Management methods

Techniques of judiciously controlling or directing resources for a predetermined goal.

126 results listed by similarity [list alphabetically]
St. Petersburg Coastal and Marine Science Center's Geologic Core and Sample Database Metadata

This database contains a comprehensive inventory of geologic (coral, coral reef, limestone, and sediment) cores and samples collected, analyzed, published, and/or archived by, or in collaboration with, the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC). The SPCMSC Geologic Core and Sample Database includes geologic cores and samples collected beginning in the 1970s to present day, from study sites across the world. This database captures metadata about samples ...

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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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Coast Train--Labeled imagery for training and evaluation of data-driven models for image segmentation

Coast Train is a library of images of coastal environments, annotations, and corresponding thematic label masks (or ‘label images’) collated for the purposes of training and evaluating machine learning (ML), deep learning, and other models for image segmentation. It includes image sets from both geospatial satellite, aerial, and UAV imagery and orthomosaics, as well as non-geospatial oblique and nadir imagery. Images include a diverse range of coastal environments from the U.S. Pacific, Gulf of Mexico, ...

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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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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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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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Intrinsic and Extrinsic Calibration Data From USGS CoastCam deployed at Madeira Beach, Florida

A digital video camera was installed at Madeira Beach, Florida (FL) and faced west along the beach. Every hour during daylight hours, daily from 2017 to 2022, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological Survey (USGS) research project to study the beach and ...

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Imagery from USGS CoastCam deployed at Madeira Beach, Florida

A digital video camera was installed at Madeira Beach, Florida (FL) and faced west along the beach. Every hour during daylight hours, daily from 2017 to 2022, the camera collected raw video and produced snapshots and time-averaged image products. The images included in this data release were collected from January 21, 2017, to December 31, 2017. The camera is part of a U.S. Geological Survey (USGS) research project to study the beach and nearshore environment. USGS researchers analyzed the imagery collected ...

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ViTexOCR; a script to extract text overlays from digital video

The ViTexOCR script presents a new method for extracting navigation data from videos with text overlays using optical character recognition (OCR) software. Over the past few decades, it was common for videos recorded during surveys to be overlaid with real-time geographic positioning satellite chyrons including latitude, longitude, date and time, as well as other ancillary data (such as speed, heading, or user input identifying fields). Embedding these data into videos provides them with utility and ...

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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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hawaii_oha - Overall Hazard Assessment in the coastal zone of Hawaii, Hawaii

Overall Hazard Assessment in the coastal zone of Hawaii, Hawaii

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hawaii_sea - Sea Level Hazard Intensity Level in the coastal zone of Hawaii, Hawaii

Sea Level Hazard Intensity Level in the coastal zone of Hawaii, Hawaii

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hawaii_sfl - Stream Flooding Hazard Intensity Level in the coastal zone of Hawaii, Hawaii

Stream Flooding Hazard Intensity Level in the coastal zone of Hawaii, Hawaii

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hawaii_stm - Storm Hazard Intensity Level in the coastal zone of Hawaii, Hawaii

Storm Hazard Intensity Level in the coastal zone of Hawaii, Hawaii

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hawaii_tsu - Tsunami Hazard Intensity Level in the coastal zone of Hawaii, Hawaii

Tsunami Hazard Intensity Level in the coastal zone of Hawaii, Hawaii

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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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hawaii_wav - High Wave Hazard Intensity Level in the coastal zone of Hawaii, Hawaii

High Wave 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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kauai_oha - Overall Hazard Assessment in the coastal zone of Kauai, Hawaii

Overall Hazard Assessment in the coastal zone of Kauai, Hawaii

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kauai_sea - Sea Level Hazard Intensity Level in the coastal zone of Kauai, Hawaii

Sea Level Hazard Intensity Level in the coastal zone of Kauai, Hawaii

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kauai_sfl - Stream Flooding Hazard Intensity Level in the coastal zone of Kauai, Hawaii

Stream Flooding Hazard Intensity Level in the coastal zone of Kauai, Hawaii

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kauai_stm - Storm Hazard Intensity Level in the coastal zone of Kauai, Hawaii

Storm Hazard Intensity Level in the coastal zone of Kauai, Hawaii

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kauai_tsu - Tsunami Hazard Intensity Level in the coastal zone of Kauai, Hawaii

Tsunami Hazard Intensity Level in the coastal zone of Kauai, 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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kauai_wav - High Wave Hazard Intensity Level in the coastal zone of Kauai, Hawaii

High Wave 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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lanai_oha - Overall Hazard Assessment in the coastal zone of Lanai, Hawaii

Overall Hazard Assessment in the coastal zone of Lanai, Hawaii

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lanai_sea - Sea Level Hazard Intensity Level in the coastal zone of Lanai, Hawaii

Sea Level Hazard Intensity Level in the coastal zone of Lanai, Hawaii

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lanai_sfl - Stream Flooding Hazard Intensity Level in the coastal zone of Lanai, Hawaii

Stream Flooding Hazard Intensity Level in the coastal zone of Lanai, Hawaii

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lanai_stm - Storm Hazard Intensity Level in the coastal zone of Lanai, Hawaii

Storm Hazard Intensity Level in the coastal zone of Lanai, Hawaii

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lanai_tsu - Tsunami Hazard Intensity Level in the coastal zone of Lanai, Hawaii

Tsunami Hazard Intensity Level in the coastal zone of Lanai, 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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lanai_wav - High Wave Hazard Intensity Level in the coastal zone of Lanai, Hawaii

High Wave 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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maui_oha - Overall Hazard Assessment in the coastal zone of Maui, Hawaii

Overall Hazard Assessment in the coastal zone of Maui, Hawaii

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maui_sea - Sea Level Hazard Intensity Level in the coastal zone of Maui, Hawaii

Sea Level Hazard Intensity Level in the coastal zone of Maui, Hawaii

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maui_sfl - Stream Flooding Hazard Intensity Level in the coastal zone of Maui, Hawaii

Stream Flooding Hazard Intensity Level in the coastal zone of Maui, Hawaii

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maui_stm - Storm Hazard Intensity Level in the coastal zone of Maui, Hawaii

Storm Hazard Intensity Level in the coastal zone of Maui, Hawaii

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maui_tsu - Tsunami Hazard Intensity Level in the coastal zone of Maui, Hawaii

Tsunami Hazard Intensity Level in the coastal zone of Maui, 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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maui_wav - High Wave Hazard Intensity Level in the coastal zone of Maui, Hawaii

High Wave 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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molo_oha - Overall Hazard Assessment in the coastal zone of Molokai, Hawaii

Overall Hazard Assessment in the coastal zone of Molokai, Hawaii

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molo_sea - Sea Level Hazard Intensity Level in the coastal zone of Molokai, Hawaii

Sea Level Hazard Intensity Level in the coastal zone of Molokai, Hawaii

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molo_sfl - Stream Flooding Hazard Intensity Level in the coastal zone of Molokai, Hawaii

Stream Flooding Hazard Intensity Level in the coastal zone of Molokai, Hawaii

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molo_stm - Storm Hazard Intensity Level in the coastal zone of Molokai, Hawaii

Storm Hazard Intensity Level in the coastal zone of Molokai, Hawaii

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molo_tsu - Tsunami Hazard Intensity Level in the coastal zone of Molokai, Hawaii

Tsunami Hazard Intensity Level in the coastal zone of Molokai, 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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molo_wav - High Wave Hazard Intensity Level in the coastal zone of Molokai, Hawaii

High Wave 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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oahu_oha - Overall Hazard Assessment in the coastal zone of Oahu, Hawaii

Overall Hazard Assessment in the coastal zone of Oahu, Hawaii

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oahu_sea - Sea Level Hazard Intensity Level in the coastal zone of Oahu, Hawaii

Sea Level Hazard Intensity Level in the coastal zone of Oahu, Hawaii

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oahu_sfl - Stream Flooding Hazard Intensity Level in the coastal zone of Oahu, Hawaii

Stream Flooding Hazard Intensity Level in the coastal zone of Oahu, Hawaii

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oahu_stm - Storm Hazard Intensity Level in the coastal zone of Oahu, Hawaii

Storm Hazard Intensity Level in the coastal zone of Oahu, Hawaii

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oahu_tsu - Tsunami Hazard Intensity Level in the coastal zone of Oahu, Hawaii

Tsunami Hazard Intensity Level in the coastal zone of Oahu, 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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oahu_wav - High Wave Hazard Intensity Level in the coastal zone of Oahu, Hawaii

High Wave 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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sand_oha - Overall Hazard Assessment in the coastal zone of Sand Island (Oahu), Hawaii

Overall Hazard Assessment in the coastal zone of Sand Island (Oahu), Hawaii

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sand_sea - Sea Level Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii

Sea Level Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii

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sand_sfl - Stream Flooding Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii

Stream Flooding Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii

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sand_stm - Storm Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii

Storm Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii

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sand_tsu - Tsunami Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii

Tsunami Hazard Intensity Level in the coastal zone of Sand Island (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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sand_wav - High Wave Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii

High Wave Hazard Intensity Level in the coastal zone of Sand Island (Oahu), Hawaii

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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Aerial_Shorelines_1940_2015.shp - Dauphin Island, Alabama Shoreline Data Derived from Aerial Imagery from 1940 to 2015

Aerial_WDL_Shorelines.zip features digitized historic shorelines for the Dauphin Island coastline from October 1940 to November 2015. This dataset contains 10 Wet Dry Line (WDL) shorelines separated into 58 shoreline segments alongshore Dauphin Island, AL. The individual sections are divided according to location along the island and shoreline type: open-ocean, back-barrier, marsh shoreline. Imagery of Dauphin Island, Alabama was acquired from several sources including the United States Geological Survey ...

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Shapefile of Historical Bathymetric Soundings for Mississippi and Alabama Derived from National Ocean Service (NOS) Hydrographic Sheets

Hydrographic sheets (H-sheets) and nautical charts produced by the National Ocean Service (NOS) during the 1800s provide historic sounding (water depth) measurements of coastal areas. The data can be vectorized into a geographic information system (GIS), adjusted to a modern vertical datum, and converted into a digital elevation model to provide an interpretation of the historic seafloor elevation. These data were produced to provide an estimate of historical bathymetry for the Mississippi-Alabama coastal ...

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Shapefile of Historical shorelines for Fire Island and Great South Bay, New York, derived from previously unpublished National Oceanic and Atmospheric Administration (NOAA) 1834-1875 topographic sheets

Topographic sheets (t-sheets) produced by the National Ocean Service (NOS) during the 1800s provide the position of past shorelines. The shoreline data can be vectorized into a geographic information system (GIS) and compared to modern shoreline data to calculate estimates of long-term shoreline rates of change. Many t-sheets were scanned and digitized by the National Oceanic and Atmospheric Administration (NOAA) and are available on the NOAA Shoreline website (https://shoreline.noaa.gov/data/datasheets/t ...

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Georeferenced scans of National Oceanic and Atmospheric Administration (NOAA) topographic sheets (T-Sheets) Collected Along the Fire Island and Great South Bay, New York, Coastline from 1834-1875

Topographic sheets (t-sheets) produced by the National Ocean Service (NOS) during the 1800s provide the position of past shorelines. The shoreline data can be vectorized into a geographic information system (GIS) and compared to modern shoreline data to calculate estimates of long-term shoreline rates of change. Many t-sheets were scanned and digitized by the National Oceanic and Atmospheric Administration (NOAA) and are available on the NOAA Shoreline web site (https://shoreline.noaa.gov/data/datasheets/t ...

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Transects with linear regression rates of change for GPS, Worldview, and aerial image shorelines for the Grand Bay National Estuarine Research Reserve in Mississippi from 2013-2020

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a ...

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GrandBay_2010_Shoreline.shp - Grand Bay, Mississippi/Alabama, Shoreline Data Derived from 2010 Aerial Imagery

GrandBay_2010_Shoreline.zip features a digitized historical shoreline for the Grand Bay, Mississippi (MS) coastline (Pascagoula, MS to Point aux Pins, Alabama [AL]) derived from 2010 aerial imagery. Imagery of the Mississippi and Alabama coastlines was acquired from the National Agriculture Imagery Program (NAIP) and the city of Mobile, AL. Using ArcMap 10.3.1, the imagery was used to delineate and digitize the historical shoreline as either the Wet Dry Line (WDL) along sandy beaches or the vegetation edge ...

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GrandBay_2012_Shoreline.shp - Grand Bay, Mississippi/Alabama, Shoreline Data Derived from 2012 Aerial Imagery

GrandBay_2012_Shoreline.zip features a digitized historical shoreline for the Grand Bay, Mississippi (MS) coastline (Pascagoula, MS to Bayou La Fourche Bay, Alabama [AL]) derived from 2012 aerial imagery. Imagery of the Mississippi and Alabama coastlines was acquired from the National Agriculture Imagery Program (NAIP). Using ArcMap 10.3.1, the imagery was used to delineate and digitize a coarse historical shoreline as either proximal Wet Dry Line along sandy beaches or proximal vegetation edge along the ...

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Grid File of Historical Bathymetric Soundings for Mississippi and Alabama Derived from National Ocean Service (NOS) Hydrographic Sheets

Hydrographic sheets (H-sheets) and nautical charts produced by the National Ocean Service (NOS) during the 1800s provide historic sounding (water depth) measurements of coastal areas. The data can be vectorized into a geographic information system (GIS), adjusted to a modern vertical datum, and converted into a digital elevation model to provide an interpretation of the historic seafloor elevation. These data were produced to provide an estimate of historical bathymetry for the Mississippi-Alabama coastal ...

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Georeferenced National Ocean Service (NOS) Hydrographic Sheets for Grand Bay, Mississippi, and Surrounding Areas

Hydrographic sheets (H-sheets) and nautical charts produced by the National Ocean Service (NOS) during the 1800s provide historic sounding (water depth) measurements of coastal areas. The data can be vectorized into a geographic information system (GIS), adjusted to a modern vertical datum, and converted into a digital elevation model to provide an interpretation of the historic seafloor elevation. These data were produced to provide an estimate of historical bathymetry for the Mississippi-Alabama coastal ...

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Georeferenced Scans of National Oceanic and Atmospheric Administration (NOAA) T-Sheets Collected Along the New Jersey Coastline from 1839-1875

Historical shoreline surveys were conducted by the National Ocean Service (NOS), dating back to the early 1800s. The maps resulting from these surveys, often called t-sheets, provide a reference of historical shoreline position that can be compared to modern data to identify shoreline change. The t-sheets are stored at the National Archives and many have been scanned by the National Oceanic and Atmospheric Administration (NOAA) and are available on the NOAA Shoreline Web site (http://www.shoreline.noaa.gov ...

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Historical Shoreline for New Jersey (1971 to 1978): Vector Digital Data

New_Jersey_1971_78_Digitized_Shoreline.zip features a digitized historic shoreline for the New Jersey coastline (Point Pleasant, NJ to Longport, NJ) from 1971 to 1978. Imagery of the New Jersey coastline was acquired from the New Jersey Geographic Information Network (NJGIN) as two images: “1970 NJDEP Wetlands Basemap” (1971-78) and the “1977 Tidelands Basemaps” (1977-78). These images are available as a web mapping service (WMS) through the NJGIN website (https://njgin.state.nj.us/NJ_NJGINExplorer ...

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Shorelines for Barnegat and Great Bay, NJ: 1839 to 2012 (ver 1.1, December 2017)

This data set represents vector shorelines for the New Jersey coastline (Point Pleasant, NJ to Longport, NJ) from 1839 to 2012. Data were obtained from multiple data sources, including the U.S. Geological Survey (USGS), National Oceanic and Atmospheric Administration (NOAA), and New Jersey Department of Environmental Protection (NJDEP). Shorelines were obtained from the original provider and merged into a single file in order to conduct shoreline change analysis for the open-ocean and estuarine shorelines ...

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Shoreline Change Rates for Barnegat and Great Bay, NJ: 1839 to 2012 (ver 1.1, December 2017)

This dataset represents shoreline change rates for the New Jersey coastline (Point Pleasant, NJ to Longport, NJ) from 1839 to 2012. Shoreline data were obtained from multiple data sources, including the U.S. Geological Survey (USGS), National Oceanic and Atmospheric Administration (NOAA), and New Jersey Department of Environmental Protection (NJDEP). Datasets were compiled and analyzed using the R package Analyzing Moving Boundaries Using R (AMBUR) program. Rates of shoreline change can be used for ...

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Point based shorelines derived from global positioning system data with nearest WorldView shoreline distance for the Grand Bay National Estuarine Research Reserve in Mississippi from 2013-2020

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a ...

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Vectorized Marsh Shorelines for the Grand Bay National Estuarine Research Reserve in Mississippi and Alabama from 1848 to 2017

This dataset represents a compilation of vector shorelines in the Grand Bay National Estuarine Research Reserve (Mississippi and Alabama) from 1848 to 2017. Shoreline data were obtained from multiple data sources, including the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the Grand Bay National Estuarine Research Reserve (GBNERR), and the Mississippi Office of Geology (MOG). All shoreline data types have uncertainty associated with delineating the shoreline ...

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Vectorized marsh shorelines derived from high resolution aerial imagery for the Grand Bay National Estuarine Research Reserve in Mississippi from 2014-2020

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a ...

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Vectorized marsh shorelines derived from global positioning system data for the Grand Bay National Estuarine Research Reserve in Mississippi from 2013-2020

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a ...

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Vectorized Marsh Shorelines derived from WorldView imagery for the Grand Bay National Estuarine Research Reserve in Mississippi from 2013-2020

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a ...

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Transects with Shoreline Change Rates for the Grand Bay National Estuarine Research Reserve in Mississippi and Alabama from 1848 to 2017

This dataset contains shoreline change rates for the Grand Bay National Estuarine Research Reserve from 1848 to 2017. Shoreline data were obtained from multiple data sources, including the U.S. Geological Survey (USGS), National Oceanic and Atmospheric Administration (NOAA), the Grand Bay National Estuarine Research Reserve(GBNERR), and the Mississippi Office of Geology (MOG). Datasets were compiled and analyzed using the R package Analyzing Moving Boundaries Using R (AMBUR) program. Rates of shoreline ...

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Transects with net change results for GPS and Worldview shorelines for the Grand Bay National Estuarine Research Reserve in Mississippi from 2013-2020

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into coastal management, including shoreline monitoring and change analysis. Geospatial shoreline data were created from a ...

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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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Inferred hydrodynamic residence time in salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey

As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ...

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Change in salinity in salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy

As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ...

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Change in salinity exposure of salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy

As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ...

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Change in suspended sediment concentration over the salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey during Hurricane Sandy

As part of the Hurricane Sandy Science Plan, the U.S. Geological Survey is expanding National Assessment of Coastal Change Hazards and forecast products to coastal wetlands. The intent is to provide federal, state, and local managers with tools to estimate the vulnerability of coastal wetlands to various factors and to evaluate their ecosystem service potential. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their ...

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Shoreline change rates in salt marsh units in Edwin B. Forsythe National Wildlife Refuge, New Jersey

Monitoring shoreline change is of interest in many coastal areas because it enables quantification of land loss over time. Evolution of shoreline position is determined by the balance between erosion and accretion along the coast. In the case of salt marshes, erosion along the water boundary causes a loss of ecosystem services, such as habitat provision, carbon storage, and wave attenuation. In terms of vulnerability, higher shoreline erosion rates indicate higher vulnerability. This dataset ...

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