Agents of coastal change

natural phenomena and human activities that cause changes in coastal processes, landscapes, and ecosystems.

835 results listed alphabetically [list by similarity]
3D bathymetric surfaces of low- and high-relief sites from the coral reef flat off Waiakane, Molokai

3D bathymetric surfaces of low- and high-relief sites from the coral reef flat off Waiakane, Molokai, were created using structure-from-motion (SfM) techniques. The two study sites are located approximately 640 m from shore and approximately 20 m apart in the alongshore direction. At each site, an approximate 12-meter diameter area was imaged in three passes by a swimmer using a handheld digital camera. These images were fed into Structure-from-Motion (SfM) software to produce high-resolution (fine-scale), ...

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Aerial imagery from the UAS survey of the coral reef off Waiakane, Molokai, Hawaii, 24 June 2018

This portion of the data release presents raw aerial imagery collected during an unoccupied aerial system (UAS) survey of the coral reef off Waiakane, Molokai, Hawaii, on 24 June 2018. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted in a nadir orientation using a fixed mount. Before each flight, the camera’s digital ISO, aperture, and shutter speed were adjusted for ambient light ...

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Aerial imagery from UAS survey of the intertidal zone at Lone Tree Point, Kiket Bay, WA, 2019-06-05

This portion of the data release presents the raw aerial imagery collected during the Unmanned Aerial System (UAS) survey of the intertidal zone at Lone Tree Point, Kiket Bay, WA, on 2019-06-05. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. For flights F01, F02, F03, F04, and F05 the ...

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Aerial imagery from UAS survey of the intertidal zone at Post Point, Bellingham Bay, WA, 2019-06-06

This portion of the data release presents the raw aerial imagery collected during an Unmanned Aerial System (UAS) survey of the intertidal zone at Post Point, Bellingham Bay, WA, on 2019-06-06. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. The UAS was flown on pre-programmed autonomous ...

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Aerial imagery from UAS survey of the intertidal zone at Puget Creek and Dickman Mill Park, Tacoma, WA, 2019-06-03

This portion of the data release presents the raw aerial imagery collected during an Unmanned Aerial System (UAS) survey of the intertidal zone at Puget Creek and Dickman Mill Park, Tacoma, WA, on 2019-06-03. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. The UAS was flown on pre ...

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Aerial imagery from UAS survey of the intertidal zone at West Whidbey Island, WA, 2019-06-04

This portion of the data release presents the raw aerial imagery collected during the unmanned aerial system (UAS) survey of the intertidal zone at West Whidbey Island, WA, on 2019-06-04. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. Flights using both a nadir camera orientation and an oblique camera orientation were conducted. For the nadir flights (F04, F05, F06, F07, and F08), the camera was mounted ...

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BEWARE2 database: A meta-process model to assess wave-driven flooding hazards on morphologically diverse, coral reef-lined coasts

This dataset contains the reef profiles and resulting hydrodynamic outputs of the "Broad-range Estimator of Wave Attack in Reef Environments" (BEWARE-2) meta-process modeling system. A process-based, wave-resolving hydrodynamic model (XBeach Non-Hydrostatic+, "XBNH+") was used to create a large synthetic database for use in BEWARE-2, relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts. Building on previous work, BEWARE-2 improves system understanding ...

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BEWARE database: A Bayesian-based system to assess wave-driven flooding hazards on coral reef-lined coasts

A process-based wave-resolving hydrodynamic model (XBeach Non-Hydrostatic, ‘XBNH’) was used to create a large synthetic database for use in a “Bayesian Estimator for Wave Attack in Reef Environments” (BEWARE), relating incident hydrodynamics and coral reef geomorphology to coastal flooding hazards on reef-lined coasts. Building on previous work, BEWARE improves system understanding of reef hydrodynamics by examining the intrinsic reef and extrinsic forcing factors controlling runup and flooding on ...

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Buck Island, U.S. Virgin Islands, wave and water level data, 2015

Time series data of wave height and water surface elevation were acquired for 147 days at four locations off of the north coast and four locations off the south coast of Buck Island, U.S. Virgin Islands, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on the reefs were as follows: BUI15S1T and BUI15N1T – fore reef BUI15S2T and BUI15N2T – outer reef flat BUI15S3T and BUI15N3T – ...

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Buck Island, U.S. Virgin Islands, wave and water level data, 2016

Time series data of wave height and water surface elevation were acquired for 109 days at four locations off of the north coast and four locations off the south coast of Buck Island, U.S. Virgin Islands, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on the reefs were as follows: BUI16S1T and BUI16N1T – fore reef BUI16S2T and BUI16N2T – outer reef flat BUI16S3T and BUI16N3T – ...

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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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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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Central California CoSMoS v3.1 projections of coastal cliff retreat due to 21st century sea-level rise

This dataset contains spatial projections of coastal cliff retreat (and associated uncertainty) for future scenarios of sea-level rise (SLR) in Central California. Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical models and field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power, as part of Coastal Storm Modeling System (CoSMoS). Read metadata and references ...

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Central California CoSMoS v3.1 projections of shoreline change due to 21st century sea-level rise

This dataset contains projections of shoreline positions and uncertainty bands for future scenarios of sea-level rise. Projections were made using the Coastal Storm Modeling System - Coastal One-line Assimilated Simulation Tool (CoSMoS-COAST), a numerical model forced with global-to-local nested wave models and assimilated with lidar-derived shoreline vectors. Read metadata carefully. Details: Projections of shoreline position in the Central Coast of California are made for scenarios of 25, 50, 75, 92, 100 ...

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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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Climatological wave height, wave period and wave power along coastal areas of the East Coast of the United States and Gulf of Mexico

This U.S. Geological Survey data release provides data on spatial variations in climatological wave parameters (significant wave height, peak wave period, and wave power) for coastal areas along the United States East Coast and Gulf of Mexico. Significant wave height is the average wave height, from crest to trough, of the highest one-third of the waves in a specific time period. Peak wave period is the wave period associated with the most energetic waves in the wave spectrum in a specific time period. Wave ...

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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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Coral growth parameters, Kahekili, west Maui

Surface runoff and submarine groundwater discharge in particular are known vectors to the coastal ocean of elevated nutrients and contaminants leading to eutrophication, algal overgrowth, and coral disease. Freshwater discharging directly from submarine groundwater vents off of Kahekili Beach Park, Kaanapali, in West Maui contains elevated nutrient concentrations and lower pH values. Coral cores were collected in July 2013 from the shallow reef at Kahekili in Kaanapali, West Maui, Hawaii from ...

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Coral reef profiles for wave-runup prediction

This data release includes representative cluster profiles (RCPs) from a large (>24,000) selection of coral reef topobathymetric cross-shore profiles (Scott and others, 2020). We used statistics, machine learning, and numerical modelling to develop the set of RCPs, which can be used to accurately represent the shoreline hydrodynamics of a large variety of coral reef-lined coasts around the globe. In two stages, the data were reduced by clustering cross-shore profiles based on morphology and hydrodynamic ...

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Core descriptions and sand bed thickness data from Kahana Valley, O'ahu, Hawai'i

This portion of the data release contains information on cores that were collected by the U.S. Geological Survey in Kahana Valley, O'ahu, Hawaii in 2015 and 2017. Sites were cored in order to describe wetland stratigraphy and to identify potential tsunami deposits. These cores contain mud, peat, fluvial sands, and marine carbonate sands, reflecting deposition in a variety of coastal environments. PDF files describe twenty-four (24) gouge and ‘Russian’ cores (hand held, side-filling peat augers) that ...

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Core descriptions and sedimentologic data from vibracores and sand augers collected in 2021 and 2022 from Fire Island, New York

In 2021 and 2022, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and the USGS New York Water Science Center (NYWSC), on behalf of SPCMSC, conducted sediment sampling and ground penetrating radar (GPR) surveys at Point O' Woods and Ho-Hum Beach (NYWSC, 2021) and Watch Hill, Long Cove, and Smith Point (SPCMSC, 2022), Fire Island, New York. These data complement previous SPCMSC GPR and sediment sampling surveys conducted at Fire Island in 2016 ...

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Core descriptions and sedimentologic data from vibracores collected in 2021 from Central Florida Gulf Coast Barrier Islands

In 2021, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) conducted ground penetrating radar (GPR) and sediment sampling surveys on barrier islands located along the central Florida Gulf Coast (CFGC), Pinellas County, Florida (FL). This study investigated the past evolution of the CFGC from field sites at Anclote Keys, Caladesi and Honeymoon Islands, and Fort DeSoto to quantify changes that occurred along these barrier systems prior to the 20th ...

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CoSMoS 3.2 Northern California sub-regional tier 2 FLOW-WAVE model input files

This data set consists of physics-based Delft3D-FLOW and WAVE hydrodynamic model input files used for Coastal Storm Modeling System (CoSMoS) sub-regional tier 2 simulations. Sub-regional tier 2 simulations cover portions of the Northern California open-coast region, from Point Arena to the California/Oregon state border, and they provide boundary conditions to higher-resolution simulations. Simulations are run for several storm events (covering a range of no storm, 1-year, 20-year, and 100-year coastal ...

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CoSMoS 3.2 Northern California sub-regional tier 3 2D XBeach model input files

This data set consists of 2D XBeach model input files used for Coastal Storm Modeling System (CoSMoS) sub-regional tier 3 simulations. Sub-regional tier 3 simulations cover portions of the Northern California open-coast region for Humboldt County and they provide final modeled hazard outputs going into projected hazard products. Simulations are run for several storm events (covering a range of no storm, 1-year, 20-year, and 100-year coastal storm conditions) and sea-level rise (SLR) scenarios.

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CoSMoS 3.2 Northern California Tier 1 FLOW-WAVE model input files

This data set consists of physics-based Delft3D-FLOW and WAVE hydrodynamic model input files used for Coastal Storm Modeling System (CoSMoS) Tier 1 simulations. Tier 1 simulations cover the Northern California open-coast region, from the Golden Gate Bridge to the California/Oregon state border, and they provide boundary conditions to higher-resolution simulations. Simulations are run for several storm events (covering a range of no storm, 1-year, 20-year, and 100-year coastal storm conditions) and sea-level ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in Monterey County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in San Francisco County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in San Luis Obispo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in San Mateo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in Santa Barbara County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 100-year storm in Santa Cruz County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in Monterey County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in San Francisco County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in San Luis Obispo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in San Mateo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in Santa Barbara County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 1-year storm in Santa Cruz County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in Monterey County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in San Francisco County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in San Luis Obispo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in San Mateo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in Santa Barbara County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: 20-year storm in Santa Cruz County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in Monterey County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in San Francisco County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in San Luis Obispo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in San Mateo County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in Santa Barbara County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood depth and duration projections: average conditions in Santa Cruz County

This data contains maximum depth of flooding (cm) in the region landward of the present-day shoreline for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood hazard projections: 100-year storm in Monterey County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 100-year storm in San Francisco County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 100-year storm in San Luis Obispo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 100-year storm in San Mateo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 100-year storm in Santa Barbara County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 100-year storm in Santa Cruz County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood hazard projections: 1-year storm in Monterey County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 1-year storm in San Francisco County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 1-year storm in San Luis Obispo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 1-year storm in San Mateo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 1-year storm in Santa Barbara County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 1-year storm in Santa Cruz County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood hazard projections: 20-year storm in Monterey County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 20-year storm in San Francisco County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 20-year storm in San Luis Obispo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 20-year storm in San Mateo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 20-year storm in Santa Barbara County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: 20-year storm in Santa Cruz County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood hazard projections: average conditions in Monterey County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: average conditions in San Francisco County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: average conditions in San Luis Obispo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: average conditions in San Mateo County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: average conditions in Santa Barbara County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 flood-hazard projections: average conditions in Santa Cruz County

This data contains geographic extents of projected coastal flooding, low-lying vulnerable areas, and maximum/minimum flood potential (flood uncertainty) associated with the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in Monterey County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in San Francisco County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in San Luis Obispo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in San Mateo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in Santa Barbara County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 100-year storm in Santa Cruz County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in Monterey County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in San Francisco County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in San Luis Obispo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in San Mateo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in Santa Barbara County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 1-year storm in Santa Cruz County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in Monterey County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in San Francisco County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in San Luis Obispo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in San Mateo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in Santa Barbara County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: 20-year storm in Santa Cruz County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in Monterey County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in San Francisco County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in San Luis Obispo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in San Mateo County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in Santa Barbara County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 ocean-currents projections: average conditions in Santa Cruz County

This data contains maximum model-derived ocean currents (in meters per second) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in Monterey County

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in San Francisco County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in San Luis Obispo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in San Mateo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in Santa Barbara County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 100-year storm in Santa Cruz County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in Monterey County

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in San Francisco County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in San Luis Obispo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in San Mateo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in Santa Barbara County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 1-year storm in Santa Cruz County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in Monterey County

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in San Francisco County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in San Luis Obispo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in San Mateo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in Santa Barbara County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: 20-year storm in Santa Cruz County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in Monterey County

This data contains model-derived total water elevation (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in San Francisco County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in San Luis Obispo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in San Mateo County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in Santa Barbara County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 water-level projections: average conditions in Santa Cruz County

This data contains model-derived total water levels (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden Gate. Outputs ...

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CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in Monterey County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in San Francisco County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in San Luis Obispo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in San Mateo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in Santa Barbara County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 100-year storm in Santa Cruz County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in Monterey County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in San Francisco County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in San Luis Obispo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in San Mateo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in Santa Barbara County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 1-year storm in Santa Cruz County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in Monterey County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in San Francisco County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in San Luis Obispo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in San Mateo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in Santa Barbara County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: 20-year storm in Santa Cruz County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in Monterey County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in San Francisco County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in San Luis Obispo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in San Mateo County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in Santa Barbara County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

Info
CoSMoS (Coastal Storm Modeling System) Central California v3.1 wave-hazard projections: average conditions in Santa Cruz County

This data contains maximum model-derived significant wave height (in meters) for the sea-level rise (SLR) and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. Projections for CoSMoS v3.1 in Central California include flood-hazard information for the coast from Pt. Conception to the Golden ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 coastal squeeze projections

Projected coastal squeeze derived from CoSMoS Phase 2 shoreline change and cliff retreat projections. Projected coastal squeeze extents illustrate the available area between shoreline (mean high water; MHW) positions and man-made structures and barriers (referred to as non-erodible structures) or cliff-top retreat, as applicable, for a range of sea-level rise scenarios. The coastal squeeze polygons include results from the Coastal Storm Modeling System (CoSMoS) shoreline change (CoSMoS-COAST; Vitousek and ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in Los Angeles County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in Orange County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in Santa Barbara County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in the Channel Islands

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 100-year storm in Ventura County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in Los Angeles County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in Orange County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in Santa Barbara County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in the Channel Islands

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 1-year storm in Ventura County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in Los Angeles County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in Orange County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in Santa Barbara County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in the Channel Islands

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: 20-year storm in Ventura County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in Los Angeles County

Projected Hazard: Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in Orange County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in Santa Barbara County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in the Channel Islands

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard depth and duration projections: average conditions in Ventura County

Maximum depth of flooding surface (in cm) in the region landward of the present day shoreline that is inundated for the storm condition and sea-level rise (SLR) scenario indicated. Note: Duration datasets may have occasional gaps in open-coast sections. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in Los Angeles County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in Orange County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in Santa Barbara County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in the Channel Islands

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 100-year storm in Ventura County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in Los Angeles County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in Orange County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in Santa Barbara County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in the Channel Islands

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 1-year storm in Ventura County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in Los Angeles County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in Orange County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in Santa Barbara County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in the Channel Islands

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: 20-year storm in Ventura County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in Los Angeles County

Projected Hazard: Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in Orange County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in Santa Barbara County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in the Channel Islands

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 flood-hazard projections: average conditions in Ventura County

Geographic extent of projected coastal flooding, low-lying vulnerable areas, and maxium/minimum flood potential (flood uncertainty) associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in Los Angeles County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in Orange County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in Santa Barbara County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in the Channel Islands

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 100-year storm in Ventura County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in Los Angeles County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in Orange County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in Santa Barbara County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in the Channel Islands

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 1-year storm in Ventura County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in Los Angeles County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in Orange County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in Santa Barbara County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in the Channel Islands

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: 20-year storm in Ventura County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in Los Angeles County

Projected Hazard: Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in Orange County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

Info
CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in Santa Barbara County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in the Channel Islands

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 ocean-currents projections: average conditions in Ventura County

Model-derived ocean current velocities (in meters per second) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 runup projections

Geographic extent of projected runup associated with the sea-level rise and storm condition indicated. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal planners with ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in Los Angeles County

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in Orange County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in Santa Barbara County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in the Channel Islands

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 100-year storm in Ventura County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in Los Angeles County

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in Orange County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in Santa Barbara County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in the Channel Islands

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 1-year storm in Ventura County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in Los Angeles County

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in Orange County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in Santa Barbara County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in the Channel Islands

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: 20-year storm in Ventura County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in Los Angeles County

Projected Hazard: Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in Orange County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in Santa Barbara County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in the Channel Islands

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 water-level projections: average conditions in Ventura County

Model-derived total water levels (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in Channel Islands

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in Los Angeles County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in Orange County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in Santa Barbara County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 100-year storm in Ventura County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in Channel Islands

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in Los Angeles County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in Orange County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in Santa Barbara County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 1-year storm in Ventura County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in Channel Islands

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in Los Angeles County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in Orange County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in Santa Barbara County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: 20-year storm in Ventura County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in Channel Islands

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in Los Angeles County

Projected Hazard: Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. Model Summary: The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in Orange County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in Santa Barbara County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 wave-hazard projections: average conditions in Ventura County

Model-derived significant wave height (in meters) for the given storm condition and sea-level rise (SLR) scenario. The Coastal Storm Modeling System (CoSMoS) makes detailed predictions (meter-scale) over large geographic scales (100s of kilometers) of storm-induced coastal flooding and erosion for both current and future sea-level rise (SLR) scenarios. CoSMoS v3.0 for Southern California shows projections for future climate scenarios (sea-level rise and storms) to provide emergency responders and coastal ...

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CoSMoS Southern California v3.0 Phase 2 projections of coastal cliff retreat due to 21st century sea-level rise

This dataset contains projections of coastal cliff-retreat rates and positions for future scenarios of sea-level rise (SLR). Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical and statistical models based on field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power, as part of Coastal Storm Modeling System (CoSMoS) v.3.0 Phase 2 in Southern California. Details: Cliff ...

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CoSMoS Southern California v3.0 projections of shoreline change due to 21st century sea-level rise

This dataset contains projections of shoreline positions and uncertainty bands for future scenarios of sea-level rise. Projections were made using CoSMoS-COAST, a numerical model forced with global-to-local nested wave models and assimilated with lidar-derived shoreline vectors. Details: Projections of shoreline position in Southern California are made for scenarios of 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0, and 5.0 meters of sea-level rise by the year 2100. Four datasets are available for different ...

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CoSMoS Whatcom County model input files

This data set consists of physics-based XBeach and SFINCS hydrodynamic model input files used for Coastal Storm Modeling System (CoSMoS) Tier 3 simulations. This data release is for Whatcom County in Washington State and presents the final tier 3 models used to produce output data that is then post-processed into final CoSMoS products. Example model input and configuration files are included for a single domain and SLR scenario, with the full modelling framework iterating on this process to simulate ...

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Current profiler time-series data collected in 2009 offshore of Wainwright, Alaska

A time-series of binned current-velocities and recorded ping amplitudes were collected offshore Wainwright, Alaska, from August 24 to October 02, 2009 (UTC). Measurements were collected using a 1 MHz NortekTM AWAC acoustic Doppler current profiler mounted on a frame in approximately 10 m of water. The profiler was mounted on the frame 0.55 m off the bottom of the seafloor, and collected data in 8 vertical bins, centered at 1.95(bin1), 2.95, 3.95, 4.95, 5.95, 6.95, 7.95, and 8.95(bin8) meters above the ...

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Digital elevation models (DEMs) of northern Monterey Bay, California, March 2015

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in March 2015. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a ...

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Digital elevation models (DEMs) of northern Monterey Bay, California, March 2016

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in March 2016. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a ...

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Digital elevation models (DEMs) of northern Monterey Bay, California, March 2017

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in March 2017. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted at a ...

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Digital elevation models (DEMs) of northern Monterey Bay, California, September 2017

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in September 2017. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS receiver mounted ...

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Digital elevation models (DEMs) of northern Monterey Bay, California, September and October 2015

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in September and October 2015. Bathymetry data were collected using two personal watercraft (PWCs), each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using a GNSS ...

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Digital elevation models (DEMs) of northern Monterey Bay, California, September and October 2016

This part of the data release presents digital elevation models (DEMs) derived from bathymetry and topography data of northern Monterey Bay, California collected in September and October 2016. Bathymetry data were collected using a personal watercraft (PWC) and small boat, each equipped with single-beam echosounders and survey-grade global navigation satellite system (GNSS) receivers. Topography data were collected on foot with GNSS receivers mounted on backpacks and with an all-terrain vehicle (ATV) using ...

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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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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
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 ...

Info
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 ...

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
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
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

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
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
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
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
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
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
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

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
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
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
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
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
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 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 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
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
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
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 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
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
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 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
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
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 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 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 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 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 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
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
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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 ...

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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
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
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
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 ...

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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
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
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
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
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
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
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
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 ...

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Digital surface model (DSM) for the intertidal zone at Lone Tree Point, Kiket Bay, WA, 2019-06-05

This portion of the data release presents a digital surface model (DSM) and hillshade image of the intertidal zone at Lone Tree Point, Kiket Bay, WA. The DSM has a resolution of 4 centimeters per pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-05. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have ...

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Digital surface model (DSM) for the intertidal zone at West Whidbey Island, WA, 2019-06-04

This portion of the data release presents a digital surface model (DSM) and hillshade image of the intertidal zone at West Whidbey Island, WA. The DSM has a resolution of 4 centimeters per pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-04. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been ...

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Digital surface models (DSM) for the intertidal zone at Puget Creek and Dickman Mill Park, Tacoma, WA, 2019-06-03

This portion of the data release presents digital surface models (DSM) and hillshade images of the intertidal zones at Puget Creek and Dickman Mill Park, Tacoma, WA. The DSMs have a resolution of 2.5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-03. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and ...

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Digital surface models (DSMs) for the intertidal zone at Post Point, Bellingham Bay, WA, 2019-06-06

This portion of the data release presents digital surface models (DSMs) and hillshade images of the intertidal zone at Post Point, Bellingham Bay, WA. The DSMs were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-06. Unlike a digital elevation model (DEM), the DSMs represent the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been removed from the data. In addition, ...

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Digital surface models of the north coast of Barter Island, Alaska acquired on July 01 2014, September 07 2014, and July 05 2015 (GeoTIFF image)

Digital surface elevation models (DSMs) of the coastline of Barter Island, Alaska derived from aerial photographs collected on July 01 2014, September 07 2014, and July 05 2015. Aerial photographs and coincident elevation data were processed using Structure-from-Motion (SfM) photogrammetric techniques. These files are single-band, 32-bit floating point DSMs (digital surface models) that represent surface elevations of buildings, vegetation, and uncovered ground surfaces in meters with 23 cm ground sample ...

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Discharge measurements collected in the Stillaguamish River Delta, Port Susan, Washington, USA in March, April, and May 2014

Tidal water discharge within two breaches constructed in a former flood-control levee of a restored agricultural area in Port Susan, Washington, was measured repeatedly during several tidal cycles. Measurements were made on March 27, 2014, April 16, 2014, May 18, 2014, and May 29, 2014 at breach PSB1, and on May 29, 2014 at breach PSB2. These data were collected using a boat-mounted Teledyne RDI RiverRay 600 kHz acoustic Doppler current profiler (ADCP) or a Teledyne RDI StreamPro 2000 kHz ADCP, depending on ...

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Dynamically downscaled future wave projections from SWAN model results for the main Hawaiian Islands

Projected wave climate trends from WAVEWATCH3 model output were used as input for nearshore wave models (for example, SWAN) for the main Hawaiian Islands to derive data and statistical measures (mean and top 5 percent values) of wave height, wave period, and wave direction for the recent past (1996-2005) and future projections (2026-2045 and 2085-2100). Three-hourly global climate model (GCM) wind speed and wind direction output from four different GCMs provided by the Coupled Model Inter-Comparison Project ...

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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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Geomorphic habitat units derived from 2009 aerial imagery and elevation data for the Elwha River estuary, Washington

Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 11 September 2009 1 meter resolution NAIP aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (17 September 2009) for areas < MHHW and aerial lidar surveys (4-6 April 2009) for elevations > MHHW.

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Geomorphic habitat units derived from 2011 aerial imagery and elevation data for the Elwha River estuary, Washington

Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 03 September 2011* 0.3 meter resolution Microsoft/Digital Globe aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (25 August 2011) for areas < MHHW and aerial lidar surveys (13-15 April 2012) for elevations > MHHW. *Image date of 3-Sep-11 corrected in metadata. During product generation the imagery date was believed to be 8-25-2011, as reported by ...

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Geomorphic habitat units derived from 2012 aerial imagery and elevation data for the Elwha River estuary, Washington

Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 30 August 2012 0.15 meter resolution NPS Elwha PlaneCam aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (28 August 2012) for areas < MHHW and aerial lidar surveys (17 October 2012) for elevations > MHHW.

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Geomorphic habitat units derived from 2013 aerial imagery and elevation data for the Elwha River estuary, Washington

Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 26 August 2013 0.15 meter resolution NPS Elwha PlaneCam aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (16 September 2013) for areas < MHHW and aerial lidar surveys (17 October 2012) supplemented with NPS Elwha PlaneCam SfM photogrammetry data (19 September 2013) for elevations > MHHW.

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Geomorphic habitat units derived from 2014 aerial imagery and elevation data for the Elwha River estuary, Washington

Estuary geomorphic units delineated at a scale of 1:1500 using a combination of (a) 28 August 2014 0.15 meter resolution NPS Elwha PlaneCam aerial imagery; and (b) elevation-colored and hillshaded digital elevation models from USGS backpack/jetski topobathy surveys (5-8 September 2014) for areas < MHHW and aerial lidar surveys (7 November 2014) supplemented with NPS Elwha PlaneCam SfM photogrammetry data (30 September 2014) for elevations > MHHW.

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Ground control point locations for the UAS survey of the coral reef off Waiakane, Molokai, Hawaii, 24 June 2018

This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during an unoccupied aerial system (UAS) survey of the coral reef off Waiakane, Molokai, Hawaii, on 24 June 2018. Twenty temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of: nine submerged targets consisting of small (80 centimeter X 80 centimeter) ...

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Ground control point locations for UAS survey of the intertidal zone at Lone Tree Point, Kiket Bay, WA, 2019-06-05

This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during an unmanned aerial system (UAS) survey of the intertidal zone at Lone Tree Point, Kiket Bay, WA on 2019-06-05. Eighteen temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of small square tarps with black-and-white cross patterns ...

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Ground control point locations for UAS survey of the intertidal zone at Post Point, Bellingham Bay, WA, 2019-06-06

This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during an unmanned aerial system (UAS) survey of the intertidal zone at Post Point, Bellingham Bay, WA on 2019-06-06. Nineteen temporary ground control points (GCPs) were distributed throughout each survey area to establish survey control. The GCPs consisted of a combination of small square tarps with black-and-white cross patterns ...

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Ground control point locations for UAS survey of the intertidal zone at West Whidbey Island, WA, 2019-06-04

This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during an unmanned aerial system (UAS) survey of the intertidal zone at West Whidbey Island, WA on 2019-06-04. Twenty-five temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of small square tarps with black-and-white cross patterns and ...

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Ground control point locations for UAS survey of the intertidal zones at Puget Creek and Dickman Mill Park, Tacoma, WA, 2019-06-03

This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during an unmanned aerial system (UAS) survey of the intertidal zones at Puget Creek and Dickman Mill Park, Tacoma, WA, on 2019-06-03. Twelve temporary ground control points (GCPs) were distributed throughout each survey area to establish survey control. The GCPs consisted of a combination of small square tarps with black-and-white ...

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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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HyCReWW database: A hybrid coral reef wave and water level metamodel

We developed the HyCReWW metamodel to predict wave run-up under a wide range of coral reef morphometric and offshore forcing characteristics. Due to the complexity and high dimensionality of the problem, we assumed an idealized one-dimensional reef profile, characterized by seven primary parameters. XBeach Non-Hydrostatic was chosen to create the synthetic dataset and Radial Basis Functions implemented in Matlab were chosen for interpolation. Results demonstrate the applicability of the metamodel to obtain ...

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Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Locations of convergences in the maximum alongshore current

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

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Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Locations of decelerations in the direction of flow in the maximum alongshore current

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

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Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: peak wave period

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

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Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Ratio of the wave- and current-induced shear stress to the critical value for oil-tar balls and sediment mobilization over a tidal cycle

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Ratio of the wave- and current-induced shear stress to the critical value for oil-tar balls and sediment mobilization weighted by probability of wave scenario occurrence

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Ratio of wave- and current-induced shear stress to critical values for oil-sand ball and sediment mobilization

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Significant wave height

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Surf-zone integrated alongshore potential flux for oil-sand balls

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: Surf-zone integrated alongshore potential flux for oil-sand balls of varying sizes weighted by probability of wave scenario occurrence

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

Info
Hydrodynamic and Sediment Transport Model Application for OSAT3 Guidance: wave direction

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

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Hydrodynamic modeling of the mouth of the Columbia River, Oregon and Washington, 2013

A process-based numerical model of the mouth of the Columbia River (MCR) and estuary, Oregon and Washington, was applied to simulate hydrodynamic conditions for the time period of the Office of Naval Research-funded River and Inlets Dynamics (RIVET II) field experiment conducted between May 9 and June 15, 2013. The model application was constructed using Delft3D, an open-source software package used to solve the unsteady shallow water equations to simulate water motion due to tides, waves, wind, and ...

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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 ...

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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 ...

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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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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 ...

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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 ...

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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 ...

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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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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 ...

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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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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 ...

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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 ...

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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 ...

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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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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 ...

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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 ...

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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 ...

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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 ...

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Kwajalein Island, Marshall Islands, wave and water level data, 2013-2015

Time series data of water surface elevation and wave height were acquired at ten locations for 518 days (in three separate deployments) off the south coast of Kwajalein Island, Marshall Islands, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on the reefs were as follows: KWA13W1 and KWA13E1 – fore reef KWA13W2 and KWA13E2 – outer reef flat KWA13W1 and KWA13E1 – middle reef flat ...

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Lagrangian drifter data from the mouth of the Columbia River, Oregon and Washington, 2013

Lagrangian surface currents were measured using drifters equipped with global navigation satellite system (GNSS) receivers. A total of 8 drifter deployments were performed between May 25 and June 8, 2013. For each deployment, drifters were released within the MCR and their positions were recorded until the drifters were recovered. The average duration of the drifter deployments varied between 1.6 h and 17.2 h and the number of drifters released in a deployment ranged between 11 and 84. The initial positions ...

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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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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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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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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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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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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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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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
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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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 ...

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Mean high water (MHW) shorelines along the coast of California used to calculated shoreline change from 1998 to 2016

This dataset contains mean high water (MHW) shorelines for sandy beaches along the coast of California for the years 1998/2002, 2015, and 2016. The MHW elevation in each analysis region (Northern, Central, and Southern California) maintained consistency with that of the National Assessment of Shoreline Change. The operational MHW line was extracted from Light Detection and Ranging (LiDAR) digital elevation models (DEMs) using the ArcGIS smoothed contour method. The smoothed contour line was then quality ...

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Modeled effects of depth and semidiurnal temperature fluctuations on predictions of year that coral reef locations reach annual severe bleaching for various global climate model projections

Using global climate model projections of sea-surface temperature at coral reef sites, we modeled the effects of depth and exposure to semidiurnal temperature fluctuations to examine how these effects may alter the projected year of annual severe bleaching for coral reef sites globally. Here we present the first global maps of the effects these processes have on bleaching projections for three IPCC-AR5 emissions scenarios.

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Modeled nearshore wave parameters

This portion of the USGS data release contains simulated nearshore wave parameters derived from a stand-alone spectral wave model of the Columbia River littoral cell, Washington and Oregon. The model output includes significant wave heights, peak wave periods, mean wave directions, and water depths for a series of 221 shore normal transects that extended from the coastline to the -15 m NAVD88 elevation (about 16.5 m average water depth). Data are provided at the seaward extent of each transect as well as at ...

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Modeled surface waves from winds in South San Francisco Bay

A model application using the phase-averaged wave model SWAN was developed to simulate wind waves in South San Francisco Bay, California, between May 30, 2021, and May 19, 2022. This data release describes the development of the model application, provides input files suitable for running the model using Delft3D version 4.04.01, and includes output from the model simulations in netCDF format.

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Model input files for the lower Nooksack River and delta, western Washington State

This data set consists of physics-based Delft3D-Flexible Mesh hydrodynamic model input files that are used to simulate compound flood exposure of the lower Nooksack River and delta of western Washington State under existing and future conditions of anticipated climate and land-use change. The model enables assessment of the changing flood exposure associated with the cumulative impacts of expected sea-level rise, greater tidal inundation, more frequent storm surge effects, and higher winter stream floods ...

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Model parameter input files to compare effects of stream discharge scenarios on sediment deposition and concentrations around coral reefs off west Maui, Hawaii

This dataset consists of physics-based Delft3D model and Delwaq model input files used in modeling sediment deposition and concentrations around the coral reefs of west Maui, Hawaii. The Delft3D models were used to simulate waves and currents under small (SC1) and large (‘SC2’) wave conditions for current stream discharge (‘Alt1’) and stream discharge with watershed restoration (‘Alt3’). Delft3D model results were subsequently used as forcing conditions for Delwaq models to simulate sediment ...

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Model parameter input files to compare locations of coral reef restoration on different reef profiles to reduce coastal flooding

This dataset consists of physics-based XBeach Non-hydrostatic hydrodynamic models input files used to study how coral reef restoration affects waves and wave-driven water levels over coral reefs, and the resulting wave-driven runup on the adjacent shoreline. Coral reefs are effective natural coastal flood barriers that protect adjacent communities. Coral degradation compromises the coastal protection value of reefs while also reducing their other ecosystem services, making them a target for restoration. ...

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Model parameter input files to compare the influence of channels in fringing coral reefs on alongshore variations in wave-driven runup along the shoreline

An extensive set of physics-based XBeach Non-hydrostatic hydrodynamic model simulations (with input files here included) were used to evaluate the influence of shore-normal reef channels on flooding along fringing reef-lined coasts, specifically during extreme wave conditions when the risk for coastal flooding and the resulting impact to coastal communities is greatest. These input files accompany the modeling conducted for the following publication: Storlazzi, C.D., Rey, A.E., and van Dongeren, A.R., 2022, ...

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Model parameter input files to compare the influence of coral reef carbonate budgets on alongshore variations in wave-driven total water levels on Buck Island Reef National Monument

A set of physics-based XBeach Non-hydrostatic hydrodynamic model simulations (with input files here included) were used to evaluate how varying carbonate budgets, and thus coral reef accretion and degradation, affect alongshore variations in wave-driven water levels along the adjacent shoreline of Buck Island Reef National Monument (BUIS) for a number of sea-level rise scenarios, specifically during extreme wave conditions when the risk for coastal flooding and the resulting impact to coastal communities is ...

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Model parameter input files to compare wave-averaged versus wave-resolving XBeach coastal flooding models for coral reef-lined coasts

This data release includes the XBeach input data files used to evaluate the importance of explicitly modeling sea-swell waves for runup. This was examined using a 2D XBeach short wave-averaged (surfbeat, XB-SB) and a wave-resolving (non-hydrostatic, XB-NH) model of Roi-Namur Island on Kwajalein Atoll in the Republic of Marshall Islands. Results show that explicitly modelling the sea-swell component (using XB-NH) provides a better approximation of the observed runup than XB-SB (which only models the time ...

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Model parameter input files to study three-dimensional flow over coral reef spur-and-groove morphology

This data set consists of physics-based Delft3D-FLOW and SWAN hydrodynamic models input files used to study the wave-induced 3D flow over spur-and-groove (SAG) formations. SAG are a common and impressive characteristic of coral reefs. They are composed of a series of submerged shore-normal coral ridges (spurs) separated by shore-normal patches of sediment (grooves) on the fore reef of coral reef environments. Although their existence and geometrical properties are well documented, the literature concerning ...

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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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Nearshore parametric wave setup future projections (2020-2050) for the North and South Carolina coasts

This dataset presents alongshore wave setup timeseries for the North and South Carolina coastlines. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to cross-shore transects spaced at ...

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Nearshore parametric wave setup future projections (2020-2050) for the U.S. Atlantic coast

This dataset presents alongshore wave setup timeseries for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to ...

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Nearshore parametric wave setup hindcast data (1979-2019) for the North and South Carolina coasts

This dataset presents alongshore wave setup timeseries for the North and South Carolina coastlines. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to cross-shore transects spaced at ...

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Nearshore parametric wave setup hindcast data (1979-2019) for the U.S. Atlantic coast

This dataset presents alongshore wave setup timeseries for three states (Virginia, Georgia, and Florida) along the U.S. Atlantic coast. Wave setup was modelled using parameterization for open coast sandy beaches as presented in Stockdon and others (2006). The parameterization relates onshore wave setup to offshore wave conditions and beach characteristics. Wave conditions were extracted at approximately the 10 m depth contour and reverse shoaled to the deep-water condition. These data were then matched to ...

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Nearshore total water level (TWL) proxies (2018-2100) for Northern California

Nearshore proxies for total water level (TWL) developed for Coastal Storm Model (CoSMoS) work in Northern California 3.2 are presented. Deterministic dynamical modeling of future climate conditions and associated hazards, such as flooding, can be computationally-expensive if century-long time-series of waves, sea level variations, and overland flow patterns are simulated. To focus such modeling on storm events of interest, local impacts over long time periods and large geographical areas are estimated. ...

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Nearshore waves in southern California: hindcast, and modeled historical and 21st-century projected time series

Abstract: This data release presents modeled time series of nearshore waves along the southern California coast, from Point Conception to the Mexican border, hindcasted for 1980-2010 and projected using global climate model forcing for 1975-2005 and 2012-2100. Details: As part of the Coastal Storm Modeling System (CoSMoS), time series of hindcast, historical, and 21st-century nearshore wave parameters (wave height, period, and direction) were simulated for the southern California coast from Point Conception ...

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Near-surface wind fields for San Francisco Bay--historical and 21st century projected time series

To support Coastal Storm Modeling System (CoSMoS) in the San Francisco Bay (v2.1), time series of historical and 21st-century near-surface wind fields (eastward and northward wind arrays) were simulated throughout the Bay. While global climate models (GCMs) provide useful projections of near-surface wind vectors into the 21st century, resolution is not sufficient enough for use in regional wave modeling projects, such as CoSMoS. Short-duration high wind speeds, on the order of hours, are of key ...

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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 ...

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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 ...

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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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Northern California 3.2 projections of coastal cliff retreat due to 21st century sea-level

This dataset contains projections of coastal cliff retreat and associated uncertainty across Northern California for future scenarios of sea-level rise (SLR) to include 25, 50, 75, 100, 125, 150, 175, 200, 250, 300, and 500 centimeters (cm) of SLR by the year 2100 and cover coastline from the Golden Gate Bridge to the California-Oregon state border. Present-day cliff-edge positions used as the baseline for projections are also included. Projections were made using numerical models and field observations ...

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Northern California cross-shore transects for CoSMoS 3.2

Cross-shore transects (CSTs) developed for Coastal Storm Model (CoSMoS) work in Northern California 3.2 are presented. 3,528 CSTs are numbered consecutively from 8067 at Golden Gate Bridge to 11,594 at the California/Oregon state border. Each of the profiles extend from the approximate -15 m isobath to at least 10 m above NAVD88 (truncated in cases where a lagoon or other waterway exists on the landward end of the profile), and are spaced approximately 100-250 m apart.

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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 ...

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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 ...

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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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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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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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 ...

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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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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 ...

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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 ...

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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 ...

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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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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 ...

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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 ...

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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 ...

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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 ...

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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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Oceanographic time-series measurements from the mouth of the Columbia River, Oregon and Washington, 2013

Time-series data of water surface elevation, wave height, and water column currents, temperature, salinity, and acoustic seabed images were acquired for 38 days between 9 May and 15 June, 2013 in the mouth of the Columbia River, Oregon and Washington.

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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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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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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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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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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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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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 ...

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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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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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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
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 ...

Info
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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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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Orthomosaic imagery for the intertidal zone at Lone Tree Point, Kiket Bay, WA, 2019-06-05

This portion of the data release presents a high-resolution orthomosaic image of the intertidal zone at Lone Tree Point, Kiket Bay, WA. The orthomosaic has a resolution of 2 centimeters per pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-05. The raw imagery used to create the orthomosaic was acquired using a UAS fitted with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed ...

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Orthomosaic imagery for the intertidal zone at Post Point, Bellingham Bay, WA, 2019-06-06

This portion of the data release presents a high-resolution orthomosaic images of the intertidal zone at Post Point, Bellingham Bay, WA. The orthomosaics were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-06. The orthomosaics are presented with two resolutions: one image, covering the entire survey area, has a resolution of 2 centimeters per pixel; the other image which was derived from a lower-altitude flight, covers an inset ...

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Orthomosaic imagery for the intertidal zone at Puget Creek and Dickman Mill Park, Tacoma, WA, 2019-06-03

This portion of the data release presents a high-resolution orthomosaic images of the intertidal zones at Puget Creek and Dickman Mill Park, Tacoma, WA. The orthomosaics have a resolution of 1.3 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-03. The raw imagery used to create the orthomosaics was acquired using a UAS fitted with a Ricoh GR II digital camera featuring a global shutter. The UAS was ...

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Orthomosaic imagery for the intertidal zone at West Whidbey Island, WA, 2019-06-04

This portion of the data release presents a high-resolution orthomosaic image of the intertidal zone at West Whidbey Island, WA. The orthomosaic has a resolution of 2 centimeters per pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-04. The raw imagery used to create the orthomosaic was acquired using a UAS fitted with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed ...

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Orthomosaic imagery from the UAS survey of the coral reef off Waiakane, Molokai, Hawaii, 24 June 2018

This portion of the data release presents a high-resolution orthomosaic image of the coral reef off Waiakane, Molokai, Hawaii. The orthomosaic has a resolution of 2.5 centimeters (cm) per pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unoccupied aerial system (UAS) on 24 June 2018. The raw imagery used to create the orthomosaic was acquired using a UAS fitted with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre ...

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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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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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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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Physics-based numerical circulation model outputs of ocean surface circulation during the 2010-2013 summer coral-spawning seasons in Maui Nui, Hawaii, USA

Ocean surface current results from a physics-based, 3-dimensional coupled ocean-atmosphere numerical model were generated to understand coral larval dispersal patterns in Maui Nui, Hawaii, USA. The model was used to simulate coral larval dispersal patterns from a number of existing State-managed reefs and large tracks of reefs with high coral coverage that might be good candidates for marine-protected areas (MPAs) during 8 spawning events during 2010-2013. The goal of this effort is to provide geophysical ...

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Physics-based numerical model simulations of wave propagation over and around theoretical atoll and island morphologies for sea-level rise scenarios

Schematic atoll models with varying theoretical morphologies were used to evaluate the relative control of individual morphological parameters on alongshore transport gradients. Here we present physics-based numerical SWAN model results of incident wave transformations for a range of atoll and island morphologies and sea-level rise scenarios. Model results are presented in NetCDF format, accompanied by a README text file that lists the parameters used in each model run. These data accompany the following ...

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Polycyclic aromatic hydrocarbons (PAHs) in the San Lorenzo River, Santa Cruz, California, USA, from 2015 to 2016

Polycyclic aromatic hydrocarbons (PAHs) are reported for water samples collected from the San Lorenzo River water during the rainy seasons from 2015 to 2016. Samples were collected during 2-, 5- and close to 10 year flood events.

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Projected coastal flooding depths for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in American Samoa

This data release provides flood depth GeoTIFFs based on sea-level rise and wave-driven total water levels for the coast of the American Samoa’s most populated islands of Tutuila, Ofu-Olosega, and Tau. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated American Samoan Islands due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to ...

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Projected coastal flooding depths for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Hawaiian Islands (ver. 1.1, September 2024)

This data release provides flood depth GeoTIFFs based on sea-level rise and wave-driven total water levels for the coast of the most populated Hawaiian Islands of Oahu, Molokai, Kauai, Maui, and Big Island. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Hawaiian Islands due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves ...

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Projected coastal flooding depths for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Mariana Islands

This data release provides flood depth GeoTIFFs based on sea-level rise and wave-driven total water levels for the coast of the most populated Mariana Islands of Guam and Saipan. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Mariana Islands due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves and storm surge at 10-m2 ...

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Projected coastal flooding extents for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in American Samoa

This data release provides flooding extent polygons based on sea-level rise and wave-driven total water levels for the coast of American Samoa's most populated islands of Tutuila, Ofu-Olosega, and Tau. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves and storm surge at 10-m2 resolution ...

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Projected coastal flooding extents for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Hawaiian Islands

This data release provides flooding extent polygons based on sea-level rise and wave-driven total water levels for the coast of the most populated Hawaiian Islands of Oahu, Molokai, Kauai, Maui, and Big Island. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves and storm surge at 10-m2 ...

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Projected coastal flooding extents for 1-, 20-, and 100-year return interval storms and 0.00, +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Mariana Islands

This data release provides flooding extent polygons based on sea-level rise and wave-driven total water levels for the coast of the most populated Mariana Islands of Guam and Saipan. Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding due to climate change and sea-level rise. We followed risk-based valuation approaches to map flooding due to waves and storm surge at 10-m2 resolution along these islands' ...

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Projected coastal flooding inundation depths for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in American Samoa

This data release provides flood depth GeoTIFFs based on sea-level rise (SLR) for the coast of the most populated American Samoa s most populated islands of Tutuila, Ofu-Olosega, and Ta'u. Digital elevation models were used to extract SLR flooded areas at 10-m2 resolution along the coastlines for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m SLR scenarios.

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Projected coastal flooding inundation depths for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Hawaiian Islands

This data release provides flood depth GeoTIFFs based on potential future sea-level rise (SLR)for the coast of the most populated Hawaiian Islands of O'ahu, Moloka'i, Kaua'i, Maui, and Big Island. Digital elevation models were used to extract SLR flooded areas at 10-m2 resolution along the coastlines for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m SLR scenarios.

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Projected coastal flooding inundation depths for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Mariana Islands

This data release provides flood depth GeoTIFFs based on sea-level rise for the coast of the most populated Mariana Islands of Guam and Saipan. Digital elevation models were used to extract sea-level rise flooded areas at 10-m2 resolution along the coastlines for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios.

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Projected flood water depths on Roi-Namur, Kwajalein Atoll, Republic of the Marshall Islands

Projected future wave-driven flooding depths on Roi-Namur Island on Kwajalein Atoll in the Republic of the Marshall Islands for a range of climate-change scenarios. This study utilized field data to calibrate oceanographic and hydrogeologic models, which were then used with climate-change and sea-level rise projections to explore the effects of sea-level rise and wave-driven flooding on atoll islands and their freshwater resources. The overall objective of this effort, due to the large uncertainty in ...

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Projected sea-level rise flooding inundation extents for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter in the Mariana Islands

This data release provides flooding extent polygons based on potential future sea-level rise (SLR) rise water levels for the coast of the most populated Mariana Islands of Guam and Saipan. Digital elevation models were used to predict SLR flooding extents for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m SLR rise scenarios.

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Projected sea-level rise flooding inundation extents for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in American Samoa

This data release provides flooding extent polygons based on sea-level rise (SLR) water levels for the coast of American Samoa's most populated islands of Tutuila, Ofu-Olosega, and Ta'u. Digital elevation models were used to predict SLR flooding extents for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m SLR scenarios.

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Projected sea-level rise flooding inundation extents for +0.25, +0.50, +1.00, +1.50, +2.00, and +3.00 meter sea-level rise scenarios in the Hawaiian Islands

This data release provides flooding extent polygons based on potential future sea-level rise (SLR) water levels for the coast of the most populated Hawaiian Islands of O'ahu, Moloka'i, Kaua'i, Maui, and Big Island. Digital elevation models were used to extract SLR flooded areas along the coastlines at 10-m2 resolution and converted to polygon shapefiles of the extents for +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m SLR scenarios.

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Projections of coastal flood depths for the U.S. Atlantic coast

Projected depths from compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for the U.S. Atlantic coast for three states (Florida, Georgia, and Virginia). Projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a tropical cyclone database from U.S. Army Corp of Engineers. The resulting data are depths of projected flood hazards along the U.S. Atlantic ...

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Projections of coastal flood depths for Whatcom County, Northwest Washington State coast (2015-2100)

Projected flood depths associated with compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are provided for Whatcom County, Washington, in a series of raster geotiff files. Projections were made using a system of numerical models with atmospheric forcing, tides, sea level position and stream discharge driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting computed coastal flood depths along the Whatcom ...

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Projections of coastal flood durations for Whatcom County, Northwest Washington State coast (2015-2100)

Projected flood duration associated with compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are provided for Whatcom County, Washington, in a series of raster geotiff files. Projections were made using a system of numerical models with atmospheric forcing, tides, sea level position and stream discharge driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting computed coastal flood duration along the ...

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Projections of coastal flood extents for Whatcom County, Northwest Washington State coast (2015-2100)

Projected flood extents associated with compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are provided for Whatcom County, Washington, in a series of shapefile files. Projections were made using a system of numerical models with atmospheric forcing, tides, sea level position and stream discharge driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting computed coastal flood extents along the Whatcom ...

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Projections of coastal flood hazards and flood potential for North Carolina and South Carolina

Projected impacts by compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for North Carolina and South Carolina. Accompanying uncertainty for each SLR and storm scenario, indicating total uncertainty from model processes and contributing datasets, are illustrated in maximum and minimum flood potential. As described by Nederhoff and others (2024), projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the ...

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Projections of coastal flood hazards and flood potential for the U.S. Atlantic coast

Projected impacts by compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for the U.S. Atlantic coast for three states (Florida, Georgia, and southern Virginia). Accompanying uncertainty for each SLR and storm scenario, indicating total uncertainty from model processes and contributing datasets, are illustrated in maximum and minimum flood potential. As described by Nederhoff and others (2024), projections were made using a system of numerical models driven by output ...

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Projections of coastal flood velocities for Whatcom County, Northwest Washington State coast (2015-2100)

Projected flood velocities associated with compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are provided for Whatcom County, Washington, in a series of raster geotiff files. Projections were made using a system of numerical models with atmospheric forcing, tides, sea level position and stream discharge driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting computed coastal flood velocities along the ...

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Projections of coastal flood water levels for Whatcom County, Northwest Washington State coast (2015-2100)

Projected flood levels associated with compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are provided for Whatcom County, Washington, in a series of raster geotiff files. Projections were made using a system of numerical models with atmospheric forcing, tides, sea level position and stream discharge driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting computed coastal flood levels along the Whatcom ...

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Projections of coastal water depths for North Carolina and South Carolina

Projected water depths from compound coastal flood hazards for future sea-level rise (SLR) and storm scenarios are shown for North Carolina and South Carolina. As described by Nederhoff and others (2024), projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and a tropical cyclone database from U.S. Army Corp of Engineers. The resulting data are depths of projected flood hazards along the ...

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Projections of compound floodwater depths for the lower Nooksack River and delta, western Washington State

Computed flood depths associated with the combined influence of sea level position, tides, storm surge, and streamflow under existing conditions and projected future higher sea level and peak stream runoff are provided for the lower (Reach 1) of the Nooksack River and delta in Whatcom County, western Washington State. The flood-depth projection data are provided in a series of raster geotiff files. Flood-depth projections were computed using a system of numerical models that accounted for projected changes ...

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Projections of shoreline change for California due to 21st century sea-level rise

This dataset contains projections of shoreline change and uncertainty bands across California for future scenarios of sea-level rise (SLR). Projections were made using the Coastal Storm Modeling System - Coastal One-line Assimilated Simulation Tool (CoSMoS-COAST), a numerical model run in an ensemble forced with global-to-local nested wave models and assimilated with satellite-derived shoreline (SDS) observations across the state. Scenarios include 25, 50, 75, 100, 125, 150, 175, 200, 250, 300 and 500 ...

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Projections of shoreline change of current and future (2005-2100) sea-level rise scenarios for North Carolina and South Carolina

This dataset contains projections of shoreline change and uncertainty bands for future scenarios of sea-level rise (SLR). Scenarios include 25, 50, 75, 100, 150, 200, and 300 centimeters (cm) of SLR by the year 2100. Output for SLR of 0 cm is also included, reflective of conditions in 2005, in accordance with recent SLR projections and guidance from the National Oceanic and Atmospheric Administration (NOAA; see process steps). Projections were made using the Coastal Storm Modeling System - Coastal One-line ...

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Projections of shoreline change of current and future (2005-2100) sea-level rise scenarios for the U.S. Atlantic Coast

This dataset contains projections of shoreline change and uncertainty bands for future scenarios of sea-level rise (SLR). Scenarios include 25, 50, 75, 100, 150, 200, and 300 centimeters (cm) of SLR by the year 2100. Output for SLR of 0 cm is also included, reflective of conditions in 2005, in accordance with recent SLR projections and guidance from the National Oceanic and Atmospheric Administration (NOAA; see process steps).Projections were made using the Coastal Storm Modeling System - Coastal One-line ...

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Projections of wave heights for Whatcom County, Northwest Washington State coast (2015-2100)

Projected wave heights associated with compound coastal flood hazards for existing and future sea-level rise (SLR) and storm scenarios are shown for Whatcom County, Washington, in a series of raster geotiff files. Projections were made using a system of numerical models driven by output from Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The resulting data are water levels of projected flood hazards along the Whatcom County coast due to sea level rise and ...

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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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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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Refraction-corrected bathymetric digital surface model (DSM) from the UAS survey of the coral reef off Waiakane, Molokai, Hawaii, 24 June 2018

This portion of the data release presents a bathymetric digital surface model (DSM) from an unoccupied aerial system (UAS) survey of the coral reef off Waiakane, Molokai, Hawaii, on 24 June 2018. The DSM has a horizontal resolution of 10 centimeters per pixel and has been corrected for the effects of refraction using the techniques described in Dietrich (2017a). The DSM was created from structure-from-motion (SfM) processing of aerial imagery collected using a UAS with a Ricoh GR II digital camera fitted ...

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Refraction-corrected bathymetric point cloud from the UAS survey of the coral reef off Waiakane, Molokai, Hawaii, 24 June 2018

This portion of the data release presents a bathymetric point cloud from an unoccupied aerial system (UAS) survey of the coral reef off Waiakane, Molokai, Hawaii, on 24 June 2018. The point cloud has been corrected for the effects of refraction using the techniques described in Dietrich (2017a). The point cloud was created from structure-from-motion (SfM) processing of aerial imagery collected using a UAS with a Ricoh GR II digital camera fitted with a circular polarizing filter. During the survey, a ...

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Remote Sensing Coastal Change Simple Data Distribution Service

The Remote Sensing Coastal Change Simple Data Service provides timely and long-term access to emergency, provisional, and approved photogrammetric imagery, derivatives, and ancillary data through a web service via HyperText Transfer Protocol to a folder/file structure organized by data collection platform and survey (collection effort) with metadata sufficient to facilitate both human and machine access. Data are acquired, processed, and published using standardized workflows. Each data type added to the ...

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Rincon, Puerto Rico, wave and water level data, 2019

Time series data of wave height and water surface elevation were acquired for 147 days at eleven locations, in two cross-reef transects, off of the west coast of Rincon, Puerto Rico, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on the reef were as follows: PRI19N01 – offshore reef crest, north transect PRI19N02, PRI19N03 – offshore reef flat, north transect PRI19S03 – offshore reef flat, south ...

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Rincon, Puerto Rico, wave and water level data, 2020

Time series data of wave height and water surface elevation were acquired for 135 days at six locations off of the west coast of Rincon, Puerto Rico, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on the reef were as follows: PRI20N01 – offshore PRI20N02 and PRI20N03 – fore reef PRI20N35, PRI20N04 and PRI20N45 – reef flat

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Riparian vegetation abundance (percent cover) in the Elwha River estuary, Washington, in 2007 and 2014

This portion of the data release presents riparian plant species abundance (percent cover) data from plots sampled in the Elwha River estuary, Washington, in 2007 and 2014. In August 2007, we established 21 vegetation plots within the study area in a stratified random fashion, with three to five plots in five of the vegetation cover types denoted in the habitat classification maps: mixed riparian forest, willow-alder forest, riparian shrub, emergent marsh/marsh-shrub transition, and dunegrass. Each plot was ...

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Riparian vegetation species richness in the Elwha River estuary, Washington, in 2007 and 2014

This portion of the data release presents riparian plant species richness (number of unique taxa) data from plots sampled in the Elwha River estuary, Washington, in 2007 and 2014. In August 2007, we established 21 vegetation plots within the study area in a stratified random fashion, with three to five plots in five of the vegetation cover types denoted in the habitat classification maps: mixed riparian forest, willow-alder forest, riparian shrub, emergent marsh/marsh-shrub transition, and dunegrass. Each ...

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Roi-Namur Island, Marshall Islands, wave and water level data, 2013-2015

Time series data of water surface elevation and wave height were acquired at ten locations for 517 days (in three separate deployments) off the north coast of Roi-Namur Island, Kwajalein Atoll, Marshall Islands, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on the reefs were as follows: ROI13W1 and ROI13E1 – fore reef ROI13W2 and ROI13E2 – outer reef flat ROI13W1 and ROI13E1 – ...

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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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San Juan, Puerto Rico, wave and water level data, 2018-2019

Time series data of water surface elevation and wave height were acquired at ten locations for 153 days off San Juan, on the north coast of Puerto Rico, in support of a study on the transformation of surface waves and resulting water levels over the coral reefs. The relative placement of sensors on the reefs were as follows: PRI18E01, PRI18W01 – fore reef PRI18E02, PRI18W02 – reef crest PRI18E03, PRI18W03 – outer reef flat PRI18E04, PRI18W04 – middle reef flat PRI18E05, ...

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Satellite-derived shorelines for North Carolina and South Carolina (1984-2021)

This dataset contains shoreline positions derived from available Landsat satellite imagery for North Carolina and South Carolina for the time period of 1984 to 2021. Positions were determined using CoastSat (Vos and others, 2019a and 2019b), an open-source mapping toolbox, was used to classify coastal Landsat imagery and detect shorelines at the sub-pixel scale. To understand shoreline evolution in complex environments and operate long-term simulations illustrating potential shoreline positions in the next ...

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Satellite-derived shorelines for the U.S. Atlantic coast (1984-2021)

This dataset contains shoreline positions derived from available Landsat satellite imagery for five states (Delaware, Maryland, Viginia, Georgia, and Florida) along the U.S. Atlantic coast for the time period 1984 to 2021. An open-source toolbox, CoastSat (Vos and others, 2019a and 2019b), was used to classify coastal Landsat imagery and detect shorelines at the sub-pixel scale. Resulting shorelines are presented in KMZ format. Significant uncertainty is associated with the locations of shorelines in ...

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Satellite-derived shorelines for the U.S. Gulf Coast states of Texas, Louisiana, Mississippi, and Florida for the period 1984-2022, obtained using CoastSat

This dataset contains shoreline positions derived from available Landsat satellite imagery for four states (Texas, Louisiana, Mississippi, and Florida) along the U.S. Gulf coast for the time period 1984 to 2022. An open-source toolbox, CoastSat (Vos and others, 2019a and 2019b), was used to classify coastal Landsat imagery and detect shorelines at the sub-pixel scale. Resulting shorelines are presented in CSV format. Significant uncertainty is associated with the locations of shorelines in extremely dynamic ...

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Scenarios_Grid

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

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Seawater carbonate chemistry, Kahekili, west Maui

Time-series of seawater carbonate chemistry variables, including salinity, dissolved inorganic nutrients, pH, total alkalinity, and dissolved inorganic carbon from sites along Kahekili Beach Park, west Maui near submarine groundwater seeps and living coral reefs. Samples for seawater were collected by pumping bottom water from the seafloor using a peristaltic pump and collecting discrete water samples every 4-hrs over a 6-day period.

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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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Sedimentologic Data from Vibracores Collected in 2023 from St. Andrew Bay, Florida

In April 2023, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected 11 sediment vibracores within East Bay, St. Andrew Bay, Florida (FL). Sediment vibracore and lithology data in this data release provide assessments on the composition and age of sediments below the seafloor.

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Shoreline change data along the coast of California from 2015 to 2016

This dataset contains shoreline change measurements for sandy beaches along the coast of California over the 2015/2016 El Nino winter season. Mean high water (MHW) shorelines were extracted from Light Detection and Ranging (LiDAR) digital elevation models from the fall of 2015 and the spring of 2016 using the ArcGIS smoothed contour method. The MHW elevation in each analysis region (Northern, Central, and Southern California) maintained consistency with that of the National Assessment of Shoreline Change. ...

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Shoreline change rates along the coast of California from 1998 to 2016

This dataset contains California shoreline change rates derived from mean high water (MHW) shorelines from 1998 (in Central and Southern California) and 2002 (in Northern California) to 2016. The MHW elevation in each analysis region (Northern, Central, and Southern California) maintained consistency with that of the National Assessment of Shoreline Change. The operational MHW line was extracted from Light Detection and Ranging (LiDAR) digital elevation models (DEMs) using the ArcGIS smoothed contour method ...

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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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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 ...

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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 ...

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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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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 ...

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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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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 ...

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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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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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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 ...

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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 ...

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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 ...

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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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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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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Spectral wave model input files

A stand-alone wave model application was constructed using the spectral wave model SWAN within the Delft3D4 (version 4.04.01) modeling system to simulate nearshore wave dynamics along the coast of the Columbia River littoral cell, Washington and Oregon. Nearshore wave dynamics are solved at hourly intervals on a series of nested grids with resolutions varying between 750 m for the largest grid to about 80 m for the two detailed grids that cover the Grays Harbor and Columbia River inlets. The provided model ...

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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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Summary statistics for the central Beaufort Sea coast, Alaska

A nested spectral wave model (Simulating Waves WAves Nearshore [SWAN]; Booij and others, 1999) was deployed for the central Beaufort Sea coast of Alaska to simulate waves for the period from 1979 to 2019. Results in the form of spatial summary statistics, describing wave parameters, wind speed and sea-ice area cover for the intermediate grid (see Overview Image on main page of data release), are provided. Further information can be found in Nederhoff and others (2021).

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Suspended sediment concentration (SSC) in the San Lorenzo River, Santa Cruz, California, USA, from 2008 to 2019

Suspended-sediment concentrations are reported in mg/L for water samples collected from the San Lorenzo River during the rainy seasons from 2008 to 2019. Samples were collected during 2-, 5- and 10-year flood events.

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Terrestrial lidar data from northern Monterey Bay, California, March 2015

This part of the data release presents topography data from northern Monterey Bay, California collected in March 2015 with a terrestrial lidar scanner.

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Terrestrial lidar data from northern Monterey Bay, California, March 2016

This part of the data release presents topography data from northern Monterey Bay, California collected in March 2016 with a terrestrial lidar scanner.

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Terrestrial lidar data from northern Monterey Bay, California, March 2017

This part of the data release presents topography data from northern Monterey Bay, California collected in March 2017 with a terrestrial lidar scanner.

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Terrestrial lidar data from northern Monterey Bay, California, October 2016

This part of the data release presents topography data from northern Monterey Bay, California collected in October 2016 with a terrestrial lidar scanner.

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Terrestrial lidar data from northern Monterey Bay, California, September 2015

This part of the data release presents topography data from northern Monterey Bay, California collected in September 2015 with a terrestrial lidar scanner.

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Terrestrial lidar data from northern Monterey Bay, California, September 2017

This part of the data release presents topography data from northern Monterey Bay, California collected in September 2017 with a terrestrial lidar scanner.

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Tidal_Grid

The U.S. Geological Survey has developed a method for estimating the mobility and potential alongshore transport of heavier-than-water sand and oil agglomerates (tarballs or surface residual balls, SRBs). During the Deepwater Horizon spill, some oil that reached the surf zone of the northern Gulf of Mexico mixed with suspended sediment and sank to form sub-tidal mats. If not removed, these mats can break apart to form SRBs and subsequently re-oil the beach. A method was developed for estimating SRB ...

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Time series for the central Beaufort Sea coast, Alaska

Time series output from a spectral wave model (Simulating Waves WAves Nearshore [SWAN]; Booij and others 1999), implemented for the central Beaufort Sea coast of Alaska from 1979 to 2019, are provided. The variables include significant wave heights, mean wave periods, mean wave directions, wave steepness, and orbital velocities. Additionally, water depths, x (east-west) and y (north-south) components of the wind, and sea ice concentrations are provided. Further information can be found in Nederhoff and ...

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Topographic point cloud for the intertidal zone at Lone Tree Point, Kiket Bay, WA, 2019-06-05

This portion of the data release presents a topographic point cloud of the intertidal zone at Lone Tree Point, Kiket Bay, WA. The point cloud was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-05. The point cloud has 206,323,353 points with an average point density of 929 points per-square meter. The point cloud is tiled to reduce individual file sizes and is grouped within a zip file for downloading. Each point in the point ...

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Topographic point cloud for the intertidal zone at Post Point, Bellingham Bay, WA, 2019-06-06

This portion of the data release presents topographic point clouds of the intertidal zone at Post Point, Bellingham Bay, WA. The point clouds were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-06. Two point clouds are presented with different resolutions: one point cloud (PostPoint_2019-06-06_pointcloud.zip) covers the entire survey area and has 145,653,2221 points with an average point density of 1,057 points per-square meter ...

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Topographic point cloud for the intertidal zone at Puget Creek and Dickman Mill Park, Tacoma, WA, 2019-06-03

This portion of the data release presents topographic point clouds of the intertidal zone at Puget Creek and Dickman Mill Park, Tacoma, WA, derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-03. The point clouds for Puget Creek and Dickman Mill Park contain 74,565,548 and 122,791,637 points, respectively, at an approximate point spacing of 1 point every 2 centimeters. Each point contains an explicit horizontal and vertical ...

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Topographic point cloud for the intertidal zone at West Whidbey Island, WA, 2019-06-04

This portion of the data release presents a topographic point cloud of the intertidal zone at West Whidbey Island, WA. The point cloud was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unmanned aerial system (UAS) on 2019-06-04. The point cloud has 293,261,002 points with an average point density of 1,063 points per-square meter. The point cloud is tiled to reduce individual file sizes and is grouped within a zip file for downloading. Each point in the point cloud ...

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Tuvalu, South Pacific, wave and water level data, 2019

Time series data of wave height and water surface elevation were acquired for 100 days at three locations off of the island of Nanumanga, three locations off of the island of Nanumea, three locations off of the island of Nui, two locations off of the island of Nikulaelae, and two locations off of the island of Niulakita, in the island nation of Tuvalu, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on ...

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UAV-based methane data from Barter Island, Northern Alaska, September 2017

We present methane data from along the coast of Barter Island, Alaska, collected with an Unmanned Aerial System and an off-the-shelf, cost-effective methane sensor. The data were collected on September 3 and September 5, 2017, as part of a larger Arctic coastal erosion investigation study by the U.S. Geological Survey (USGS). The data contain latitude, longitude and CH4 (ppm), and are presented as tab-delimited text files that have been zipped into one file. In addition, we have included one file of ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 ...

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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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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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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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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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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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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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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 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 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 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 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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Vegetation habitat units derived from 2009 aerial imagery and field data for the Elwha River estuary, Washington

Estuary vegetation cover delineated from 11 September 2009 1-meter-resolution NAIP aerial imagery at a scale of 1:1500.

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Vegetation habitat units derived from 2011 aerial imagery and field data for the Elwha River estuary, Washington

Estuary vegetation cover delineated from 3 September 2011* 0.3-meter-resolution aerial imagery (Microsoft/Digital Globe) at a scale of 1:1500. *Image date of 3-Sep corrected in metadata. During product generation the imagery date was believed to be 8-25-2011, as reported by DigitalGlobe reseller.

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Vegetation habitat units derived from 2012 aerial imagery and field data for the Elwha River estuary, Washington

Estuary vegetation cover delineated from 30 August 2012 0.15-meter-resolution NPS Elwha PlaneCam aerial imagery at a scale of 1:1500.

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Vegetation habitat units derived from 2013 aerial imagery and field data for the Elwha River estuary, Washington

Estuary vegetation cover delineated from 26 August 2013 0.15-meter-resolution NPS Elwha PlaneCam aerial imagery at a scale of 1:1500.

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Vegetation habitat units derived from 2014 aerial imagery and field data for the Elwha River estuary, Washington

Estuary vegetation cover delineated from 28 August 2014 0.15-meter-resolution NPS Elwha PlaneCam aerial imagery at a scale of 1:1500.

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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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Vessel-mounted acoustic Doppler current profiler (ADCP) data from the mouth of the Columbia River, Oregon and Washington, 2013

Spatial surveys of water column currents were performed between June 14 and 16, 2013, in the mouth of the Columbia River, Oregon and Washington. These data were collected using an acoustic-doppler current profiler (ADCP).

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Vibracore photographs, computed tomography scans, and core-log descriptions from Anahola Valley, Kaua'i, Hawai'i

This portion of the data release contains information on vibracores that were collected by the U.S. Geological Survey in Anahola Valley, Kaua'i, Hawai'i in 2015. Sites were cored in order to identify potential tsunami deposits and describe wetland stratigraphy. These vibracores contain mud, peat, volcanic sands, and carbonate sands, reflecting deposition in a variety of coastal environments. PDF files describe eight (8) vibracores that were split, imaged by a line-scanner camera, scanned to generate ...

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Vibracore photographs, computed tomography scans, and core-log descriptions from Pololu Valley, Island of Hawaii

This portion of the data release contains information on vibracores that were collected by the U.S. Geological Survey in Pololu Valley, Island of Hawai'i in 2014. Five sites were cored in order to describe wetland stratigraphy and to identify potential tsunami deposits. These vibracores contain mud, peat, fluvial sands, and marine volcanic sands, reflecting deposition in a variety of coastal environments. Two (2) pdf files (VC1.pdf, VC2.pdf) describe vibracores that were split, imaged by a line-scanner ...

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Waiakane, Molokai, Hawaiian Islands, wave and water level data, 2018

Time series data of water surface elevation, wave height, and water column currents and temperature were acquired at seven locations for 86 days off of Waiakane on the south coast of the island of Molokai, Hawaii, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on the reef were as follows: MKK18C01 – offshore MKK18C02 and MKK18C09 – fore reef MKK18C18 – reef crest MKK18C20 – ...

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Water level and velocity measurements from the 2012 University of Western Australia Fringing Reef Experiment (UWAFRE)

This data release contains water level and velocity measurements from wave runup experiments performed in a laboratory flume setting. Wave-driven water level variability (and runup at the shoreline) is a significant cause of coastal flooding induced by storms. Wave runup is challenging to predict, particularly along tropical coral reef-fringed coastlines due to the steep bathymetric profiles and large bottom roughness generated by reef organisms. The 2012 University of Western Australia Fringing Reef ...

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Wave and wind projections along United States coasts

Coastal managers and ocean engineers rely heavily on projected average and extreme wave conditions for planning and design purposes, but when working on a local or regional scale, are faced with much uncertainty as changes in the global climate impart spatially varying trends. Future storm conditions are likely to evolve in a fashion that is unlike past conditions and is ultimately dependent on the complicated interaction between the Earth’s atmosphere and ocean systems. Despite a lack of available data ...

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Wave model grids and bathymetry for the central Beaufort Sea coast, Alaska

The required grid and bathymetry files to run a nested spectral wave model (Simulating Waves WAves Nearshore [SWAN]; Booij and others, 1999) for the central Beaufort Sea coast of Alaska are provided. A three-level SWAN nesting grid with grid resolutions of 5000 meters, 1000 meters, and 200 meters for the overall, intermediate and detail grids, respectively (see included Browse Graphic) has been developed. For this purpose, available local bathymetry (Coastal Frontiers Corporation, 2014; Kasper and others, ...

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Wave model input files

Provided here are the required input files to run a standalone wave model (Simulating Waves WAves Nearshore [SWAN]; Booij and others, 1999) on eleven model domains from the Canada-U.S. border to Norton Sound, Alaska to create a downscaled wave database (DWDB). The DWDB, in turn, can be used to reconstruct hindcast (1979-2019) and projected (2020-2050) time series at each point in the model domains see Engelstad and others, 2023 for further information on reconstruction of time-series. The model forcing ...

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Wave observations from bottom-mounted pressure sensors along the West side of Whidbey Island, Washington from Dec 2018 to Jan 2020

RBRduo pressure and temperature sensors mounted on aluminum frames, were moored in shallow (4-9 m) water depths along the West side of Whidbey Island, Washington, to measure wave heights and periods. Continuous pressure fluctuations were transformed into surface-wave observations of wave heights, periods, and frequency spectra at 30-minute intervals.

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Wave observations from bottom-mounted pressure sensors in Bellingham Bay, Washington from Dec 2017 to Jan 2018

RBRduo pressure and temperature sensors (early 2015 generation), mounted on aluminum frames, were moored in shallow (< 6 m) water depths in Bellingham Bay, Washington, to capture wave heights and periods. Continuous pressure fluctuations are transformed into surface-wave observations of wave heights, periods, and frequency spectra at 30-minute intervals.

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Wave observations from bottom-mounted pressure sensors in Skagit Bay, Washington from Dec 2017 to Feb 2018

RBRduo pressure and temperature sensors (early 2015 generation), mounted on aluminum frames, were moored in shallow (< 6 m) water depths in Skagit Bay to capture wave heights and periods. Continuous pressure fluctuations are transformed into surface-wave observations of wave heights, periods, and frequency spectra at 30-minute intervals.

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Wave time-series data collected in 2009 offshore of Wainwright, Alaska

Time series wave data were collected offshore of Wainwright, Alaska, from August 24 to October 02, 2009 (UTC). Measurements were collected using a 1 MHz NortekTM AWAC acoustic Doppler current profiler mounted on a frame in approximately 10 m of water. The instrument was mounted to the frame at 0.55 m off the bottom of the seafloor, and collected data in 8.53-minute bursts at 2 Hz. Significant wave heights (Hs), maximum significant wave heights (Hmax), peak and mean wave periods (Tp and Tm, respectively), ...

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Wave time-series: ERA5 hindcast period 1979-2019 - U.S. Canada border to Bering Strait

Modeled wave time series data are presented for the hindcast period of 1979 to 2019 from the U.S. Canada border to the Bering Strait close to the 5 and 10 m isobaths. Outputs include three-hourly nearshore significant wave heights (Hs), mean wave periods (Tm) and mean wave directions (Dm) for 6424 locations. Data are available as netCDF files and are packaged for the Beaufort Sea region from the U.S. Canada border to Nuvuk (Point Barrow), and for the Chukchi Sea region from Nuvuk to Kotzebue Sound and from ...

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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 ...

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West Maui, Hawaiian Islands, wave and water level data, 2017

Time series data of wave height and water surface elevation were acquired at ten locations for 75 days south of Lahaina, off of the west coast of the island of Maui, Hawaii, in support of a study on the coastal circulation patterns and the transformation of surface waves over the coral reefs. The relative placement of sensors on the reefs were as follows: MAU17TP1 and MAU17LA1 – middle fore reef MAU17TP2 and MAU17LA2 – upper fore reef MAU17TP3 and MAU17LA3 – outer reef flat ...

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