba divers. Forty-eight sediment samples were collected at low tide using a push ... |
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Surface-sediment grain-size distributions from the Elwha River delta, Washington, September 2013
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in September 2013 (USGS Field Activity W-07-13-PS). Surface sediment was collected from 62 locations using a small ponar, or 'grab', sampler from the R/V Frontier on September 19, 2013 in depths between about 1 and 12 m around the delta. An additional 21 sediment samples were collected between September 16 and September 19, 2013 at low tide from intertidal locations on the delta. ... |
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Surface-sediment grain-size distributions of the Elwha River delta, Washington, January 2015
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in January 2015 (USGS Field Activity 2015-605-FA). Surface sediment was collected from 61 locations using a small ponar, or 'grab', sampler from the R/V Frontier in depths between about 1 and 17 m around the delta. A handheld global satellite navigation system (GNSS) receiver was used to determine the locations of sediment samples. The grain-size distributions of samples were ... |
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Grain size and bulk density of sediment cores from Little Holland Tract and Liberty Island, Sacramento-San Joaquin Delta, California, 2014
Grain size distribution and bulk density are reported for sediment push cores from two flooded agricultural tracts, Little Holland Tract and Liberty Island, in the Sacramento-San Joaquin Delta, California. Push core samples were collected from 14 sites by the U.S Geological Survey in August, 2014. Each core was analyzed at multiple depths to investigate variations in particle sizes with depth below the sediment surface. The same sites were sampled again in 2016 (https://www.sciencebase.gov/catalog/item ... |
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Grain size and bulk density of sediment cores from Little Holland Tract and Liberty Island, Sacramento-San Joaquin Delta, California, 2016
Grain size distribution and bulk density are reported for sediment push cores from two flooded agricultural tracts, Little Holland Tract and Liberty Island, in the Sacramento-San Joaquin Delta, California. Push core samples were collected from 17 sites by the U.S. Geological Survey in June 2016. Each core was analyzed at multiple depths to investigate variations in particle sizes with depth below the sediment surface. The same sites were sampled previously in 2014 (https://www.sciencebase.gov/catalog/item ... |
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Grain-size distributions from San Pablo Bay, California, 2011 to 2012
Sediment cores were collected from San Pablo Bay, in the Sacramento-San Joaquin Delta in California by the U.S. Geological Survey Pacific Coastal and Marine Science Center (PCMSC) during multiple surveys from 2011 to 2012. The cores were analyzed for grain-size distributions at the PCMSC sediment lab. |
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Surface-sediment grain-size distributions of the Elwha River delta, Washington, February 2016
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in February 2016. Surface sediment was collected from 83 locations using a small ponar, or 'grab' sampler from the R/V Frontier in water depths between 17 and 1 m around the delta. An additional 18 samples were collected by hand at low tide. A handheld global satellite navigation system (GNSS) receiver was used to determine the locations of sediment samples. The grain size ... |
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Grain size, bulk density, and organic carbon of sediment cores from three locations in the Sacramento-San Joaquin Delta, California, 2017 to 2018
Bed sediment samples were collected in Lindsey Slough in April 2017, and Middle River and the Mokelumne River in March 2018, to analyze for sediment properties, including bulk density, particle size distribution, and percent organic carbon. Sediment samples were collected within the vegetation with push corers deployed from a small vessel, and in the unvegetated channel with a Gomex box corer, which was subsampled with three push cores per Gomex core. Data are provided in a comma-delimited values ... |
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Grain size of bed sediment surface samples from south San Francisco Bay, California, summer 2020
Bed sediment samples were collected in south San Francisco Bay on two days in July 2020 to analyze for sediment grain size distributions. Sediment samples were collected from the R/V Snavely near pre-established U.S. Geological Survey instrument moorings using a Gomex or Ponar box corer that was subsampled by scraping the top 0.5 cm of the core. Data are provided in a comma-delimited values spreadsheet. |
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Surface-sediment grain-size distributions of the Elwha River delta, Washington, July 2017
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in July 2017 (USGS Field Activity 2017-638-FA). Surface sediment was collected from 80 locations using a small ponar, or 'grab', sampler from the R/V Frontier in water depths between about 1 and 17 m around the delta. An additional 31 samples were collected by hand at low tide. A hand-held global satellite navigation system (GNSS) receiver was used to determine the locations of ... |
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Turbidity data from the Carmel River, central California, 2014 to 2017
This data provides river turbidity measurements collected on the Carmel River, CA. Turbidity was measured to study any changes in the Carmel River’s sediment loads following the removal of the San Clemente Dam. The USGS-run DTS-12 turbidity sensor was deployed above the Sleepy Hollow Weir on the Carmel River, CA (instrument was located at 36.445250 degrees North, 121.710494 degrees West). Deployment began on December 9, 2014. After June 16, 2016, the instrument was removed for calibration. A new ... |
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Surface-sediment grain-size distributions of the Elwha River delta, Washington, July 2018
This portion of the data release presents sediment grain-size data from samples collected on the Elwha River delta, Washington, in July 2018 (USGS Field Activity 2018-648-FA). Surface sediment was collected from 39 locations using a small ponar, or 'grab', sampler from the R/V Frontier in water depths between about 1 and 17 m around the delta. An additional 35 samples were collected by hand at low tide. A hand-held global satellite navigation system (GNSS) receiver was used to determine the locations of ... |
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Grain size, bulk density, and organic carbon of sediment cores from San Pablo Bay and Grizzly Bay, California, 2020
Bed sediment samples were collected in San Pablo Bay and Grizzly Bays on eight days from January through September 2020, to analyze for sediment properties including bulk density, particle size distribution, and percent organic carbon. Sediment samples were collected from a small vessel near pre-established USGS instrument moorings using a Gomex box corer that was subsampled with three push cores (37 mm in diameter) per Gomex core. Six subsamples were collected from the top 5 centimeters (cm) of each push ... |
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Grain size, bulk density, and organic carbon of sediment cores from San Pablo Bay and Grizzly Bay, California, 2019
Bed sediment samples were collected in San Pablo Bay and Grizzly Bays on eight days from June through November 2019, to analyze for sediment properties including bulk density, particle size distribution, and percent organic carbon. Sediment samples were collected from a small vessel near pre-established USGS instrument moorings using a Gomex box corer that was subsampled with three push cores (37 mm in diameter) per Gomex core. Six subsamples were collected from the top 5 centimeters (cm) of each push ... |
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Oceanographic time-series measurements collected in the Stillaguamish River Delta, Port Susan, Washington, USA from March 2014 to July 2015
Water level, flow velocity, temperature, salinity, and turbidity were measured in a breach constructed in a flood-protection levee surrounding a restored former agricultural area in Port Susan, Washington, USA, near the mouth of the Stillaguamish River. Data were collected in a breach known as PSB1 at 15-minute intervals from March 21, 2014 to July 1, 2015 using a SonTek Argonaut-SW current meter, an In-Situ Aqua TROLL 200 pressure, conductivity, and temperature sensor, and an FTS DTS-12 turbidity sensor. |
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Radiocarbon data from coastal wetlands on the Hawaiian islands of Kaua'i, O'ahu, and Hawai'i
This portion of the data release presents radiocarbon age data from 66 samples collected from Anahola Valley (Kaua'i), Kahana Valley (O'ahu), and Pololu Valley (Hawai'i). Sample ages were determined by the National Ocean Sciences Accelerator Mass Spectrometry (NOSAMS) facility. The data are provided in a comma-delimited spreadsheet (.csv). |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - 2005/06/19 through 2005/11/20 Deterministic Scenario
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - 2015/08/27 through 2015/08/29 Deterministic Scenario
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - 2015/12/09 through 2015/12/11 Deterministic Scenario
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 10-Year Simulation with 0.5-meter of Sea Level Rise
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 10-Year Simulation Without Sea Level Rise
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 2010 Simulation With 0.5-meter of Sea Level Rise
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Existing Condition 2010 Simulation Without Sea Level Rise
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Initial Existing Conditions Grid
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Dauphin Island Decadal Hindcast Model Inputs and Results: Final DEM
The model output of bathymetry and topography values resulting from a deterministic simulation at Dauphin Island, Alabama, as described in USGS Open-File Report 2019–1139 (https://doi.org/10.3133/ofr20191139), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry refer to Mickey and others (2020). |
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Wave Scenario Grid with Proposed Sediment Borrow Pit 3 of Breton Island, Louisiana: Model Input Grid 4 with Pit 3 Configuration
The Simulating WAves Nearshore (SWAN) wave model input grid 4 bathymetry with pit 3 configuration (G4_P3_grid.shp) and output of significant wave height, dominant wave period, and mean wave direction resulting from simulation of wave scenarios at Breton Island, LA, as described in USGS Open-File Report 20151055 are provided here. |
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Archive of Digitized Analog Boomer and Minisparker Seismic Reflection Data Collected from the Northern Gulf of Mexico: 1981, 1990 and 1991
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (https:/ ... |
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Idealized Antecedent Topography Sensitivity Study: Initial Baseline and Modified Profiles Modeled with XBeach
Antecedent topography is an important aspect of coastal morphology when studying and forecasting coastal change hazards. The uncertainty in morphologic response of storm-impact models and their use in short-term hazard forecasting and decadal forecasting is important to account for when considering a coupled model framework. Mickey and others (2020) provided a methodology to investigate uncertainty of profile response within the storm impact model, XBeach, related to varying antecedent topographies. A ... |
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Storm-Impact Scenario XBeach Model Inputs – Initial Bathymetry and Topography Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Dauphin Island Decadal Hindcast Model Inputs and Results: Initial DEM
The model input for the bathymetry and topography values resulting from a deterministic simulation at Dauphin Island, Alabama, as described in U.S. Geological Survey (USGS) Open-File Report 2019-1139 (https://doi.org/10.3133/ofr20191139), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Initial DEMs with and without restoration alternatives R2-R7
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Archive of Digitized Analog Boomer Seismic Reflection Data Collected from the Northern Gulf of Mexico: Intersea 1980
The U.S. Geological Survey (USGS) Coastal and Marine Hazards and Resources Program (CMHRP) has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters (m) long. As part of the National Geological and Geophysical Data Preservation ... |
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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Ivan Constant Land Friction Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Ivan Default Friction Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Intermediate-Low Sea Level Rise (SLR) Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Low Sea Level Rise (SLR) Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Present-Day Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Ivan Spatially Varying Friction Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Static Intermediate-Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Ivan Static Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Katrina before Hurricane Ivan Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Katrina Constant Land Friction Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Katrina Default Friction Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Intermediate-Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Low Sea Level Rise Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
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Dauphin Island Storms and Sea Level Rise Assessment: XBeach Model Input and Results for the Hurricane Katrina Present-Day Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ... |
Info |
XBeach Bottom Friction Scenarios: Model Inputs and Results for Hurricane Katrina Spatially Varying Friction Scenario
Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ... |
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Archive of digitized analog boomer seismic reflection data collected along the Louisiana Shelf, 1982–1984
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (https:/ ... |
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Archive of digitized analog boomer seismic reflection data collected during USGS Cruise Kit Jones 92-1 along the Florida Shelf, July 1992
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (NGGDPP; https:/ ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 10-Year Simulation With 0.5-meter of Sea Level Rise
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 10-Year Simulation Without Sea Level Rise
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - With-Project Condition 2010 Simulation Without Sea Level Rise
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Mobile Harbor Navigation Channel Delft3D Model Inputs and Results - Initial Project Conditions Grid
The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ... |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 2 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 3 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 4 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 5 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 6 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Dauphin Island Decadal Forecast Evolution Model Inputs and Results: Final DEMs with restoration alternative 7 that extends Pelican Island simulated with ST2_SL1 and ST3_SL3 scenarios
The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020). |
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Storm-Impact Scenario XBeach Model Results – Scenario 11 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 12 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 1 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 20 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 2 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 3 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 6 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 7 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Storm-Impact Scenario XBeach Model Results – Scenario 8 Digital Elevation Model (DEM) Grid
The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ... |
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Archive of Digitized Analog Boomer Seismic Reflection Data Collected from the Northern Gulf of Mexico: 1982, 1985, 1986, 1989, 1991, and 1992
The U.S. Geological Survey (USGS) Coastal and Marine Hazards and Resources Program (CMHRP) has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program ... |
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Archive of digitized analog boomer seismic reflection data collected during USGS Cruise USFHC in Mississippi Sound and Bay St. Louis, September 1989
The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. As part of the National Geological and Geophysical Data Preservation Program (NGGDPP, https:/ ... |
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The Massachusetts Bay Internal Wave Experiment, August 1998: Data Report
This data report presents oceanographic observations made in Massachusetts Bay in August 1998 as part of the Massachusetts Bay Internal Wave Experiment (MBIWE98). MBIWE98 was carried out to characterize large-amplitude internal waves in Massachusetts Bay and to investigate the possible resuspension and transport of bottom sediments caused by these waves. This data report presents a description of the field program, an overview of the data through summary plots and statistics, and the time-series data in ... |
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Sedimentary Environments of the Sea Floor off Eastern Cape Cod, Massachusetts (CC_ENVIRON.SHP, Geographic, WGS84)
This data set includes the sedimentary environments for the sea floor offshore of northern and eastern Cape Cod, Massachusetts. This interpretation is based on data collected with a multibeam sea floor mapping system during USGS survey 98015, conducted November 9 - 25, 1998 and on data collected with a bottom sampling and photographic system during USGS survey 04011, conducted during May and June, 2004. |
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Seafloor or Short Core Hydrate Locations in the Gulf of Mexico (HYDRATES.SHP)
This GIS overlay is a component of the U.S. Geological Survey, Woods Hole Field Center's, Gulf of Mexico ArcView GIS database. The Gulf of Mexico GIS database is intended to organize and display USGS held data and provide on-line (WWW) access to the data and/or metadata. Additional GIS overlays downloaded from the WWW, such as the one described here, are also included in the Gulf of Mexico ArcView GIS database. Attempts to properly attribute such GIS overlays with the WWW address and data compilers has been ... |
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South Carolina Coastal Erosion Study Data Report for Observations : October 2003 - April 2004
Oceanographic observations have been made at nine locations in Long Bay, South Carolina from October 2003 through April 2004. These sites are centered around a shore-oblique sand feature that is approximately 10 km long, 2 km wide, and in excess of 3 m thick. The observations were collected through a collaborative effort with the U.S. Geological Survey, the University of South Carolina, and Georgia Institute of Technology Savannah Campus as part of a larger study to understand the physical processes that ... |
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Sedimentary Environments of NOAA H11310 Sidescan Sonar Mosaic in Central Narragansett Bay (H11310SEDENVIRONS.SHP)
The United States Geological Survey (USGS) is working cooperatively with the National Oceanic and Atmospheric Association (NOAA) to interpret the surficial geology in estuaries along the coast of the northeastern United States. The purpose of our present study is to interpret the distributions of surficial sediments and sedimentary environments in an area of Narragansett Bay using sidescan sonar imagery, high-resolution bathymetry, and sediment data. The mosaic presented herein covers an area of the sea ... |
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Interpretation Showing the Distribution of Sea-Floor Sedimentary Environments in Quicks Hole, MA (H11076_SEDENV.SHP, Geographic)
The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Massachusetts Office of Coastal Zone Management (MA CZM), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of the Massachusetts coastline, show the composition and terrain of the seabed, and provide information on sediment ... |
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Interpretation of the Sedimentary Environments of National Oceanic and Atmospheric Administration (NOAA) H11320 Sidescan Sonar Mosaic in Rhode Island Sound (H11320ENVIRONS)
The U.S. Geological Survey (USGS) is working cooperatively with the National Oceanic and Atmospheric Administration (NOAA) to interpret the surficial geology in estuaries along the coast of the northeastern United States. The purpose of our present study is to define the sea floor morphology and sedimentary environments in an area of Rhode Island Sound using sidescan sonar imagery, multibeam bathymetry, and seismic records. The mosaic, bathymetry, and their interpretations serve many purposes, including: (1 ... |
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Interpretation of Sedimentary Environments from National Oceanic and Atmospheric Administration (NOAA) Survey H11922 West of Gay Head, Massachusetts, in Eastern Rhode Island Sound (H11922_SEDENV.SHP, Geographic, WGS84)
The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities off southern New England, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. During July-August 2008 NOAA completed hydrographic ... |
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Interpretation of Sedimentary Environments from National Oceanic and Atmospheric Administration (NOAA) Survey H12007 in the Vicinity of Cross Rip Channel in Nantucket Sound, Offshore Southeastern Massachusetts (H12007_SEDENV.SHP, Geographic, WGS84)
The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities off southern New England, shows the character and terrain of the seabed, and provides information on sediment transport and benthic habitat. During April-May 2009 NOAA completed hydrographic survey ... |
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Interpretation of Sedimentary Environments Within the Area of National Oceanic and Atmospheric Administration (NOAA) Survey H12013 Offshore in Northeastern Long Island Sound (Geographic, WGS84, H12012_SEDENV.SHP)
The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Connecticut Department of Energy and Environmental Protection (CT DEEP), has produced detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities in Long Island Sound, shows the terrain of the seabed, and provides information on sediment transport and benthic ... |
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Interpretation of Sedimentary Environments from National Oceanic and Atmospheric Administration (NOAA) Survey H12299 in Block Island Sound (Geographic, WGS 84, H12299SEDENV.SHP)
The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetric data, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of Block Island Sound, show the composition and terrain of the seabed, and provide information on sediment transport and benthic habitat. During June 2013, bottom photographs and ... |
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Interpretation of Sedimentary Environments from National Oceanic and Atmospheric Administration (NOAA) Survey H12298 in Block Island Sound (Geographic, WGS 84, H12298SEDENV.SHP)
The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetric and sidescan-sonar data, originally collected by NOAA for charting purposes, provide a framework for research and management activities along western Block Island Sound, show the composition and terrain of the seabed, and provide information on sediment transport and benthic habitat. During June 2013, bottom photographs ... |
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Interpretation of Sedimentary Environments from National Oceanic and Atmospheric Administration (NOAA) Survey H12324 in Narragansett Bay (Geographic, WGS 84)
The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetric data, originally collected by NOAA for charting purposes, provide a framework for research and management activities along southern Narragansett Bay, show the composition and terrain of the seabed, and provide information on sediment transport and benthic habitat. During September 2014, bottom photographs and surficial ... |
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The 95th percentile of bottom shear stress for the Gulf of Maine south into the Middle Atlantic Bight, May 2010 to May 2011 (GMAINE_95th_perc.shp, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 0.03 degree (2.5-3.75 km, depending on latitude) ... |
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The half interpercentile range of bottom shear stress for the Gulf of Maine south into the Middle Atlantic Bight, May 2010 to May 2011 (GMAINE_hIPR, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 0.03 degree (2.5-3.75 km, depending on latitude) ... |
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The median of bottom shear stress for the Gulf of Maine south into the Middle Atlantic Bight, May 2010 to May 2011 (GMAINE_median.shp, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 0.03 degree (2.5-3.75 km, depending on latitude) ... |
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Recurrence interval of sediment mobility at select points in the Gulf of Maine south into the Middle Atlantic Bight for May, 2010 - May, 2011 (GMAINE_mobile_freq, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 0.03 degree (2.5-3.75 km, depending on latitude) ... |
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Percentage of time sediment is mobile for May, 2010 - May, 2011 at select points in the Gulf of Maine south into the Middle Atlantic Bight (GMAINE_mobile_perc.SHP, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 0.03 degree (2.5-3.75 km, depending on latitude) ... |
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The 95th percentile of bottom shear stress for the Gulf of Mexico, May 2010 to May 2011 (GMEX_95th_perc, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 0.04-0.06 degree (5-7 km, depending on latitude) ... |
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The half-interpercentile range of bottom shear stress for the Gulf of Mexico, May 2010 to May 2011 (GMEX_hIPR, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 0.04-0.06 degree (5-7 km, depending on latitude) ... |
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The median of bottom shear stress for the Gulf of Mexico, May 2010 to May 2011 (GMEX_median, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 0.04-0.06 degree (5-7 km, depending on latitude) ... |
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Recurrence interval of sediment mobility at select points in the Gulf of Mexico for May 2010 to May 2011 (GMEX_mobile_freq, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 0.04-0.06 degree (5-7 km, depending on latitude) ... |
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Percentage of time sediment is mobile for May 2010 to May 2011 at select points in the Gulf of Mexico (GMEX_mobile_perc, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 0.04-0.06 degree (5-7 km, depending on latitude) ... |
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95th percentile of wave-current bottom shear stress in the Middle Atlantic Bight for May, 2010 - May, 2011 (MAB_95th_perc.SHP)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ... |
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Half interpercentile range (half of the difference between the 16th and 84th percentiles) of wave-current bottom shear stress in the Middle Atlantic Bight for May, 2010 - May, 2011 (MAB_hIPR.SHP)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ... |
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Median of wave-current bottom shear stress in the Middle Atlantic Bight for May, 2010 - May, 2011 (MAB_median.SHP)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ... |
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Recurrence interval of sediment mobility at select points in the Middle Atlantic Bight for May, 2010 - May, 2011 (MAB_mobile_freq_v1_1.SHP, Geographic, WGS 84)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ... |
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Percentage of time sediment is mobile for May, 2010 - May, 2011 at select points in the Middle Atlantic Bight (MAB_mobile_perc.SHP)
The U.S. Geological Survey has been characterizing the regional variation in shear stress on the sea floor and sediment mobility through statistical descriptors. The purpose of this project is to identify patterns in stress in order to inform habitat delineation or decisions for anthropogenic use of the continental shelf. The statistical characterization spans the continental shelf from the coast to approximately 120 m water depth, at approximately 5 km resolution. Time-series of wave and circulation are ... |
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Oceanographic Time Series Data: Northeast Atlantic Outer Continental Shelf, Gulf of Maine and Georges Bank Marine Sanctuary
Time-series oceanographic data for the Northeast Atlantic outer continental shelf, Gulf of Maine and Georges Bank collected by the U.S. Geological Survey (USGS) or used in conjunction with USGS projects. These data are stored as NetCDF files using conventions developed by National Oceanic and Atmospheric Administration (NOAA) Pacific Marine Environmental Laboratory (PMEL) lab to be compatible with their EPIC system. Variables present in the files include: ocean current, temperature, pressure, conductivity, ... |
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Post-Expedition Report for USGS T-3 Ice Island Heat Flow Measurements in the High Arctic Ocean, 1963-1973
In February 1963, the U.S. Geological Survey (USGS) began a study of heat flow in the Arctic Ocean Basin and acquired data at 356 sites in Canada Basin and Nautilus Basin and on Alpha-Mendeleev Ridge by the end of the project in 1973. The USGS heat flow and associated piston coring operations were conducted from a scientific station on the freely drifting T-3 Ice island (also known as Fletcher's Ice Island). The Naval Arctic Research Laboratory (NARL) had established T-3 as a drifting research station in ... |
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USGS T-3 enhanced thermal data from T-3 Ice Island, 1963-73
The T-3 (Fletcher's) Ice Island in the Arctic Ocean was the site of a scientific research station re-established by the Naval Arctic Research Laboratory starting in 1962. Starting in 1963, the USGS acquired marine heat flow data and coincident sediment cores at sites in Canada Basin, Nautilus Basin, Mendeleev Ridge, and Alpha Ridge as the ice island drifted in the Amerasian Basin. At least 584 heat flow penetrations were attempted, and data were reported at 356 of these. This dataset is the enhanced version ... |
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USGS T-3 Original Thermal Gradient, Thermal Conductivity, and Heat Flow Data from T-3 Ice Island, 1963-73
The T-3 (Fletcher's) Ice Island in the Arctic Ocean was the site of a scientific research station re-established by the Naval Arctic Research Laboratory starting in 1962. Starting in 1963, the USGS acquired marine heat flow data and coincident sediment cores at sites in Canada Basin, Nautilus Basin, Mendeleev Ridge, and Alpha Ridge as the ice island drifted in the Amerasian Basin. At least 584 heat flow penetrations were attempted, and data were reported at 356 of these. This dataset is the digital version ... |
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Radiogenic heat content for selected cores recovered during T-3 Ice Island heat flow operations in the Arctic Ocean, 1963-74 (ver. 1.1, December 2022)
The T-3 (Fletcher's) Ice Island in the Arctic Ocean was the site of a scientific research station re-established by the Naval Arctic Research Laboratory starting in 1962. Starting in 1963, the USGS acquired marine heat flow data and coincident sediment cores at sites in Canada Basin, Nautilus Basin, Mendeleev Ridge, and Alpha Ridge as the ice island drifted in the Amerasian Basin. Radiogenic heat content in sediments can be an important contributor to measured heat flow. The USGS therefore measured ... |
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Folds--Offshore of Bolinas Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Bolinas map area, California. The vector data file is included in "Folds_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, ... |
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Folds--Offshore of Fort Ross Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Fort Ross map area, California. The vector data file is included in "Folds_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E ... |
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Folds--Offshore of Half Moon Bay Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Half Moon Bay map area, California. The vector data file is included in "Folds_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., ... |
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Folds--Offshore of Pacifica map area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Pacifica map area, California. The vector data file is included in "Folds_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R ... |
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Folds--Offshore of Salt Point Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Salt Point map area, California. The vector data file is included in "Folds_OffshoreSaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, ... |
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Folds--Offshore of San Gregorio Map Area, California
This part of SIM 3306 presents data for the folds for the geologic and geomorphic map of the Offshore of San Gregorio map area, California. The vector data file is included in "Folds_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, ... |
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Folds--Offshore of Point Reyes Map Area, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Point Reyes map area, California. The vector data file is included in "Folds_OffshorePointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A ... |
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Folds--Offshore Refugio Beach, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Refugio Beach map area, California. The vector data file is included in "Folds_OffshoreRefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G ... |
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Folds--Offshore of San Francisco Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of San Francisco map area, California. The vector data file is included in "Folds_OffshoreSanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R ... |
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Folds--Offshore of Tomales Point Map Area, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Offshore of Tomales Point map area, California. The vector data file is included in "Folds_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W. ... |
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Folds--Offshore of Carpinteria, California
This part of DS 781 presents fold data for the Offshore of Carpinteria map area, California. The vector data file is included in "Folds_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L., ... |
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Folds--Offshore of Coal Oil Point, California
This part of DS 781 presents fold data for the Offshore of Coal Oil Point map area, California. The vector data file is included in "Folds_OffshoreCoalOilPoint.zip," which is accessible from https ://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, H.G., ... |
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Folds--Offshore of Santa Barbara, California
This part of DS 781 presents fold data for the Offshore of Santa Barbara map area, California. The vector data file is included in "Folds_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., Seitz, G.G., ... |
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Folds--Offshore of Ventura, California
This part of DS 781 presents fold data for the Offshore of Ventura map area, California. The vector data file is included in "Folds_OffshoreVentura.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D ... |
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Folds--Drakes Bay and Vicinity Map Area, California
This part of DS 781 presents data of folds for the geologic and geomorphologic map of the Drakes Bay and Vicinity map area, California. The vector data file is included in "Folds_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., ... |
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Folds--Hueneme Canyon and Vicinity, California
This part of DS 781 presents data for folds for the geologic and geomorphic map of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Folds_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B. ... |
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Folds--Offshore of Monterey, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Monterey map area, California. The vector data file is included in "Folds_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, ... |
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Folds--Offshore Pigeon Point, California
This part of DS 781 presents data for the folds for the geologic and geomorphic map of the Offshore Pigeon Point map area, California. The vector data file is included in "Folds_OffshorePigeonPoint.zip," which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, ... |
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Folds--Offshore of Scott Creek map area, California
This part of DS 781 presents data for the folds for the geologic and geomorphic map of the Offshore of Scott Creek map area, California. The vector data file is included in "Folds_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie ... |
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Folds--Offshore of Aptos Map Area, California
This part of DS 781 presents data for the folds for the geologic and geomorphic map of the Offshore Aptos map area, California. The vector data file is included in "Folds_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R ... |
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Folds--Offshore of Point Conception Map Area, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Folds_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series� ... |
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Folds--Offshore of Gaviota Map Area, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Gaviota map area, California. The vector data file is included in "Folds_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. In the offshore part of the map area, closely-spaced seismic-reflection profiles image many shallow, west-northwest striking folds that have variable geometry, length, amplitude, continuity, and wavelength. The two longest folds, the 17-km-long Molino anticline ... |
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Folds--Offshore Santa Cruz, California
This part of DS 781 presents data for the folds for the geologic and geomorphic map of the Offshore of Santa Cruz map area, California. The vector data file is included in "Folds_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, ... |
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Folds--Monterey Canyon and Vicinity Map Area, California
This part of DS 781 presents fold data for the geologic and geomorphic map of the Monterey Canyon and Vicinity map area, California. The vector data file is included in "Folds_MontereyCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/MontereyCanyon/data_catalog_MontereyCanyon.html. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., ... |
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Folds—Point Sur to Point Arguello, California
This part of DS 781 presents data for the folds of the Point Sur to Point Arguello, California, region. The vector data file is included in the “Folds_PointSurToPointArguello.zip,” which is accessible from https://doi.org/10.5066/P97CZ0T7. Folds in the Point Sur to Point Arguello region are identified on seismic-reflection data based on warping and tilting of reflections. Folds were primarily mapped by interpretation of seismic reflection profile data collected by the U.S. Geological Survey between 2008 ... |
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Static chamber gas fluxes and carbon and nitrogen isotope content of age-dated sediment cores from a Phragmites wetland in Sage Lot Pond, Massachusetts, 2013-2015
Coastal wetlands are major global carbon sinks; however, quantification of carbon flux can be difficult in these heterogeneous and dynamic ecosystems. To characterize spatial and temporal variability in a New England salt marsh, static chamber measurements of greenhouse gas (GHG) fluxes were compared among major plant-defined zones (high marsh dominated by Distichlis spicata and a zone of invasive Phragmites australis) during 2013 and 2014 growing seasons. Two sediment cores were collected in 2015 from the ... |
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Hurricane Florence Overwash Extents
The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the southeast coast of the United States from North Carolina to Virginia and attributed to coastal processes during [Atlantic Basin] Hurricane Florence, which made landfall in the U.S. on September 14, 2018. |
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Hurricane Isaias Overwash Extents
The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the coast of the Carolinas and attributed to coastal processes during [Atlantic Basin] Hurricane Isaias, which made landfall in the U.S. on August 4, 2020. |
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Hurricane Matthew Overwash Extents (version 2.0, 20210916)
The National Assessment of Coastal Change Hazards project exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Florida, Georgia, North Carolina,and South Carolina coasts and attributed to coastal processes during [Atlantic Basin] Hurricane Matthew, which made landfall in the U.S. on October 8, 2018. |
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Hurricane Sally Overwash Extents
The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Florida and Alabama coast and attributed to coastal processes during [Atlantic Basin] Hurricane Sally, which made landfall in the U.S. on September 16, 2020. |
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Exposure potential of salt marsh units in Edwin B. Forsythe National Wildlife Refuge to environmental health stressors (polygon shapefile)
Natural and anthropogenic contaminants, pathogens, and viruses are found in soils and sediments throughout the United States. Enhanced dispersion and concentration of these environmental health stressors in coastal regions can result from sea level rise and storm-derived disturbances. The combination of existing environmental health stressors and those mobilized by natural or anthropogenic disasters could adversely impact the health and resilience of coastal communities and ecosystems. This dataset displays ... |
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Raster image of exposure potential to environmental health stressors in Edwin B. Forsythe National Wildlife Refuge (32-bit GeoTIFF)
Natural and anthropogenic contaminants, pathogens, and viruses are found in soils and sediments throughout the United States. Enhanced dispersion and concentration of these environmental health stressors in coastal regions can result from sea level rise and storm-derived disturbances. The combination of existing environmental health stressors and those mobilized by natural or anthropogenic disasters could adversely impact the health and resilience of coastal communities and ecosystems. This dataset displays ... |
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Collection, Analysis, and Age-Dating of Sediment Cores from Salt Marshes on the South Shore of Cape Cod, Massachusetts, From 2013 Through 2014
The accretion history of fringing microtidal salt marshes located on the south shore of Cape Cod, Massachusetts, was reconstructed from sediment cores collected in low and high marsh vegetation zones. The location of these marshes within protected embayments and the absence of large rivers on Cape Cod result in minimal sediment supply and a dominance of organic matter contribution to sediment peat. Age models based on 210-lead and 137-cesium were constructed to evaluate how vertical accretion and carbon ... |
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Collection, Analysis, and Age-Dating of Sediment Cores from Salt Marshes, Rhode Island, 2016
The accretion history of fringing salt marshes in Narragansett Bay, Rhode Island, was reconstructed from sediment cores. Age models, based on excess lead-210 and cesium-137 radionuclide analysis, were constructed to evaluate how vertical accretion and carbon burial rates have changed during the past century. The Constant Rate of Supply (CRS) age model was used to date six cores collected from three salt marshes. Both vertical accretion rates and carbon burial increased from 1900 to 2016, the year the data ... |
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Collection, analysis, and age-dating of sediment cores from Herring River wetlands and other nearby wetlands in Wellfleet, Massachusetts, 2015–17
The Herring River estuary in Wellfleet, Cape Cod, Massachusetts, has been tidally restricted for more than a century by a dike constructed near the mouth of the river. Upstream from the dike, the tidal restriction has caused the conversion of salt marsh wetlands to various other ecosystems including impounded freshwater marshes, flooded shrub land, drained forested upland, and brackish wetlands dominated by Phragmites australis. This estuary is now managed by the National Park Service, which plans to ... |
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Collection, analysis, and age-dating of sediment cores from mangrove wetlands in San Juan Bay Estuary, Puerto Rico, 2016
The San Juan Bay Estuary, Puerto Rico, contains mangrove forests that store significant amounts of organic carbon in soils and biomass. There is a strong urbanization gradient across the estuary, from the highly urbanized and clogged Caño Martin Peña in the western part of the estuary, a series of lagoons in the center of the estuary, and a tropical forest reserve (Piñones) in the easternmost part with limited urbanization. We collected sediment cores to determine carbon burial rates and vertical ... |
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Elevation of the late Wisconsinan to early Holocene regressive unconformity (Ur) offshore of western and southern Martha's Vineyard and north of Nantucket, Massachusetts
Geologic, sediment texture, and physiographic zone maps characterize the sea floor south and west of Martha's Vineyard and north of Nantucket, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This ... |
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Holocene fluvial and estuarine (Qfe) and nearshore marine (Qmn) sediment thickness offshore of western and southern Martha's Vineyard and north of Nantucket, Massachusetts
Geologic, sediment texture, and physiographic zone maps characterize the sea floor south and west of Martha's Vineyard and north of Nantucket, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This ... |
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Collection, analysis, and age-dating of sediment cores from a salt marsh platform and ponds, Rowley, Massachusetts, 2014-15
Sediment cores were collected from three sites within the Plum Island Ecosystems Long-Term Ecological Research (PIE-LTER) domain in Massachusetts to obtain estimates of long-term marsh decomposition and evaluate shifts in the composition and reactivity of sediment organic carbon in disturbed marsh environments. Paired sediment cores were collected from three sites on the marsh platform and from three ponds; these cores were about 100 and 50 centimeters in length, respectively. The marsh sites had similar ... |
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Collection, analysis, and age-dating of sediment cores from mangrove and salt marsh ecosystems in Tampa Bay, Florida, 2015
Coastal wetlands in Tampa Bay, Florida, are important ecosystems that deliver a variety of ecosystem services. Key to ecosystem functioning is wetland response to sea-level rise through accumulation of mineral and organic sediment. The organic sediment within coastal wetlands is composed of carbon sequestered over the time scale of the wetland’s existence. This study was conducted to provide information on soil accretion and carbon storage rates across a variety of coastal ecosystems that was utilized in ... |
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Collection, analysis, and age-dating of sediment cores from natural and restored salt marshes on Cape Cod, Massachusetts, 2015-16
Nineteen sediment cores were collected from five salt marshes on the northern shore of Cape Cod where previously restricted tidal exchange was restored to part of the marshes. Cores were collected in duplicate from two locations within each marsh complex: one upstream and one downstream from the former tidal restriction (typically caused by an undersized culvert or a berm). The unaltered, natural downstream sites provide a comparison against the historically restricted upstream sites. The sampled cores ... |
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Hurricane Delta Overwash Extents
The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Louisiana coast and attributed to coastal processes during [Atlantic Basin] Hurricane Delta, which made landfall in the U.S. on October 9, 2020. |
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Hurricane Irma Overwash Extents
The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Florida coast and attributed to coastal processes during [Atlantic Basin] Hurricane Irma, which made landfall in the U.S. on September 9, 2017. |
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Hurricane Laura Overwash Extents
The National Assessment of Coastal Change Hazards project project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Louisiana coast and attributed to coastal processes during [Atlantic Basin] Hurricane Laura, which made landfall in the U.S. on August 27, 2020. |
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Hurricane Michael Overwash Extents
The National Assessment of Coastal Change Hazards project at the U.S. Geological Survey (USGS) exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the Florida coast and attributed to coastal processes during [Atlantic Basin] Hurricane Michael, which made landfall in the U.S. on October 10, 2018. |
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Hurricane Zeta Overwash Extents
The National Assessment of Coastal Change Hazards project exists to understand and predict storm impacts to our nation's coastlines. This geospatial dataset defines the alongshore extent of overwash sediments deposited along the Louisiana coast and attributed to coastal processes during [Atlantic Basin] Hurricane Zeta, which made landfall in the U.S. on October 28, 2020. |
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Sediment deposition in the Elwha River estuary, Washington, measured on rod surface elevation tables (RSETs) from 2011 to 2014
This portion of the data release presents sediment deposition in the estuary as measured using rod surface elevation tables (RSETs) at fifteen locations throughout the Elwha River estuary, Washington, from August 2011 to June 2014 (no associated USGS Field Activities numbers because data were collected predominantly by biologists from the Lower Elwha Klallam Tribe). The locations of the RSETs were determined with a hand-held global positioning system (GPS). We measured sediment deposition from 2011 to 2013 ... |
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Geochemical analysis of authigenic carbonates and chemosynthetic mussels at Atlantic Margin seeps (ver. 2.0, March 2019)
Isotopic analyses of authigenic carbonates and methanotrophic deep-sea mussels, Bathymodiolus sp., was performed on samples collected from seep fields in the Baltimore and Norfolk Canyons on the north Atlantic margin. Samples were collected using remotely operated underwater vehicles (ROVs) during three different research cruises in 2012, 2013, and 2015. Analyses were performed by several different laboratories, and the results are presented in spreadsheet format. |
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Characterization of seafloor photographs near the mouth of the Elwha River during the first two years of dam removal (2011-2013)
We characterized seafloor sediment conditions near the mouth of the Elwha River from underwater photographs taken every four hours from September 2011 to December 2013. A digital camera was affixed to a tripod that was deployed in approximately 10 meters of water. Each photograph was qualitatively characterized as one of six categories: (1) base, or no sediment; (2) low sediment; (3) medium sediment; (4) high sediment; (5) turbid; or (6) kelp. For base conditions, no sediment was present on the seafloor. ... |
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Geochemical analysis of seeps along the Queen Charlotte Fault
Geochemical analyses of authigenic carbonates, bivalves, and pore fluids were performed on samples collected from seep fields along the Queen Charlotte Fault, a right lateral transform boundary that separates the Pacific and North American tectonic plates. Samples were collected using grab samplers and piston cores, and were collected during three different research cruises in 2011, 2015, and 2017. |
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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 1967-10-18
Presented here is a point cloud produced by the U.S. Geological Survey (USGS) from historical U.S. Air Force vertical aerial imagery, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was downloaded from USGS Eros Data Center and processed using structure-from-motion ... |
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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-03-08
Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ... |
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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-05-19
Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point Cloud Coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ... |
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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-05-27
Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ... |
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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-06-13
Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ... |
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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-06-26
Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ... |
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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-10-12
Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using a UAS-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Ricoh GR camera in DNG format and processed using structure-from-motion photogrammetry ... |
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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-12-07
Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using a UAS-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. Point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Ricoh GR camera in DNG format and processed using structure-from-motion photogrammetry with ... |
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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-12-21
Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. Point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ... |
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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2018-01-29
Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. Point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ... |
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Landslide debris aprons offshore of southern California, 2023
Landslide debris aprons have been mapped offshore of Southern California. Polygons were mapped from visual interpretation of high-resolution multibeam echosounder data (MBES), single-beam echosounder data, and seismic reflection data. |
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Submarine-landslide scarps--Hueneme Canyon and Vicinity, California
This part of DS 781 presents data for the submarine-landslide scarps for the geologic and geomorphic map of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "SubmarineLandslideScarps_HuenemeCanyon.zip," which is accessible from http://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G. ... |
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Landslide evacuation zones offshore of Southern California, 2023
Landslide evacuation zones, which represent the areas from which material is removed by landslide processes, have been mapped offshore of Southern California. Polygons were mapped from visual interpretation of high-resolution multibeam echosounder data (MBES) and single-beam echosounder data. |
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Landslides offshore of southern California, 2023
Landslides have been mapped offshore of Southern California. Polygons were mapped from visual interpretation of high-resolution multibeam echosounder data (MBES), single-beam echosounder data, and seismic reflection data. |
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Landslide mass-wasting zones offshore of Southern California, 2023
Landslide mass-wasting zones have been mapped offshore of Southern California. Polygons were mapped from visual interpretation of high-resolution multibeam echosounder data (MBES) and single-beam echosounder data. |
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Landslide scarps offshore of Southern California, 2023
Landslide scarp features have been mapped offshore of Southern California. Polygons were mapped from visual interpretation of high-resolution multibeam echosounder data (MBES) and single-beam echosounder data. |
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Unprocessed aerial imagery from 9 December 2015 coastal survey of Central California.
This is a set of 1132 oblique aerial photogrammetric images and their derivatives, collected from Capitola to Pajaro Dunes with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 January 2016 coastal survey of Central California.
This is a set of 1836 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 February 2016 coastal survey of Central California.
This is a set of 3494 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 2 March 2016 coastal survey of Central California.
This is a set of 1309 oblique aerial photogrammetric images and their derivatives, collected from Santa Cruz to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 March 2016 coastal survey of Central California.
This is a set of 2753 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 15 September 2016 coastal survey of Central California.
This is a set of 1600 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 26 September 2016 coastal survey of Central California.
This is a set of 1569 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ano Nuevo with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 1 December 2016 coastal survey of Central California.
This is a set of 3234 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 20 December 2016 coastal survey of Central California.
This is a set of 3036 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 25 January 2017 coastal survey of Central California.
This is a set of 4521 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Cape San Martin with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 22 February 2017 coastal survey of Central California.
This is a set of 4808 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Lucia with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 8 March 2017 coastal survey of Central California.
This is a set of 5642 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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Unprocessed aerial imagery from 5 April 2017 coastal survey of Central California.
This is a set of 5044 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Cape San Martin with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ... |
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Unprocessed aerial imagery from 8 May 2017 coastal survey of Central California.
This is a set of 1975 oblique aerial photogrammetric images and their derivatives, collected from Pedro Point to Sunset Beach with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ... |
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