Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for developing approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the effects of sea-level rise on shoreline change, barrier island geomorphology, and habitat availability for species such as piping plover ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This portion of the data release presents a digital surface model (DSM) and digital elevation model (DEM) of the exposed Los Padres Reservoir delta where the Carmel River enters the reservoir. The DSM and DEM have a resolution of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unoccupied aerial system (UAS) on 2017-11-01. The DSM represents the elevation of the highest object within the bounds of a cell, including vegetation, woody ...

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 the unoccupied aerial system (UAS) survey of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01. Twenty temporary ground control points (GCPs) consisting of small square tarps with black-and-white cross patterns were distributed throughout the area to establish survey control. The GCP positions were measured ...

This portion of the data release presents the raw aerial imagery collected during the unoccupied aerial system (UAS) survey of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01. 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. A total of six flights were conducted for the ...

This portion of the data release presents a high-resolution orthomosaic image of the exposed Los Padres Reservoir delta where the Carmel River enters the reservoir. The orthomosaic has a resolution of 2.5 centimeters per pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unoccupied aerial system (UAS) on 2017-11-01. 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. ...

This portion of the data release presents a topographic point cloud of the exposed Los Padres Reservoir delta where the Carmel River enters the reservoir. The point cloud was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unoccupied aerial system (UAS) on 2017-11-01. The point cloud has 115,819,907 points with an average point density of 611 points per-square meter. Each point in the point cloud contains an explicit horizontal and vertical coordinate, color, ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This web mapping application is a compilation of geoscientific data collected and published by the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC). This application does not serve as a complete archive of all the geoscientific data collected by the center, but highlights frequently published data types. Data within this web application include: seismic data extents, seismic survey tracklines (boomer, chirp, and minisparker), bathymetric footprints, bathymetric ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

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, ...

Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. To re-establish a population at Assateague Island National Seashore (ASIS), seabeach amaranth cultivars were planted by ASIS natural resources staff for three growing seasons from 1999 to 2001 and have been monitored since 2001. Characteristics of favorable seabeach amaranth locations were assessed by sampling barrier island and habitat characteristics at sites ...

Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. To re-establish a population at Assateague Island National Seashore (ASIS), seabeach amaranth cultivars were planted by ASIS natural resources staff for three growing seasons from 1999 to 2001 and have been monitored since 2001. Characteristics of favorable seabeach amaranth locations were assessed by sampling barrier island and habitat characteristics at sites ...

Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. To re-establish a population at Assateague Island National Seashore (ASIS), seabeach amaranth cultivars were planted by ASIS natural resources staff for three growing seasons from 1999 to 2001 and have been monitored since 2001. Characteristics of favorable seabeach amaranth locations were assessed by sampling barrier island and habitat characteristics at sites ...

Digital elevation models (DEMs) were created from aerial imagery collected October 11, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions one-month after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface one-month post-Hurricane Dorian and were created to document inter-annual changes in ...

This portion of the data release presents digital surface models (DSM) of the Whale's Tail Marsh region of South San Francisco Bay, CA. The DSMs have resolutions of 5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of repeat aerial imagery collected from fixed-wing aircraft. Unlike a digital elevation model (DEM), a DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, structures, and other objects have not been removed from the data. ...

This portion of the data release presents orthomosaic images of the Whale's Tail Marsh region of South San Francisco Bay, CA. The orthomosaics have resolutions of 2.5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of repeat aerial imagery collected from fixed-wing aircraft. The raw imagery used to create these elevation models was acquired from an approximate altitude of 427 meters (1,400 feet) above ground level (AGL), using a Hasselblad A6D-100c camera fitted with an HC ...

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), ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

Using version 20.1_19 of the Discontinuous-Galerkin Shallow Water Equations Model (DG-SWEM) (Kubatko and others, 2006), astronomic tides and salinity transport were simulated at Grand Bay, Alabama (AL), under scenarios of interior headland restoration and sea level rise, as described in Passeri and others (2023). The two-dimensional DG-SWEM model can be applied to coastal and estuarine systems to solve for time-dependent hydrodynamic circulation and salinity transport. The DG-SWEM model uses the ADCIRC ...

To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a ...

To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve, Mississippi (GNDNERR). These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This portion of the data release presents digital surface models (DSM) of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with unoccupied aerial systems (UAS) during low tides on 7 and 8 August 2017. Unlike a digital elevation model (DEM), the DSMs represent the elevation of the highest object within the bounds ...

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 the August 2017 unoccupied aerial system (UAS) surveys of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. Eighteen temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of ...

This portion of the data release presents the raw aerial imagery collected during the uncrewed aerial system (UAS) survey conducted on the ocean beaches adjacent to the Columbia River Mouth at the Oregon-Washington border in August 2017. 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 ...

This portion of the data release presents topographic point clouds of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. The point clouds were derived from structure-from-motion (SfM) processing of aerial imagery collected with unoccupied aerial systems (UAS) on during low tide surveys on 7 and 8 August 2017. The point clouds from each survey are tiled into 1000 by 1000 meter tiles to reduce individual file sizes. The Fort Stevens point clouds have a ...

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 the July 2021 unoccupied aerial system (UAS) surveys of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. Eighteen temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of small ...

This portion of the data release presents the raw aerial imagery collected during the uncrewed aerial system (UAS) survey conducted on the ocean beaches adjacent to the Columbia River Mouth at the Oregon-Washington border in July 2021. 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 ...

This portion of the data release presents topographic point clouds of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. The point clouds were derived from structure-from-motion (SfM) processing of aerial imagery collected with unoccupied aerial systems (UAS) on 2017-11-01 during low tide surveys on 22 and 23 July 2021. The point clouds from each survey are tiled into 500 by 500 meter tiles to reduce individual file sizes. The Fort Stevens point clouds ...

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

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

These data map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA, providing updated regional context for the 2019 CoastCam installation. CoastCam CACO-01 are two video cameras aimed at the beach that view the coast shared by beachgoers, shorebirds, seals, and sharks. These data were collected as part of field activity 2021-014-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region. In February 2021, U.S. Geological Survey and ...

The data in this publication map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide regional context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. These data were collected as part of field activity 2021-022-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-02, which are two video cameras aimed at the ...

This portion of the data release presents a digital elevation model (DEM) of portions of Oxbow Reservoir in Placer County, California. The DEM was created using topographic survey data collected on 26 October 2022, when the reservoir was partially de-watered to allow repairs to the dam infrastructure following the Mosquito Fire. Although the gates of the dam were open during this time, significant portions of the reservoir site remained inaccessible to surveyors due to the continued flow of the Middle Fork ...

This portion of the data release presents topographic survey data of portions of Oxbow Reservoir in Placer County, California. These data were collected on 26 October 2022, when the reservoir was partially de-watered to allow repairs to the dam infrastructure following the Mosquito Fire. Although the gates of the dam were open during this time, significant portions of the reservoir site remained inaccessible to surveyors due to the continued flow of the Middle Fork American River. Consequently, these data ...

This portion of the data release presents high-resolution orthomosaic images of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. The orthomosaics have resolutions of 5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with unoccupied aerial systems (UAS) during low tide surveys on 7 and 8 August 2017. The raw imagery used to create the orthomosaics was acquired with a UAS fitted with a Ricoh ...

This portion of the data release presents digital surface models (DSM) of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with unoccupied aerial systems (UAS) during low tides on 22 and 23 July 2021. Unlike a digital elevation model (DEM), the DSMs represent the elevation of the highest object within the bounds ...

This portion of the data release presents high-resolution orthomosaic images of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. The orthomosaics have resolutions of 5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with unoccupied aerial systems (UAS) during low tide surveys on 22 and 23 July 2021. The raw imagery used to create the orthomosaics was acquired with a UAS fitted with a Ricoh ...

This portion of the data release presents a digital surface model (DSM) and hillshade of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2019-11-12. 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 removed from the data. In addition, data artifacts resulting from noise and vegetation in the original ...

This portion of the data release presents an RGB orthomosaic image of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2019-11-12. The orthomosaic is available in a high-resolution 6-centimeter (cm) version, as well as a medium-resolution 25 cm version. The high-resolution version is divided into two tiles (east and west) to reduce file download sizes. All imagery is provided in a three-band cloud optimized GeoTIFF format, with 8-bit ...

This portion of the data release presents an RGB orthomosaic image of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2020-11-10. The orthomosaic is available in a high-resolution 5-centimeter (cm) version, as well as a medium-resolution 25 cm version. The high-resolution version is divided into two tiles (east and west) to reduce file download sizes. All imagery is provided in a three-band cloud optimized GeoTIFF format, with 8-bit ...

RGB-averaged orthoimages were created from aerial imagery collected May 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RGB-averaged orthoimages were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RGB-averaged orthoimages help researchers document inter-annual changes in shoreline position and coastal morphology in ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Sand Key Beach in Clearwater, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate ...

A digital video camera was installed at Tres Palmas, Rincón, Puerto Rico (PR) and faced west along the beach. Every hour during daylight hours, daily from August 27, 2019, to March 10, 2020, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the red, green, ...

A digital video camera was installed at Isla Verde Beach in San Juan, Puerto Rico (PR) and faced northeast along the beach. Every hour during daylight hours, daily from February 1, 2019, to July 15, 2019, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the ...

A digital video camera was installed at Waiakāne, Moloka'i, Hawai'i (HI) and faced west along the beach. Every hour during daylight hours, daily from June 26, 2018, to September 20, 2018, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the red, green, and ...

A digital video camera was installed at Isla Verde, Puerto Rico (PR) and faced northeast along the beach. Every hour during daylight hours, daily from February 1, 2019, to July 15, 2019, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological Survey (USGS) research ...

This data release presents the post-processed Global Navigation Satellite System (GNSS) ground-survey data acquired during the installation of the Argus camera at Isla Verde, Puerto Rico. The data contains topographic survey data collected during the installation of the camera. Data were collected on foot by a person equipped with a GNSS antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ). The GNSS measurements were made using Post-Processed Kinematic (PPK) corrections ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches.Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (L=lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

A digital video camera was installed at Tres Palmas, Rincón, Puerto Rico (PR) and faced west to view the beach and water offshore. Every hour during daylight hours, daily from August 27, 2019 to March 10, 2020, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological ...

This data release serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery from Delaware Bay, New Jersey (NJ) to Shinnecock Bay, New York (NY). A total of 119 images acquired between 2008 and 2022 were analyzed to produce 143 thematic land-cover raster datasets. Water, bare earth (sand), and vegetated land-cover classes were mapped using successive thresholding and masking of the modified normalized difference water index (mNDWI), the normalized difference bare ...

This data release serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery from Delaware Bay, New Jersey (NJ) to Shinnecock Bay, New York (NY). A total of 119 images acquired between 2008 and 2022 were analyzed to produce 143 thematic land-cover raster datasets. Water, bare earth (sand), and vegetated land-cover classes were mapped using successive thresholding and masking of the modified normalized difference water index (mNDWI), the normalized difference bare ...

This data release presents the post-processed Global Navigation Satellite System (GNSS) ground-survey data acquired during the installation of a camera system at Tres Palmas, Rincón, Puerto Rico (PR). The data contains topographic survey data collected during the installation of the camera. Data were collected on foot, by a person equipped with a GNSS antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ). The GNSS measurements were made using Post-Processed Kinematic (PPK) ...

A morphologically diverse and dynamic group of barrier islands along the Central Florida (FL) Gulf Coast (CFGC) form a 75-kilometer-long chain stretching from Anclote Key in the north to Egmont Key in the south. In 2021, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) conducted ground penetrating radar (GPR) surveys on barrier islands located along the CFGC, in Pinellas County, FL. This study investigated the past evolution of the CFGC from field ...

A digital video camera was installed at Waiakāne, Moloka'i, Hawai'i (HI) and faced west along the beach. Every hour during daylight hours, daily from June 26, 2018, to September 20, 2018, the camera collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The camera is part of a U.S. Geological Survey (USGS) research ...

This data release presents the post-processed global navigation satellite system (GNSS) ground-survey data acquired during the installation of the Argus camera at Waiakāne, Moloka'i, Hawai'i. The data contains topographic survey data collected during the installation of the camera. Data were collected on foot by a person equipped with a GNSS antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ). The GNSS measurements were made using Post-Processed Kinematic (PPK) ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

Two digital video cameras were installed at Sand Key, Florida (FL), facing south (camera 1) and north (camera 2) along the beach. Every hour during daylight hours, the cameras collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements.. The cameras are part of a U.S. Geological Survey (USGS) research project to study the ...

Two digital video cameras were installed at Sand Key, Florida (FL), facing south (camera 1) and north (camera 2) along the beach. Every hour during daylight hours, the cameras collected raw video and produced snapshots and time-averaged image products. This data release includes the necessary intrinsic orientation (IO) and extrinsic orientation (EO) calibration data to utilize imagery to make quantitative measurements. The images included in this data release were collected by camera 2 (c2) from May 29, ...

A digital video camera was installed at Madeira Beach, Florida (FL) and faced west along the beach. Every hour during daylight hours, daily from 2017 to 2022, the camera collected raw video and produced snapshots and time-averaged image products. One such product is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup timestacks store the red, green, and blue or monochrome pixel ...

Two digital video cameras were installed at Sand Key, Florida (FL), facing south (camera 1) and north (camera 2) along the beach. Every hour during daylight hours, daily from 2018 to 2022, the cameras collected raw video and produced snapshots and time-averaged image products. For camera 2, one such product that is created is a "runup timestack". Runup timestacks are images created by sampling a cross-shore array of pixels from an image through time as waves propagate towards and run up a beach. Runup ...

The Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the Massachusetts coast. Seventy-six maps were produced in 1997 depicting a statistical analysis of shoreline change on ocean-facing shorelines from the mid-1800s to 1978 using multiple data sources. In 2001, a 1994 shoreline was added. More recently, in cooperation with CZM, the U.S. Geological Survey (USGS) delineated a new shoreline for Massachusetts using color ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreline locations from the mid-1800s to 1978 were produced from multiple data sources, and in 2001, a 1994 shoreline ...

This data release of dune metrics for the Massachusetts coast is part of a 2018 update to the Massachusetts Shoreline Change Project. Because of continued coastal population growth and the increased threat of coastal erosion, the Massachusetts Office of Coastal Zone Management (CZM) launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. Maps of historic shoreline locations from the mid-1800s to 1978 were produced from multiple data sources, and in 2001, a 1994 shoreline ...

Low-altitude (80-100 meters above ground level) Unmanned Aircraft Systems (UAS) imagery of Town Neck Beach in Sandwich, Massachusetts, were used in a structure-from-motion (SfM) photogrammetry workflow to create high-resolution topographic datasets. Imagery was collected at close to low tide on twelve days to observe changes in beach and dune morphology. Ground control points (GCPs), which are temporary targets on the ground located by using a real-time kinematic global navigation satellite system (RTK-GNSS ...

Low-altitude (80-100 meters above ground level) Unmanned Aircraft Systems (UAS) imagery of Town Neck Beach in Sandwich, Massachusetts, were used in a structure-from-motion (SfM) photogrammetry workflow to create high-resolution topographic datasets. Imagery was collected at close to low tide on twelve days to observe changes in beach and dune morphology. Ground control points (GCPs), which are temporary targets on the ground located by using a real-time kinematic global navigation satellite system (RTK-GNSS ...

This data release contains mean high water (MHW) shorelines for the Outer Cape of Cape Cod, Massachusetts, from Nauset Inlet to Race Point. From 1998-2005, the U.S. Geological Survey surveyed 45 kilometers of coastline 111 times using a ground-based system called Surveying Wide-Area Shorelines (SWASH). The SWASH system used a six-wheeled amphibious all-terrain vehicle as a platform for an array of Global Positioning System sensors. High-accuracy measurements of horizontal position, vertical position, and ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ...

Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ...

This portion of the data release presents high-resolution Digital Surface Models (DSM) of the Jenkinson Lake upper reservoir delta in El Dorado County, California. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected during surveys with unoccupied aerial systems (UAS). The surveys were on 2021-10-13, 2021-11-04, 2022-10-25, and 2023-11-13, and were generally timed to coincide with low water level in the reservoir to ...

This portion of the data release presents high-resolution orthomosaic images of the Jenkinson Lake upper reservoir delta in El Dorado County, California. The orthomosaics have resolutions of 2.5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected during surveys with unoccupied aerial systems (UAS). The surveys were on 2021-10-13, 2021-11-04, 2022-10-25, and 2023-11-13, and were generally timed to coincide with low water level in the reservoir to ...

The U.S. Geological Survey (USGS), in cooperation with the National Marine Sanctuary Program of the National Oceanic and Atmospheric Administration (NOAA), has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The interpretive datasets and source information presented here are for quadrangle 5, which is one of 18 similarly sized segments of the 3,700 square kilometer (km2) SBNMS region. The seabed of the SBNMS region is a glaciated ...

Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ...

Two digital video cameras were temporarily installed at the U.S. Fish and Wildlife Service (USFWS) Pea Island National Wildlife Refuge (PINWR) in North Carolina (NC), as part of the DUring Nearshore Event eXperiment (DUNEX). DUNEX was a collaborative community-led experiment that took place in the fall of 2021 along the Outer Banks of NC, with the goal of improving the understanding, observational techniques, and predictive capabilities for extreme storm processes and impacts within the coastal environment. ...

Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), in collaboration with the U.S. Army Corps of Engineers (USACE), conducted geophysical and sedimentological surveys around Cat Island, the westernmost island in the Mississippi-Alabama barrier island chain. The objectives of the study were to understand the geologic evolution of Cat Island relative to other barrier islands in the northern Gulf of Mexico and to identify relationships between the ...

Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), in collaboration with the U.S. Army Corps of Engineers (USACE), conducted geophysical and sedimentological surveys around Cat Island, the westernmost island in the Mississippi-Alabama barrier island chain. The objectives of the study were to understand the geologic evolution of Cat Island relative to other barrier islands in the northern Gulf of Mexico and to identify relationships between the ...

As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in March and September 2012. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier ...

As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in March and September 2012. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier ...

As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in March and September 2012. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier ...

As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in March and September 2012. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier ...

As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in July 2013. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to understand better the depositional and erosional processes that drive the morphologic evolution of barrier islands over ...

As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in July 2013. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier islands over ...

A digital elevation model (DEM) mosaic was produced for Assateague Island, Maryland and Virginia, post-Hurricane Joaquin, from remotely sensed, geographically referenced elevation measurements collected by Quantum Spatial using a Leica ALS70 (1064-nm wavelength) lidar sensor.

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation ...

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Cape Cod National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system ...

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation ...

A first-surface topography Digital Elevation Model (DEM) mosaic for the Cape Cod National Seashore was produced from remotely sensed, geographically referenced elevation measurements acquired cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over Cape Cod National Seashore using the first-generation National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging ...

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high ...

A Digital Elevation Model (DEM) mosaic was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system ...

This data release serves as an archive of sediment physical properties and grain-size data for surficial samples collected offshore of Assateague Island, Maryland and Virginia, for comparison with surficial estuarine and subaerial sedimentological samples collected and assessed following Hurricane Sandy (Ellis and others, 2015 (http://doi.org/10.3133/ofr20151219); Smith and others, 2015 (http://doi.org/10.3133/ofr20151169); Bernier and others, 2016 (https://pubs.usgs.gov/ds/0999/)). The sediment samples ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ...

Binary point-cloud data were produced for a portion of the upper Florida Keys reef tract, Florida, from remotely sensed, geographically referenced elevation measurements collected by Leading Edge Geomatics (LEG) using a Leica Chiroptera II Bathymetric and Topographic Sensor. Dewberry reports that the nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1-Unclassified, 2-Ground ...

A digital elevation model (DEM) mosaic was produced for a portion of the upper Florida Keys reef tract, Florida, from remotely sensed, geographically referenced elevation measurements collected by Leading Edge Geomatics (LEG) using a Leica Chiroptera II Bathymetric and Topographic Sensor. Dewberry reports that the nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1 ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

This data release serves as an archive of sediment physical properties and grain-size data for surficial samples collected offshore of Assateague Island, Maryland and Virginia, for comparison with surficial estuarine and subaerial sedimentological samples collected and assessed following Hurricane Sandy (Ellis and others, 2015 (http://doi.org/10.3133/ofr20151219); Smith and others, 2015 (http://doi.org/10.3133/ofr20151169); Bernier and others, 2016 (https://pubs.usgs.gov/ds/0999/)). The sediment samples ...

This data release serves as an archive of sediment physical properties and grain-size data for surficial samples collected offshore of Assateague Island, Maryland and Virginia, for comparison with surficial estuarine and subaerial sedimentological samples collected and assessed following Hurricane Sandy (Ellis and others, 2015 (http://doi.org/10.3133/ofr20151219); Smith and others, 2015 (http://doi.org/10.3133/ofr20151169); Bernier and others, 2016 (https://pubs.usgs.gov/ds/0999/)). The sediment samples ...

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

These data comprise laboratory observations of oscillatory flows over mobile sand ripples. The data were collected January 6-7, 2016, in the small-oscillatory flow tunnel (S-OFT) in the Sediment Dynamics Laboratory at the U.S. Naval Research Laboratory (NRL), Stennis Space Center, Mississippi (MS), while Donya Frank-Gilchrist was a National Research Council post-doctoral fellow there. The flow tunnel has a 2-m long acrylic test section which was filled with coarse quartz sand. A piston and flywheel were ...

These data comprise laboratory observations of oscillatory flows over mobile sand ripples. The data were collected January 6-7, 2016, in the small-oscillatory flow tunnel (S-OFT) in the Sediment Dynamics Laboratory at the U.S. Naval Research Laboratory (NRL), Stennis Space Center, Mississippi (MS), while Donya Frank-Gilchrist was a National Research Council post-doctoral fellow there. The flow tunnel has a 2-m long acrylic test section which was filled with coarse quartz sand. A piston and flywheel were ...

In 2015, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) conducted sediment sampling surveys on and around the barrier islands of Dauphin Island and Little Dauphin Island, Mobile County, Alabama (AL) under USGS Field Activity Number (FAN) 2015-322-FA (sub-FAN 15BIM09). The study investigated surficial sediment surrounding Dauphin Island and surrounding environments to inform sediment transport model scenarios of coastal change. This data release ...

Over time, as sea levels rise and land subsides, marsh transgression can occur. As shorelines erode and the marsh slowly transgresses landward into the upland, valuable coastal habitat simultaneously is lost and gained. If the shoreline erosion is faster than the rate of upland transgression, the result is a net loss in coastal wetlands. This dataset represents a marsh area change analysis for the Point Aux Chenes and Grand Bay estuaries in Mississippi and Alabama from 1848-1957/1958, 1848-2019/2022, and ...

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.

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 ...

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.

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.

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.

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 ...

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 ...

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 ...

This dataset contains information on the probabilities of storm-induced erosion (collision, inundation and overwash) for each 100-meter (m) section of the United States Pacific coast for return period storm scenarios. The analysis is based on a storm-impact scaling model that uses observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to the hydrodynamic forcing. Storm-induced water levels, due to both surge and waves, are compared to coastal ...

This portion of the data release presents a wave model application developed to simulate wind generated surface gravity waves on an ancient lake on Mars. The phase-averaged wave model, SWAN, was applied within the Delft3D modeling system (Deltares, 2018) with reduced gravity and a range of atmospheric densities and wind speeds to simulate potential conditions that could generate wind waves on Mars. The data release includes model input files for simulations with three different atmospheric densities, ...

This portion of the data release presents tabulated wave parameter results derived from simulations of wind generated surface gravity waves on an ancient lake on Mars. The phase-averaged wave model, SWAN, was applied within the Delft3D modeling system (Deltares, 2018) with reduced gravity and a range of atmospheric densities and wind speeds to simulate potential conditions that could generate wind waves on Mars.

This dataset includes one vector shapefile delineating the position of the top edge of the coastal permafrost bluffs at Barter Island, Alaska spanning seven decades, between the years of 1950 and 2020. Bluff-edge positions delineated from a combination of aerial photography, declassified satellite photography, and very-high resolution satellite imagery can be used to quantify the movement of the bluff edge through time. These data were used to calculate rates of change every 10 meters alongshore using the ...

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the coastal bluffs at Barter Island, Alaska for the time period 1950 to 2020. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate bluff-change rates.

This dataset consists of rate-of-change statistics for the coastal bluffs at Barter Island, Alaska for the time period 1950 to 2020. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each bluff line establishing measurement points, which are then used to ...

This dataset includes one vector shapefile delineating the position of the shorelines at Barter Island, Alaska spanning seven decades, between the years 1947 and 2020. Shoreline positions delineated from a combination of aerial photography, declassified satellite photography, and very-high resolution satellite imagery can be used to quantify the movement of the shoreline through time. These data were used to calculate rates of change every 10 meters alongshore using the Digital Shoreline Analysis System ...

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the shorelines near Barter Island, Alaska for the time period 1947 to 2020. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

This dataset consists of rate-of-change statistics for the shorelines at Barter Island, Alaska for the time period 1947 to 2020. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.0, an ArcGIS extension developed by the U.S. Geological Survey. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to ...

This portion of the data release presents the raw aerial imagery collected during the Unmanned Aerial System (UAS) survey of the Liberty Island Conservation Bank Wildlands restoration site in the Sacramento-San Joaquin Delta on 2018-10-23. The imagery was acquired using two Department of Interior owned 3DR Solo quadcopters fitted with Ricoh GR II digital cameras featuring global shutters. The cameras were mounted using a fixed mount on the bottom of the UAS and oriented in a roughly nadir orientation. The ...

This portion of the data release presents a digital surface model (DSM) and hillshade of the Liberty Island Conservation Bank Wildlands restoration site in the Sacramento-San Joaquin Delta. The DSM has a resolution of 10 centimeters per-pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an Unmanned Aerial System (UAS) on 2018-10-23. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. ...

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 the Unmanned Aerial System (UAS) survey on of the Liberty Island Conservation Bank Wildlands restoration site in the Sacramento-San Joaquin Delta on 2018-10-23. The GCPs were used to establish ground control for the survey and consisted of 24 small (80 x 80 centimeter) square tarps with black-and-white cross patterns placed ...

This portion of the data release presents a high-resolution orthomosaic image of the Liberty Island Conservation Bank Wildlands restoration site in the Sacramento-San Joaquin Delta. The orthomosaic has a resolution of 3 centimeters per-pixel and was derived from structure-from-motion (SfM) processing of aerial imagery collected with an Unmanned Aerial System (UAS) on 2018-10-23. The raw imagery used to create the orthomosaic image was acquired using two UAS fitted with Ricoh GR II digital cameras with ...

This portion of the data release presents a topographic point cloud of the Liberty Island Conservation Bank Wildlands restoration site in the Sacramento-San Joaquin Delta, derived from structure-from-motion (SfM) processing of aerial imagery collected with an Unmanned Aerial System (UAS) on 2018-10-23. The point cloud contains 380,296,568 points at an approximate point density of 323 point per square-meter. Each point contains an explicit horizontal and vertical coordinate, color, intensity, and ...

This portion of the data release presents a digital surface model (DSM) and hillshade of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2018-12-02. 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 removed from the data. In addition, data artifacts resulting from noise and vegetation in the original ...

This portion of the data release presents an RGB orthomosaic image of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2018-12-02. The orthomosaic is available in a high-resolution 6-centimeter (cm) version, as well as a medium-resolution 25 cm version. The high-resolution version is divided into two tiles (east and west) to reduce file download sizes. All imagery is provided in a three-band cloud optimized GeoTIFF format, with 8-bit ...

This portion of the data release presents a digital surface model (DSM) and hillshade of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired 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 other objects have not been removed from the data. In addition, data artifacts resulting from noise and vegetation in the original ...

This portion of the data release presents an RGB orthomosaic image of an expanded area surrounding Whiskeytown Lake derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2019-06-03. The orthomosaic is available in a high-resolution 14-centimeter (cm) version, as well as a medium-resolution 25 cm version. The high-resolution version is divided into two tiles (east and west) to reduce file download sizes. All imagery is provided in a three-band cloud-optimized GeoTIFF format, with ...

This portion of the data release presents an RGB orthomosaic image of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2019-06-03. The orthomosaic is available in a high-resolution 6-centimeter (cm) version, as well as a medium-resolution 25 cm version. The high-resolution version is divided into two tiles (east and west) to reduce file download sizes. All imagery is provided in a three-band cloud-optimized GeoTIFF format, with 8-bit ...

This portion of the data release presents a digital surface model (DSM) and hillshade of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2020-11-10. 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 removed from the data. In addition, data artifacts resulting from noise and vegetation in the original ...

Beach elevation profiles were measured along 29 shore-normal transects on and around Arey and Barter Islands, Alaska in August 2010 and July 2011. Profile data are available in a single comma-delimited file and a zip file including multiple .jpg images that show a visual representation of the individual profiles.

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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) ...

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 ...

This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Faults_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series� ...

This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Point Conception Map Area, California. The vector data file is included in "Folds_OffshorePointConception.zip," which is accessible from https://doi.org/10.5066/F7QN64XQ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series� ...

This part of DS 781 presents fault data for the geologic and geomorphic map of the Offshore of Gaviota map area, California. The vector data file is included in "Faults_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. Cochran, eds.), 2018, California State Waters Map Series—Offshore of Gaviota ...

This part of DS 781 presents fold data for the geologic and geomorphic map of the Offshore of Gaviota map area, California. The vector data file is included in "Folds_OffshoreGaviota.zip," which is accessible from https://doi.org/10.5066/F7TH8JWJ. In the offshore part of the map area, closely-spaced seismic-reflection profiles image many shallow, west-northwest striking folds that have variable geometry, length, amplitude, continuity, and wavelength. The two longest folds, the 17-km-long Molino anticline ...

This part of DS 781 presents data for the paleoshorelines for the geologic and geomorphic map of Monterey Canyon and Vicinity, California. The vector data file is included in "Paleoshorelines_MontereyCanyon.zip," which is accessible from https://doi.org/10.3133/ofr20161072. These data accompany the pamphlet and map sheets of Dartnell, P., Maier, K.L., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Hartwell, S.R., Cochrane, G.R., Ritchie, A.C., Finlayson, D.P., Kvitek, R.G., Sliter, R.W., Greene, H ...

Geologic attributes of the coastal zone of Hawaii, Hawaii

Coastal Slope along the coastal zone of Hawaii, Hawaii

Geologic attributes of the coastal zone of Kauai, Hawaii

Coastal Slope along the coastal zone of Kauai,Hawaii

Geologic attributes of the coastal zone of Lanai, Hawaii

Coastal Slope along the coastal zone of Lanai, Hawaii

Geologic attributes of the coastal zone of Maui, Hawaii

Coastal Slope along the coastal zone of Maui, Hawaii

Geologic attributes of the coastal zone of Molokai, Hawaii

Coastal Slope along the coastal zone of Molokai, Hawaii

Geologic attributes of the coastal zone of Oahu, Hawaii

Coastal Slope along the coastal zone of Oahu, Hawaii

Geologic attributes of the coastal zone of Sand Island (Oahu), Hawaii

Coastal Slope along the coastal zone of Sand Island (Oahu), Hawaii

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 6, 2006, the USGS conducted an oblique aerial photographic survey from Navarre, Florida, to the Chandeleur Islands, Louisiana, and from Grand Point, Alabama, to St. Joseph Point, Mississippi, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 26-27, 2006, the USGS conducted an oblique aerial photographic survey from Dauphin Island, Alabama, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On November 14, 2006, the USGS conducted an oblique aerial photographic survey from the Harney River, Everglades National Park, Florida to Anclote Key, Florida, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On July 26-27, 2007, the USGS conducted an oblique aerial photographic survey from Dauphin Island, Alabama, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On May 6, 2008, the USGS conducted an oblique aerial photographic survey from False Cape State Park, Virginia, to Myrtle Beach, South Carolina, aboard a U.S. Coast Guard HH60 Helicopter aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission (08CH01) was conducted to collect data ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 24–25, 2008, the USGS conducted an oblique aerial photographic survey from Dog Island, Florida, to Breton Island, Louisiana, aboard a U.S. Coast Guard HH60 Helicopter at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 4, 2008, the USGS conducted an oblique aerial photographic survey from the Chandeleur Islands, Louisiana, to Isles Dernieres Barrier Islands Refuge, Louisiana, aboard a Beechcraft Super King Air 200 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted ...

Data release doi:10.5066/P9RIB5GC associated with this metadata record serves as an archive of single-beam bathymetric (SBB) data collected in July 2004 (Madison Bay) and August 2008 (Bully Camp, Point au Chien, Caminada, Fourchon, and Leeville) at six study areas in the Mississippi River Delta Plain (MRDP), Louisiana. Data were collected from historically formed open-water bodies as part of the U.S. Geological Survey’s (USGS) Gulf Coast Subsidence project to provide more extensive spatial coverage than ...

Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), in collaboration with the U.S. Army Corps of Engineers (USACE), conducted geophysical and sedimentological surveys around Cat Island, the westernmost island in the Mississippi-Alabama barrier island chain. The objectives of the study were to understand the geologic evolution of Cat Island relative to other barrier islands in the northern Gulf of Mexico and to identify relationships between the ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On July 24, 2010, the USGS conducted an oblique aerial photographic survey at the Chandeleur Islands, Louisiana, and Dauphin Island, Alabama, aboard a Beechcraft BE90 King Air aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 3, 2010, the USGS conducted an oblique aerial photographic survey from Breton Island to the Chandeleur Islands, Louisiana, aboard a Cessna 210 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On May 19-20, 2010, the USGS conducted an oblique aerial photographic survey from Horseshoe Beach, Florida, to East Cape, Florida, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 22–23, 2010, the USGS conducted an oblique aerial photographic survey from Tampa Bay to the Marquesas Keys, Florida, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On January 22, 2011, the USGS conducted an oblique aerial photographic survey at Breton Island and the Chandeleur Islands, LA, aboard a Cessna 210 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the beach and ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On August 24, 2011, the USGS conducted an oblique aerial photographic survey from Ponte Vedra, Florida, to the South Carolina/North Carolina border, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing ...

As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in July 2013. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to understand better the depositional and erosional processes that drive the morphologic evolution of barrier islands over ...

Breton Island, located at the southern end of the Chandeleur Islands, supports one of Louisiana’s largest historical brown pelican (Pelecanus occidentalis) nesting colonies. Although the brown pelican was delisted as an endangered species in 2009, nesting areas are threatened by continued land loss and are extremely vulnerable to storm impacts. The U.S. Fish and Wildlife Service proposed to restore Breton Island to pre-Hurricane Katrina conditions through rebuilding the shoreface, dune, and back-barrier ...

Foraminiferal samples were collected from Chincoteague Bay, Newport Bay, and Tom’s Cove as well as the marshes on the back-barrier side of Assateague Island and the Delmarva (Delaware-Maryland-Virginia) mainland by U.S. Geological Survey (USGS) researchers from the St. Petersburg Coastal and Marine Science Center in March, April (14CTB01), and October (14CTB02) 2014. Samples were also collected by the Woods Hole Coastal and Marine Science Center (WHCMSC) in July 2014 and shipped to the St. Petersburg ...

Foraminiferal samples were collected from Chincoteague Bay, Newport Bay, and Tom’s Cove as well as the marshes on the back-barrier side of Assateague Island and the Delmarva (Delaware-Maryland-Virginia) mainland by U.S. Geological Survey (USGS) researchers from the St. Petersburg Coastal and Marine Science Center in March, April (14CTB01), and October (14CTB02) 2014. Samples were also collected by the Woods Hole Coastal and Marine Science Center (WHCMSC) in July 2014 and shipped to the St. Petersburg ...

Foraminiferal samples were collected from Chincoteague Bay, Newport Bay, and Tom’s Cove as well as the marshes on the back-barrier side of Assateague Island and the Delmarva (Delaware-Maryland-Virginia) mainland by U.S. Geological Survey (USGS) researchers from the St. Petersburg Coastal and Marine Science Center in March, April (14CTB01), and October (14CTB02) 2014. Samples were also collected by the Woods Hole Coastal and Marine Science Center (WHCMSC) in July 2014 and shipped to the St. Petersburg ...

Foraminiferal samples were collected from Chincoteague Bay, Newport Bay, and Tom’s Cove as well as the marshes on the back-barrier side of Assateague Island and the Delmarva (Delaware-Maryland-Virginia) mainland by U.S. Geological Survey (USGS) researchers from the St. Petersburg Coastal and Marine Science Center in March, April (14CTB01), and October (14CTB02) 2014. Samples were also collected by the Woods Hole Coastal and Marine Science Center (WHCMSC) in July 2014 and shipped to the St. Petersburg ...

Foraminiferal samples were collected from Chincoteague Bay, Newport Bay, and Tom’s Cove as well as the marshes on the back-barrier side of Assateague Island and the Delmarva (Delaware-Maryland-Virginia) mainland by U.S. Geological Survey (USGS) researchers from the St. Petersburg Coastal and Marine Science Center in March, April (14CTB01), and October (14CTB02) 2014. Samples were also collected by the Woods Hole Coastal and Marine Science Center (WHCMSC) in July 2014 and shipped to the St. Petersburg ...

Microfossil (benthic foraminifera) samples were obtained from surficial grab (denoted with “G”) and push core (denoted with “M”) sediments collected in Grand Bay estuary, Mississippi and Alabama, to aid in the paleoenvironmental understanding of Grand Bay estuary. The data presented here were collected as part of the U.S. Geological Survey’s Sea-level and Storm Impacts on Estuarine Environments and Shorelines (SSIEES) project, and Barrier Island Evolution Research (BIER) project. Sampling was ...

Data release doi:10.5066/P9RIB5GC associated with this metadata record serves as an archive of single-beam bathymetric (SBB) data collected in July 2004 (Madison Bay) and August 2008 (Bully Camp, Point au Chien, Caminada, Fourchon, and Leeville) at six study areas in the Mississippi River Delta Plain (MRDP), Louisiana. Data were collected from historically formed open-water bodies as part of the U.S. Geological Survey’s (USGS) Gulf Coast Subsidence project to provide more extensive spatial coverage than ...

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ...

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ...

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ...

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ...

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ...

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ...

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ...

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ...

Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, ...

Breton Island, located at the southern end of the Chandeleur Islands, supports one of Louisiana’s largest historical brown pelican (Pelecanus occidentalis) nesting colonies. Although the brown pelican was delisted as an endangered species in 2009, nesting areas are threatened by continued land loss and are extremely vulnerable to storm impacts. The U.S. Fish and Wildlife Service proposed to restore Breton Island to pre-Hurricane Katrina conditions through rebuilding the shoreface, dune, and back-barrier ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

Researchers from the U.S. Geological Survey (USGS) conducted a long-term coastal morphologic-change study at Fire Island, New York, prior to and after Hurricane Sandy impacted the area in October 2012. The Fire Island Coastal Change project objectives include understanding the morphologic evolution of the barrier island system on a variety of time scales (months to centuries) and resolving storm-related impacts, post-storm beach response, and recovery. In April 2016, scientists from the USGS St. Petersburg ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On September 7, 2016, the USGS conducted an oblique aerial photographic survey from Navarre Beach, Florida, to Breton Island, Louisiana, aboard a Maule MT57 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes in the ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On October 13–15, 2016, the USGS conducted an oblique aerial photographic survey from Port St. Lucie, Florida, to Kitty Hawk, North Carolina, aboard a Cessna 182 aircraft at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was conducted to collect data for assessing incremental changes ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On June 09, 2017, the USGS conducted an oblique aerial photographic survey of the U.S. Army Corps of Engineers Field Research Facility (USACE FRF), located in Duck, North Carolina, aboard a Cessna 182 aircraft at an altitude of approximately 1000 feet (ft). This mission was conducted to collect data for USACE FRF ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic change, and for understanding coastal vulnerability and ...

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project surveyed 34 features visible from the air to be used as ground control points (GCP) on the Outer Banks, North Carolina, on September 24 and 25, 2019, after the passing of Hurricane Dorian (U.S. landfall on September 6, 2019). Global Positioning System (GPS) data were collected in support of aerial imagery surveys documenting the storm impacts and subsequent recovery along the coast and will be used as control and check points in ...

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

Scientist from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected xyz locations for 53 Ground Control Points (GCP) in North Topsail Beach and within the Camp Lejeune Marine Corps Base, North Carolina, June 12-14, 2019. During this study, Global Positing System (GPS) data were collected using a single Spectra SP80 Global Navigation Satellite System (GNSS) receiver affixed to a 2-meter (m) survey pole. Additional attributes pertaining to each survey point ...

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths, in response to storm events, with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three-dimensional (3D) point clouds, and digital elevation/surface models (DEMs/DSMs) using Structure-from-Motion (SfM) photogrammetry methods. These products are valuable for measuring topographic and landscape change, and for understanding coastal ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

The U.S. Geological Survey (USGS) conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On March 27, 1998, the USGS conducted an oblique aerial photographic survey from Fenwick Island State Park, Delaware, to Corolla, North Carolina, aboard a U.S. Coast Guard HH60 Helicopter at an altitude of 500 feet (ft) and approximately 1,000 ft offshore. This mission was conducted to collect data for assessing ...

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

Analysis of shoreline change for Dauphin Island, Alabama was conducted using the U.S. Geological Survey (USGS) Digital Shoreline Analysis System (DSAS) v.4.3 for ArcMap (Thieler and others, 2009) and vector shorelines derived from air photos and lidar elevation surveys. DSAS-generated transects were cast at 100-meter intervals along a user defined shore-parallel baseline. The intersections of transects with the mean high water (MHW) shoreline positions are identified by intercept points. The rate of ...

Analysis of shoreline change for Dauphin Island, Alabama was conducted using the U.S. Geological Survey (USGS) Digital Shoreline Analysis System (DSAS) v.4.3 for ArcMap (Thieler and others, 2009) and vector shorelines derived from air photos and lidar elevation surveys. DSAS-generated transects were cast at 100-meter intervals along a user defined shore-parallel baseline. The intersections of transects with the mean high water (MHW) shoreline positions are identified by intercept points. The rate of ...

Analysis of shoreline change for Dauphin Island, Alabama was conducted using the U.S. Geological Survey (USGS) Digital Shoreline Analysis System (DSAS) v.4.3 for ArcMap (Thieler and others, 2009) and vector shorelines derived from air photos and lidar elevation surveys. DSAS-generated transects were cast at 100-meter intervals along a user defined shore-parallel baseline. The intersections of transects with the mean high water (MHW) shoreline positions are identified by intercept points. The rate of ...

Analysis of shoreline change for Dauphin Island, Alabama was conducted using the U.S. Geological Survey (USGS) Digital Shoreline Analysis System (DSAS) v.4.3 for ArcMap (Thieler and others, 2009) and vector shorelines derived from air photos and lidar elevation surveys. DSAS-generated transects were cast at 100-meter intervals along a user defined shore-parallel baseline. The intersections of transects with the mean high water (MHW) shoreline positions are identified by intercept points. The rate of ...

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

Sedimentologic and topographic data from Hurricane Sandy washover deposits were collected from Southern Long Beach Island, New Jersey, in order to document changes to the barrier-island beaches, dunes, and coastal wetlands due to Hurricane Sandy and subsequent storm events. These data will provide a baseline dataset for use in future coastal change descriptive and predictive studies and assessments. The data presented here were collected as part of the U.S. Geological Survey’s Barrier Island and Estuarine ...

ASCII XYZ data for Cape Hatteras, North Carolina, were produced from remotely sensed, geographically referenced elevation measurements collected post-Hurricane Isabel on September 21, 2003 by the U.S. Geological Survey, in cooperation with the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the first-generation Experimental Advanced Airborne Research Lidar (EAARL-A), a pulsed laser ranging system mounted onboard an aircraft to measure ground ...

Binary point-cloud data were produced for the Chandeleur Islands, Louisiana, from remotely sensed, geographically referenced elevation measurements collected by Leading Edge Geomatics (LEG) using a Leica Chiroptera II Bathymetric and Topographic Sensor. Dewberry reports that the nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1-Unclassified, 2-Ground (includes model key ...

A digital elevation model (DEM) mosaic was produced for the Chandeleur Islands, Louisiana, from remotely sensed, geographically referenced elevation measurements collected by Leading Edge Geomatics (LEG) using a Leica Chiroptera II Bathymetric and Topographic Sensor. Dewberry reports that the nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 0-Never Classified, 1-Unclassified, 2-Ground (includes ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 303 surface sediment samples from Dauphin Island, Alabama, and the surrounding water bodies in August 2015. These sediments were processed to determine physical characteristics such as organic content, bulk density, and grain-size. The environments where the sediments were collected include high and low salt marshes, over-wash deposits, dunes, beaches, sheltered bays, and open water. Sampling by the USGS ...

Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 303 surface sediment samples from Dauphin Island, Alabama, and the surrounding water bodies in August 2015. These sediments were processed to determine physical characteristics such as organic content, bulk density, and grain-size. The environments where the sediments were collected include high and low salt marshes, over-wash deposits, dunes, beaches, sheltered bays, and open water. Sampling by the USGS ...

Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 303 surface sediment samples from Dauphin Island, Alabama, and the surrounding water bodies in August 2015. These sediments were processed to determine physical characteristics such as organic content, bulk density, and grain-size. The environments where the sediments were collected include high and low salt marshes, over-wash deposits, dunes, beaches, sheltered bays, and open water. Sampling by the USGS ...

Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 303 surface sediment samples from Dauphin Island, Alabama, and the surrounding water bodies in August 2015. These sediments were processed to determine physical characteristics such as organic content, bulk density, and grain-size. The environments where the sediments were collected include high and low salt marshes, over-wash deposits, dunes, beaches, sheltered bays, and open water. Sampling by the USGS ...

In 2000, the U.S. Geological Survey (USGS), in cooperation with the University of New Orleans (UNO) and the U.S. Army Corps of Engineers (USACE), conducted geophysical surveys in Barataria Bight from Sandy Point to Belle Pass, LA (Study Area Map). Sediment cores were collected as part of the USGS Subsidence and Coastal Change (SCC) Project, which included the Barataria Sand-Resource Study (bss) vibracore surveys (Kindinger and others, 2001). This report also contains information from other cruise data sets, ...

In 2006 and 2007, the U.S. Geological Survey (USGS) and collaborators at the University of New Orleans (UNO) collected high-resolution seismic profiles and subsurface cores around the Chandeleur and Breton Islands, Louisiana. To ground-truth the acoustic seismic surveys conducted in 2006, 124 vibracores were acquired during the 07SCC04 and 07SCC05 cruises in 2007. These cores were collected within the back-barrier, nearshore, and offshore environments. The surveys were conducted as part of a post-hurricane ...

As part of the Barrier Island Evolution Research (BIER) project, scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) collected sediment samples from the northern Chandeleur Islands in March and September 2012. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier ...

Assessing the physical change to shorelines and wetlands is critical in determining the resiliency of wetland systems that protect adjacent habitat and communities. The wetland and back-barrier shorelines of Assateague Island, located in Maryland and Virginia, changed as a result of wave action and storm surge that occurred during Hurricane Sandy, which made landfall on October 29, 2012. The impact of Hurricane Sandy will be assessed and placed in its historical context to understand the future ...

Assessing the physical change to shorelines and wetlands is critical in determining the resiliency of wetland systems that protect adjacent habitat and communities. The wetland and back-barrier shorelines of Assateague Island, located in Maryland and Virginia, changed as a result of wave action and storm surge that occurred during Hurricane Sandy, which made landfall on October 29, 2012. The impact of Hurricane Sandy will be assessed and placed in its historical context to understand the future ...

Assessing the physical change to shorelines and wetlands is critical in determining the resiliency of wetland systems that protect adjacent habitat and communities. The wetland and back-barrier shorelines of New Jersey changed as a result of wave action and storm surge that occurred during Hurricane Sandy, which made landfall on October 29, 2012. The impact of Hurricane Sandy will be assessed and placed in its historical context to understand the future vulnerability of wetland systems. Making these ...

Assessing the physical change to shorelines and wetlands is critical in determining the resiliency of wetland systems that protect adjacent habitat and communities. The wetland and back-barrier shorelines of New Jersey changed as a result of wave action and storm surge that occurred during Hurricane Sandy, which made landfall on October 29, 2012. The impact of Hurricane Sandy will be assessed and placed in its historical context to understand the future vulnerability of wetland systems. Making these ...

In response to the 2010 Governor’s Action Plan to clean up the Barnegat Bay–Little Egg Harbor (BBLEH) estuary in New Jersey, the U.S. Geological Survey (USGS) partnered with the New Jersey Department of Environmental Protection in 2011 to begin a multidisciplinary research project to understand the physical controls on water quality in the bay. Between 2011 and 2013, USGS scientists mapped the geological and morphological characteristics of the seafloor of the BBLEH estuary using a suite of geophysical ...

In response to the 2010 Governor’s Action Plan to clean up the Barnegat Bay–Little Egg Harbor (BBLEH) estuary in New Jersey, the U.S. Geological Survey (USGS) partnered with the New Jersey Department of Environmental Protection in 2011 to begin a multidisciplinary research project to understand the physical controls on water quality in the bay. Between 2011 and 2013, USGS scientists mapped the geological and morphological characteristics of the seafloor of the BBLEH estuary using a suite of geophysical ...

The U.S. Geological Survey has a long history of responding to and documenting the impacts of storms along the Nation’s coasts and incorporating these data into storm impact and coastal change vulnerability assessments. Although physical changes caused by tropical and extratropical storms to the sandy beaches and dunes fronting barrier islands are generally well documented, the interaction between sandy shoreline erosion and overwash with the back-barrier wetland and estuarine environments is poorly ...

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high ...

A Digital Elevation Model (DEM) mosaic was data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over some of the eastern Louisiana barrier islands in cooperation with the National Park Service (NPS), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

Hurricane Sandy made U.S. landfall, coincident with astronomically high tides, near Atlantic City, New Jersey, on October 29, 2012. The storm, the largest on historical record in the Atlantic basin, affected an extensive area of the east coast of the United States. The highest waves and storm surge were focused along the heavily populated New York and New Jersey coasts. At the height of the storm, a record significant wave height of 9.6 meters (m) was recorded at the wave buoy offshore of Fire Island, New ...

Hurricane Sandy made U.S. landfall, coincident with astronomical high tides, near Atlantic City, New Jersey, on October 29, 2012. The storm, the largest on historical record in the Atlantic basin, affected an extensive area of the east coast of the United States. The highest waves and storm surge were focused along the heavily populated New York and New Jersey coasts. At the height of the storm, a record significant wave height of 9.6 meters (m) was recorded at the wave buoy offshore of Fire Island, New ...

Hurricane Sandy made U.S. landfall, coincident with astronomically high tides, near Atlantic City, New Jersey, on October 29, 2012. The storm, the largest on historical record in the Atlantic basin, affected an extensive area of the east coast of the United States. The highest waves and storm surge were focused along the heavily populated New York and New Jersey coasts. At the height of the storm, a record significant wave height of 9.6 meters (m) was recorded at the wave buoy offshore of Fire Island, New ...

Hurricane Sandy made U.S. landfall, coincident with astronomical high tides, near Atlantic City, New Jersey, on October 29, 2012. The storm, the largest on historical record in the Atlantic basin, affected an extensive area of the east coast of the United States. The highest waves and storm surge were focused along the heavily populated New York and New Jersey coasts. At the height of the storm, a record significant wave height of 9.6 meters (m) was recorded at the wave buoy offshore of Fire Island, New ...

The model output of bathymetry and topography values resulting from a deterministic simulation at Dauphin Island, Alabama, as described in USGS Open-File Report 2019–1139 (https://doi.org/10.3133/ofr20191139), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry refer to Mickey and others (2020).

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

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

The Simulating WAves Nearshore (SWAN) wave model input grid 4 bathymetry with pit 3 configuration (G4_P3_grid.shp) and output of significant wave height, dominant wave period, and mean wave direction resulting from simulation of wave scenarios at Breton Island, LA, as described in USGS Open-File Report 20151055 are provided here.

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

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

To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a ...

To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a ...

To understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites in the Grand Bay National Estuarine Research Reserve, Mississippi (GNDNERR). Each site consisted of four plots located along a transect perpendicular to the marsh-estuary shoreline at 5-meter (m) increments (5, 10, 15, and 20 m from the shoreline). Each plot contained four net sedimentation tiles (NST) that were secured ...

To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each site consisted of five plots located along a ...

To understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected four study sites in the Grand Bay National Estuarine Research Reserve, Mississippi (GNDNERR). Each site consisted of four plots located along a transect perpendicular to the marsh-estuary shoreline at 5-meter (m) increments (5, 10, 15, and 20 m from the shoreline). Each plot contained four net sedimentation tiles (NST) that were secured ...

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

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

On October 29, 2012, Hurricane Sandy made landfall as a post-tropical storm near Brigantine, New Jersey, with sustained winds of 70 knots (80 miles per hour) and tropical-storm-force winds extending 870 nautical miles in diameter (Blake and others, 2013). The effects of Hurricane Sandy’s winds and storm surge included erosion of the beaches and dunes as well as breaching of barrier islands in both natural and heavily developed areas of the coast (Spokin et. al., 2014). On November 4-6, 2012, the U.S. ...

Antecedent topography is an important aspect of coastal morphology when studying and forecasting coastal change hazards. The uncertainty in morphologic response of storm-impact models and their use in short-term hazard forecasting and decadal forecasting is important to account for when considering a coupled model framework. Mickey and others (2020) provided a methodology to investigate uncertainty of profile response within the storm impact model, XBeach, related to varying antecedent topographies. A ...

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over a portion of the Texas coastline, post-Hurricane Ike (September 2008 hurricane), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams ...

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over a portion of the Texas coastline, post-Hurricane Ike (September 2008 hurricane), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams ...

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

The model input for the bathymetry and topography values resulting from a deterministic simulation at Dauphin Island, Alabama, as described in U.S. Geological Survey (USGS) Open-File Report 2019-1139 (https://doi.org/10.3133/ofr20191139), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry refer to Mickey and others (2020).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over northwest Florida, post-Hurricane Katrina (August 2005 hurricane), using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The ...

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over northwest Florida, post-Hurricane Katrina (August 2005 hurricane), using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), hurricanes Ivan (2004) and Katrina (2005) were simulated at Dauphin Island, Alabama, under present-day conditions and future sea level rise scenarios as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) ...

Using the numerical model XBeach version 4926 (Roelvink and others, 2009), various bottom friction scenarios were simulated for hurricanes Ivan (2004) and Katrina (2005) at Dauphin Island, Alabama as described in Passeri and others, 2018. The XBeach model setup requires the input of a merged topographic and bathymetric digital elevation model (DEM), and inputs of wave spectra (based on significant wave height, peak wave period and wave direction) and water level (tide and surge) time series. Model inputs ...

This shapefile consists of Dauphin Island, AL shorelines extracted from lidar data collected from November 1998 to January 2014. This dataset contains 14 Mean High Water (MHW) shorelines separated into 37 shoreline segments alongshore Dauphin Island, AL. The individual sections are divided according to location along the island and shoreline type: open ocean, back-barrier, marsh shoreline. Raw lidar point data was converted to a gridded surface, from which a contour of the operational MHW shoreline (0.24 ...

The data release (Bernier, 2021) associated with this metadata record serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery at the northern Chandeleur Islands, Louisiana. To minimize the effects of tidal water-level variations, 75 cloud-free, low-water images acquired between 1984 and 2019 were analyzed. Water, bare earth (sand), vegetated, and intertidal land-cover classes were mapped from Hewes Point to Palos Island using successive thresholding and masking ...

The data release (Bernier, 2021) associated with this metadata record serves as an archive of coastal land-cover and feature datasets derived from Landsat satellite imagery at the northern Chandeleur Islands, Louisiana. To minimize the effects of tidal water-level variations, 75 cloud-free, low-water images acquired between 1984 and 2019 were analyzed. Water, bare earth (sand), vegetated, and intertidal land-cover classes were mapped from Hewes Point to Palos Island using successive thresholding and masking ...

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

The shoreline of Cape Hatteras, North Carolina, is experiencing long-term coastal erosion. In order to better understand and monitor the changing coastline, historical aerial imagery is used to map shoreline change. For the area of Hatteras Island from Cape Point to Oregon Inlet, fourteen aerial datasets from 1978-2002 were scanned and georeferenced for use in a Geographic Information System (GIS). Shoreline positions (high water line) were digitized from georeferenced imagery. The shoreline vectors were ...

The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ...

The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ...

The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ...

The Barrier Island and Estuarine Wetland Physical Change Assessment was created to calibrate and test probability models of barrier island estuarine shoreline (backshore) and beach sandline change for study areas in Virginia, Maryland, and New Jersey. The models examined the influence of hydrologic and physical variables related to long-term and storm-derived overwash and back-barrier shoreline change. Input variables were constructed into a Bayesian Network (BN) using Netica, a computer program created by ...

Seamless topographic-bathymetric (topo-bathy) profiles and their derived morphologic characteristics were developed for sandy coastlines along the Atlantic and Gulf coasts of the United States. As such, the rocky coasts of Maine, the coral reefs in southern Florida and the Keys, and the marsh coasts in the Mississippi Delta and the Florida Big Bend region and are not included in this dataset. Topographic light detection and ranging (lidar) data (dune crest, dune toe, and shorelines) from Doran and others ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

The numerical model Delft3D (developed by Deltares) was developed to evaluate the potential effects of proposed navigation channel deepening and widening in Mobile Harbor, Alabama (AL). The Delft3D model setup requires the input of a merged topographic and bathymetric elevations, a wave climate based on significant wave heights, peak wave period and mean wave direction, and a tidal-time series. The model was validated by comparing model outputs from deterministic runs with observations of water levels and ...

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

The model input and output of topography and bathymetry values resulting from forecast simulations of coupled modeling scenarios occurring between 2015 and 2025 at Dauphin Island, Alabama, and described in U.S. Geological Survey (USGS) Open-File Report 2020–1001 (https://doi.org/10.3133/ofr20201001), are provided here. For further information regarding model input generation and visualization of model output topography and bathymetry, refer to Mickey and others (2020).

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over a portion of the Texas coastline, post-Hurricane Rita (September 2005 hurricane), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams ...

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over a portion of the Texas coastline, post-Hurricane Rita (September 2005 hurricane), using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams ...

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

The numerical model XBeach (version 4937) was used to investigate how different storm scenarios impact the sediment berm constructed offshore of the Chandeleur Islands and adjacent areas. The XBeach model solves coupled 2-dimensional, horizontal wave propagation equations to predict flow, sediment transport, and bottom changes for varying spectral wave and flow boundary conditions (Roelvink and others, 2009 ). The XBeach model setup requires the input of a merged topographic and bathymetric DEM, and inputs ...

Data release doi:10.5066/F7BR8QBH associated with this metadata record serves as an archive of elevation data collected in August 2010 from Sabine National Wildlife Refuge (SNWR), Louisiana (U.S. Geological Survey [USGS] Field Activity Number [FAN] 10SWL01). Point (xyz) elevations were collected from historically formed open-water bodies and the surrounding emergent marsh using a combination of stop-and-go (semi-kinematic) and kinematic differential Global Positioning System (DGPS) surveying techniques. ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Rates of shoreline change for Dauphin Island, Alabama were generated for three analysis periods, using two different shoreline proxy datasets. Mean High Water line (MHW) shorelines were generated from 14 lidar datasets (1998-2014) and Wet Dry Line (WDL) shorelines were digitized from ten sets of georeferenced aerial images (1940-2015). Rates of change were generated for three groups of shorelines: MHW (lidar), WDL (aerial) and MHW and WDL shorelines combined. These data will aid in developing an ...

Rates of shoreline change for Dauphin Island, Alabama were generated for three analysis periods, using two different shoreline proxy datasets. Mean High Water line (MHW) shorelines were generated from 14 lidar datasets (1998-2014) and Wet Dry Line (WDL) shorelines were digitized from ten sets of georeferenced aerial images (1940-2015). Rates of change were generated for three groups of shorelines: MHW (lidar), WDL (aerial) and MHW and WDL shorelines combined. These data will aid in developing an ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

Using version 52.30 of the ADvanced CIRCulation (ADCIRC) numerical model (Luettich and others, 1992), astronomic tides were simulated at Mobile Bay, Alabama (AL), under scenarios of Holocene geomorphic configurations representing the period of 3500 to 2300 years before present including a breach in the Morgan Peninsula and a land bridge at Pass aux Herons, as described in Smith and others (2020). The two-dimensional ADCIRC model can be applied to coastal and estuarine systems to solve for time-dependent ...

The U.S. Army Corps of Engineers(USACE) contracted a beach survey of Fire Island, New York from September 17–October 6, 2013, for the purpose of planning a beach reconstruction project following Hurricane Sandy. This dataset contains elevation data of subaerial morphology and nearshore bathymetry collected using real time kinematic global positioning system (RTK-GPS) and hydrography techniques. The data were provided to the U.S. Geological Survey(USGS) to contribute to an existing monitoring dataset of ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Using version 5527 of the XBeach numerical model (Roelvink and others, 2009), barrier island morphological change was simulated at Dauphin Island, Alabama (AL), for a 30-year forecast of multiple storms and sea level rise, considering scenarios of no-action and beach and dune nourishment as described in Passeri and others (2021). The two-dimensional XBeach model can be applied to barrier islands to solve for time-dependent topography and bathymetry. The XBeach model setup requires the input of topographic ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly ...

The data in this part of the release are digital surface models (DSMs) that characterize the beach at the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study nearshore coastal processes during storm events. USGS participation in DUNEX will contribute new measurements and models that will increase our understanding of storm impacts to coastal ...

This dataset defines the volume of sand along a 10-meter (m) wide profile between the seaward-most dune toe and the mean high water shoreline derived from light detection and ranging (lidar) digital elevation models (DEMs). Refer to Doran and others (2017) for more information about the source lidar data. These data support the National Fish and Wildlife Foundation (NFWF)-funded project entitled “Monitoring Hurricane Sandy Beach and Marsh Resilience in New York and New Jersey” (NFWF project ID 2300.16 ...

The data in this part of the release are orthomosaics that characterize the beach at the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. During September and October 2021, USGS and Woods Hole Oceanographic Institute (WHOI) scientists conducted multiple field surveys to collect a topobathy elevation time series. Images of the beach for use in structure from motion were taken with a camera attached to a helium filled balloon-kite (Helikite). Agisoft Metashape (v ...

This dataset defines shoreline change rates for each 10-meter (m)-wide profile calculated via endpoint rate and linear regression from Himmelstoss and others (2018). Shoreline change rates were calculated for two time periods: pre-Sandy (2010-2012) and post-Sandy (2012-2022). The profiles were derived from light detection and ranging (lidar) digital elevation models (DEMs). Refer to Doran and others (2017) for more information about the source lidar data. These data support the National Fish and Wildlife ...

This data release presents structure-from-motion (SFM) products derived from aerial imagery surveys with precise Global Navigation Satellite System (GNSS) navigation data flown in a piloted fixed wing aircraft taken along the North Carolina coast in response to Hurricane Florence (available here https://coastal.er.usgs.gov/data-release/doi-P91KB9SF/). USGS researchers use the elevation models and orthorectified imagery to assess future coastal vulnerability, nesting habitats for wildlife, and provide data ...

This data release presents structure-from-motion (SFM) products derived from aerial imagery surveys with precise Global Navigation Satellite System (GNSS) navigation data flown in a piloted fixed wing aircraft taken along the North Carolina coast in response to Hurricane Florence (available here https://coastal.er.usgs.gov/data-release/doi-P91KB9SF/). USGS researchers use the elevation models and orthorectified imagery to assess future coastal vulnerability, nesting habitats for wildlife, and provide data ...

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 ...

These data map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA, providing updated regional context for the 2019 CoastCam installation. CoastCam CACO-01 are two video cameras aimed at the beach that view the coast shared by beachgoers, shorebirds, seals, and sharks. These data were collected as part of field activity 2022-015-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region. In March 2022, U.S. Geological Survey and Woods ...

The data in this release map the beach and nearshore environment at Marconi Beach in Wellfleet, MA and provide updated environmental context for the 2021 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2022-014-FA and a collaboration with the National Park Service at Cape Cod National Seashore to monitor the region that falls within the field of view of CoastCam CACO-02, which are two video cameras aimed at the ...

Digital elevation models (DEMs) were created from aerial imagery collected between August 30 and September 2, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions prior to Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface before Hurricane Dorian and were created to document inter-annual changes in ...

Orthoimages were created from aerial imagery collected between August 30 and September 2, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RBG-averaged orthoimages were created to document ground conditions prior to Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RBG-averaged orthoimages help researchers estimate the land surface before Hurricane Dorian and were created to document ...

Digital elevation models (DEMs) were created from aerial imagery collected between September 08 and September 13, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions post-Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface after Hurricane Dorian and were created to document inter-annual changes in ...

RGB-averaged ortho products were created from aerial imagery collected between September 8 and 13, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RBG-averaged orthoimages were created to document ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RBG-averaged orthoimages help researchers estimate the land surface after Hurricane Dorian and were created to ...

RGB-averaged orthoimages were created from aerial imagery collected on October 11, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RBG-averaged orthoimages were created to document ground conditions one-month after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RBG-averaged orthoimages help researchers estimate the land surface after Hurricane Dorian and were created to document ...

Digital elevation models (DEMs) were created from aerial imagery collected November 26, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document ground conditions two-months after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers estimate the land surface one-month post-Hurricane Dorian and were created to document inter-annual changes in ...

RGB-averaged orthoimages were created from aerial imagery collected on November 26, 2019, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RBG-averaged orthoimages were created to document ground conditions two-months after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RBG-averaged orthoimages help researchers estimate the land surface after Hurricane Dorian and were created to document ...

Digital elevation models (DEMs) were created from aerial imagery collected February 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers document inter-annual changes in shoreline position and coastal morphology in response to storm events using ...

RGB-averaged orthoimages were created from aerial imagery collected February 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These RGB-averaged orthoimages were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The RGB-averaged orthoimages help researchers document inter-annual changes in shoreline position and coastal morphology in ...

Digital elevation models (DEMs) were created from aerial imagery collected May 08 and 09, 2020, along the North Carolina coast between the Virginia-North Carolina border vicinity and Cape Lookout, North Carolina. These DEMs were created to document recovery ground conditions after Hurricane Dorian, which made landfall on the North Carolina coast on September 6, 2019. The DEMs help researchers document inter-annual changes in shoreline position and coastal morphology in response to storm events using aerial ...

The storm-induced Coastal Change Hazards component of the National Assessment of Coastal Change Hazards (NACCH) project focuses on understanding the magnitude and variability of extreme storm impacts on sandy beaches. Light detection and ranging (lidar)-derived beach morphologic features such as dune crest, toe, and shoreline help define the vulnerability of the beach to storm impacts. This dataset defines the elevation and position of the seaward-most dune crest and toe and the mean high-water shoreline ...

This part of the data release presents digital elevation models (DEMs) spanning the ocean shoreline of Alaska from Icy Cape to Cape Prince of Wales. Aerial images were collected, and data were processed, by Fairbanks Fodar (https://www.fairbanksfodar.com) in Fairbanks, Alaska, for the U.S. Geological Survey. The aerial images, from which the DEMs were created, were collected in 2016 between August 29 and September 4 and extend from the shoreline to 400-4000 meters inland. The aerial images were collected ...

This part of the data release presents orthoimagery spanning the ocean shoreline of Alaska from Icy Cape to Cape Prince of Wales. Aerial images were collected, and data were processed, by Fairbanks Fodar (https://www.fairbanksfodar.com) in Fairbanks, Alaska, for the U.S. Geological Survey. The aerial images, from which the orthoimages were created, were collected in 2016 between August 29 and September 4 and extend from the shoreline to 400-4000 meters inland. The aerial images were collected with precise ...

This part of the data release presents georeferenced elevation point clouds spanning the ocean shoreline of Alaska from Icy Cape to Cape Prince of Wales. Aerial images were collected, and data were processed, by Fairbanks Fodar (https://www.fairbanksfodar.com) in Fairbanks, Alaska, for the U.S. Geological Survey. The aerial images, from which the point clouds were derived, were collected in 2016 between August 29 and September 4 and extend from the shoreline to 400-4000 meters inland. The aerial images were ...

This part of the data release presents a shapefile that includes a spatial index of orthoimagery and elevation data describing the Alaskan coastline from Icy Cape to Cape Prince of Wales. The data products referenced in this index include orthoimagery, digital surface models, and elevation point clouds which were generated from aerial imagery using structure-from-motion methods. Fairbanks Fodar, a contracted mapping service, collected the aerial imagery in 2016 and created all of the data products ...

Beach and foreshore elevation data were collected in the vicinity of Wainwright, Alaska. The area from the mouth of the Kuk River to about 8 km to the northeast was measured in August 2009. The area from the mouth of the Kuk River to about 5 km to the northeast was measured in October 2009. The elevation data were collected with Real-Time Kinematic (RTK) Global Positioning System (GPS) systems mounted on all-terrain vehicles. The GPS sampling rate was 1 Hz with vehicle speeds maintained at less than 15 km ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...

This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides beach profile data collected at Madeira Beach, Florida. Data were collected on foot by a person equipped with a Global Positioning System (GPS) antenna affixed to a backpack outfitted for surveying location and elevation data (XYZ) along pre-determined transects. The horizontal position data are given in the Universal Transverse Mercator (UTM) projected coordinate system, Zone 17 ...