Computational methods

Mathematical techniques used to analyze numerical data.
This category is also used for mathematical methods.
Subtopics:
Image analysis (281 items)
Spatial analysis (274 items)

704 results listed by similarity [list alphabetically]
Bathymetry of the Aleutian and Bowers Basin, Bering Sea

This coverage contains bathymetric contours for Aleutian Basin and Bowers Basin east of the 1867 Convention Line in the southwestern Bering Sea. Geographic extent of this file is: 51.7 : 62.0 N / -165.1 W : 170.0 E. Bathymetric contours range from 50 m to 6400 m. This coverage was used to display the bathymetry for the Atlas of the U.S. Exclusive Economic Zone, Bering Sea, U.S. Geological Survey Misc. Investigations Series I-2053, 1991 (also known as the GLORIA survey). The map was published separately by ...

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Geological Society of America Gulf of Andyr Bathymetry

Bathymetric contours were generated from soundings collected during surveys and cruises by the Hydrographic Office, National Ocean Survey, and Coast and Geodetic Survey. The region covered by the map is the Bering Sea Shelf from Bristol Bay, Alaska to the Gulf of Anadyr, Russia. Bathymetry is in meters at 10 m intervals, with 5 m supplemental contours. The digitized portion includes the Anadyr Gulf and Bering Strait in Russian waters (west of the Exclusive Economic Zone), to supplement digitized National ...

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Bathymetric Map of the Bering/Chukchi Sea

Two bathymetric maps were developed by the U.S. Geological Survey, one for the Chukchi Sea and Arctic Ocean, and one for the Aleutian Trench and Bering Sea. The 2 maps overlap near the Bering Strait. Bathymetric contours were generated from several published sources. It is unclear whether new soundings were collected for these maps. The northern map extends from Wrangel Island, Russia to MacKenzie Bay, Canada, and north to 76 N latitude. The southern map extends from Shelikof Bay, Russia, to the western tip ...

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Bathymetry of the Bering Strait: Chukotka to Diomede Island

The bathymetric map of the northern Bering Sea region, plate 1 of USGS Professional Paper 759-B, 1976, was generated using published National Ocean Service maps and an unpublished map from Univ. of Washington. The region covered by the map includes the eastern tip of the Chukotka Peninsula, Russia, east to the Seward Peninsula and northern Yukon Delta, Alaska, and south to St. Lawrence Island, Alaska. The portion digitized was west of the Exclusive Economic Zone (EEZ, or Convention Line of 1867). Only the ...

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Chukchi Sea Bathymetry

Bathymetric contours were generated from soundings collected during geophysical surveys conducted by the USGS from 1969 to 1982, and supplemented by data from other sources. The region covered by the map is the Chukchi Sea from the Bering Strait north to the Arctic Ocean, and Point Barrow, Alaska west to Herald Island, Russia. The map stops just east of Wrangel Island, Russia. Bathymetry is in meters, including 10 meter contour intervals from 10 to 100 meters, and 100 meter contour intervals at depths ...

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Coastal Bathymetry of the Bering, Chuckhi, and Beaufort Seas

Bathymetric contours were generated from soundings collected by National Ocean Service vessels from ~1900 to ~1971. The 1:250,000 maps are available for U.S. coastal waters. Bathymetric contours are in meters, with 10 meter intervals out to 200 m, supplemented by 2 m contours. Beyond 200 m, contours are at 50 m intervals to maximum depth. The GIS database derived from these maps includes the Bering, Chukchi, and Beaufort Seas in western and northern Alaska (~100 maps).

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10-m resolution image of shaded relief multibeam bathymetry in Massachusetts Bay, pseudocolored by backscatter intensity (MB_BACKPC10M.TIF)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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10-m resolution image of shaded relief multibeam bathymetry in Massachusetts Bay, colored by water depth (MB_BATHYCLR10M.TIF)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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10-m resolution image of shaded relief multibeam bathymetry in Massachusetts Bay (MB_SRELIEF10M.TIF)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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6-m resolution gray-scale image of shaded-relief multibeam bathymetry in western Massachusetts Bay map Quadrangle 1 (Q1_SRELIEF.TIF)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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6-m resolution image of shaded relief multibeam bathymetry in western Massachusetts Bay map Quadrangle 2, pseudo-colored by backscatter intensity (Q2_BACKPC.TIF)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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6-m resolution gray-scale image of shaded-relief multibeam bathymetry in western Massachusetts Bay map Quadrangle 2 (Q2_SRELIEF.TIF)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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6-m resolution image of shaded relief multibeam bathymetry in western Massachusetts Bay map Quadrangle 3, pseudo-colored by backscatter intensity (Q3_BACKPC.TIF)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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Color shaded relief TIFF image of the area surrounding Lake Mohave: Geographic Coordinates

Lake Mohave is one of several multi-purpose reservoirs that have been constructed on the Colorado River. The lake was formed upon completion of the Davis Dam in 1953. No mapping of the floor of the lake had been conducted since completion of the Davis Dam. The U.S. Geological Survey, in cooperation with researchers from the University of Nevada Las Vegas, completed a geophysical survey of this lake in April 2002. The survey included collection of sidescan sonar imagery of nearly the entire lake floor, and ...

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Nahant to Gloucester, Massachusetts Bathymetric Slope in degrees (slopedeg_fm3)

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program. Woods Hole Science Center. Project data were collected during two separate surveys in the Fall of 2003 (RAFA03007) and the Spring of 2004 (RAFA04002). Bathymetric data were collected with a SEA/Submetrix 2000 series interferometric 234 kHz sonar. The sonar was pole-mounted on the R/V Rafael. Survey line spacing was 100m

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Hillshade of Swath Bathymetry collected by the USGS offshore of the Grand Strand, South Carolina, 1999-2003 (BATHY_HILLSH, grid)

In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this ...

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Hillshade of Multibeam Bathymetry 2 meter/pixel of Boston Harbor and Approaches (bh_2mmbhsf)

These data are high-resolution bathymetric measurements of the seafloor from Boston Harbor and the harbor approaches, Massachusetts. Approximately 170 km² of sidescan sonar and bathymetric data were collected by the National Oceanic and Atmospheric Administration (NOAA) Ship Whiting in 2000 and 2001 and reprocessed and gridded by the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS).

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Shaded-relief GeoTIFF image of a portion of Cape Cod and the surrounding sea floor

In order to test hypotheses about groundwater flow under and into estuaries and the Atlantic Ocean, geophysical surveys, geophysical probing, submarine groundwater sampling, and sediment coring were conducted by U.S. Geological Survey (USGS) scientists at Cape Cod National Seashore (CCNS) from 2004 through 2006. Coastal resource managers at CCNS and elsewhere are concerned about nutrients that are entering coastal waters via submarine groundwater discharge, which are contributing to eutrophication and ...

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25m Hillshaded Bathymetric ArcRaster Grid of Apalachicola Bay and St. George Sound, FL (APBAY25HS)

These data were collected under a cooperative mapping program between the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration Coastal Services Center (NOAA\CSC), and the Apalachicola National Estuarine Research Reserve (NERR). The primary objectives of this program were to collect marine geophysical data to develop a suite of seafloor maps to better define the extent of oyster habitats, the overall seafloor geology of the bay and provide updated information for management of ...

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5 meter color-hillshaded relief GeoTIFF of both the inshore and offshore area of Cape Ann - Salisbury Beach Survey Area (CABATH5M_GEOG.TIF, Geographic, WGS84)

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Science Center. Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine reserves, and ...

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5 meter ArcRaster Bathymetric Hillshade of both the inshore and offshore portions of the Cape Ann - Salisbury Beach Massachusetts Survey Area (CABATH5MHS, UTM Zone 19, WGS84)

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Science Center. Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine reserves, and ...

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Hillshaded relief produced from bathymetric data collected by the U.S. Geological Survey offshore of the Chandeleur Islands, LA, 2006-2007 (BATHY_HILLSH.ASC, ESRI ASCII GRID)

In 2006 and 2007, the U.S. Geological Survey, in partnership with Louisiana Department of Natural Resources and the University of New Orleans, conducted geologic mapping to characterize the sea floor and shallow subsurface stratigraphy offshore of the Chandeleur Islands in Eastern Louisiana. The mapping was carried out during two cruises on the R/V Acadiana. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (234 kHz), Klein 3000 dual frequency sidescan sonar, and an ...

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Depth-colored hillshade image of bathymetry data collected by the U.S. Geological Survey and the National Oceanic and Atmospheric Administration offshore of Massachusetts between Duxbury and Hull with data gaps (DH_bathyhlshd_wgaps, Depth-colored Hillshade GeoTIFF, UTM Zone 19, WGS84)

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine ...

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Hillshaded relief produced from bathymetric data collected by the U.S. Geological Survey and the National Oceanic and Atmospheric Administration offshore of Massachusetts between Duxbury and Hull (DH_hlshd5m, Esri binary grid, UTM Zone 19, WGS84)

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine ...

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Color-hillshade relief GeoTIFF image of the Potomac River/Chesapeake Bay Area (CLRHSHD_POTO_GEO.TIF, Geographic, NAD83)

In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ...

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Color-hillshade relief GeoTIFF image of the Potomac River/Chesapeake Bay Area (CLRHSHD_POTO.TIF, UTM, Zone 18, NAD83)

In order to test hypotheses about groundwater flow under and into Chesapeake Bay, geophysical surveys were conducted by U.S. Geological Survey (USGS) scientists on Chesapeake Bay and the Potomac River Estuary in September 2006. Chesapeake Bay resource managers are concerned about nutrients that are entering the estuary via submarine groundwater discharge, which are contributing to eutrophication. The USGS has performed many related studies in recent years to provide managers with information necessary to ...

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5 meter ArcRaster hillshade of bathymetry acquired with a SEA Ltd. SWATHplus interferometric sonar offshore of Massachusetts within northern Cape Cod Bay (CCB_FILL_HS Esri BINARY GRID, UTM Zone 19N).

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat ...

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Interpolated swath bathymetry hillshaded image collected by the U.S. Geological Survey - Woods Hole Coastal and Marine Science Center surrounding the nearshore of the Elizabeth Islands, MA, 2010 (ei_2hm_fillhs.tif, GeoTIFF)

These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ...

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Interpolated swath bathymetry shaded relief image collected by the U.S. Geological Survey - Woods Hole Coastal and Marine Science Center surrounding the nearshore of the Elizabeth Islands, MA, 2010 (ei_2hm_shdrlf_image_dd.tif, GeoTIFF)

These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ...

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5 meter ArcRaster grid of hillshaded bathymetry data collected in Buzzards Bay by the U.S. Geological Survey and the National Oceanic and Atmospheric Administration offshore of Massachusetts in 2004, 2009, 2010, and 2011 (BB_hlshd5m, UTM Zone 19N, Esri BINARY GRID)

These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish habitat ...

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30-m Hillshaded relief image produced from swath interferometric, multibeam, and lidar datasets (navd_bath_30m.tif GeoTIFF Image; UTM, Zone 19N, WGS 84)

These data are qualitatively derived interpretive polygon shapefiles and selected source raster data defining surficial geology, sediment type and distribution, and physiographic zones of the sea floor from Nahant to Northern Cape Cod Bay. Much of the geophysical data used to create the interpretive layers were collected under a cooperative agreement among the Massachusetts Office of Coastal Zone Management (CZM), the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, the National Oceanic ...

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Hillshaded relief image derived from elevations of the late-Wisconsinan regressive unconformity beneath the Massachusetts inner continental shelf between Nahant and Northern Cape Cod Bay (Urelevhs GeoTIFF Image; UTM, Zone 19N, WGS 84)

These data are qualitatively derived interpretive polygon shapefiles and selected source raster data defining surficial geology, sediment type and distribution, and physiographic zones of the sea floor from Nahant to Northern Cape Cod Bay. Much of the geophysical data used to create the interpretive layers were collected under a cooperative agreement among the Massachusetts Office of Coastal Zone Management (CZM), the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, the National Oceanic ...

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Hillshaded relief image derived from elevations of the Holocene transgressive unconformity beneath the Massachusetts inner continental shelf between Nahant and Northern Cape Cod Bay (Utelevhs GeoTIFF Image; UTM, Zone 19N, WGS 84)

These data are qualitatively derived interpretive polygon shapefiles and selected source raster data defining surficial geology, sediment type and distribution, and physiographic zones of the sea floor from Nahant to Northern Cape Cod Bay. Much of the geophysical data used to create the interpretive layers were collected under a cooperative agreement among the Massachusetts Office of Coastal Zone Management (CZM), the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, the National Oceanic ...

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Hillshaded-relief image produced from lead-line and single-beam sonar soundings, swath interferometric, multibeam, and lidar datasets (bb_navd88_hs_10m, Esri grid, UTM Zone 19N, WGS 84)

Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Buzzards Bay, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a result of a collaborative ...

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40-m Hillshaded relief image produced from elevation of the late-Wisconsinan regressive unconformity beneath Buzzards Bay, Massachusetts (GeoTIFF Image; UTM, Zone 19N, WGS 84)

Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Buzzards Bay, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a result of a collaborative ...

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NOS_5m_INT_HS.tif: 5-meter hillshaded-relief image produced from 23 multibeam hydrographic surveys collected off the Delmarva Peninsula by the National Oceanic and Atmospheric Administration's National Ocean Service between 2006 and 2011 (GeoTIFF, UTM Zone 18N, WGS 84)

Between 2006 and 2011 Science Applications International Corporation (SAIC), under contract by the National Oceanic and Atmospheric Administration's (NOAA) National Ocean Service (NOS), collected twenty-three hydrographic surveys totaling over 4100 square-kilometers of Reson multibeam bathymetric and Klein sidescan-sonar data for the purposes of updating nautical charts. Data extended from the entrance of Delaware Bay south to Parramore Island in water depths from about 3 to 35 meters below mean lower low ...

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10-m Hillshaded-relief image of Vineyard and western Nantucket Sounds produced from lead-line and single-beam sonar soundings, swath-interferometric, multibeam, and lidar datasets (TIFF image, UTM Zone 19N, WGS84)

Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Vineyard and Western Nantucket Sounds, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a ...

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Hillshaded-relief image produced from the late Wisconsinan to early Holocene regressive unconformity (Ur) beneath Vineyard and western Nantucket Sounds, Massachusetts (GeoTIFF Image; UTM, Zone 19N, WGS 84)

Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Vineyard and western Nantucket Sounds, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs, and surficial sediment samples. The interpretation of the seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a ...

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GeoTIFF image of the shaded-relief bathymetry of the sea floor, colored by backscatter intensity, of the Historic Area Remediation Site in 1996 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ...

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GeoTIFF image of the shaded-relief bathymetry of the Historic Area Remediation Site in 1996 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ...

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GeoTIFF image of the shaded-relief bathymetry of the sea floor, colored by backscatter intensity, of the Historic Area Remediation Site in 1998 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ...

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GeoTIFF image of the shaded-relief bathymetry of the Historic Area Remediation Site in 1998 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ...

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GeoTIFF image of the shaded-relief bathymetry of the sea floor, colored by backscatter intensity, of the Historic Area Remediation Site in 2000 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ...

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GeoTIFF image of the shaded-relief bathymetry of the Historic Area Remediation Site in 2000 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor of the Historic Area Remediation Site (HARS), offshore of New York and New Jersey, were carried out in 1996, 1998, and 2000 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The objective of the multiple echosounder surveys was to map the bathymetry and surficial sediments over time as dredged material was placed in the HARS to remediate contaminated sediments. Maps derived from the ...

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GeoTIFF image of shaded-relief bathymetry, colored by backscatter intensity, of the sea floor of the Hudson Shelf Valley (12-m resolution, Mercator, WGS 84)

The Hudson Shelf Valley is the submerged seaward extension of the ancestral Hudson River drainage system and is the largest physiographic feature on the Middle Atlantic continental shelf. The valley begins offshore of New York and New Jersey at about 30-meter (m) water depth, runs southerly and then southeasterly across the Continental Shelf, and terminates on the outer shelf at about 85-m water depth landward of the head of the Hudson Canyon. Portions of the 150-kilometer-long valley were surveyed in 1996, ...

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GeoTIFF image of shaded-relief bathymetry of the sea floor of the Hudson Shelf Valley (12-m resolution, Mercator, WGS 84)

The Hudson Shelf Valley is the submerged seaward extension of the ancestral Hudson River drainage system and is the largest physiographic feature on the Middle Atlantic continental shelf. The valley begins offshore of New York and New Jersey at about 30-meter (m) water depth, runs southerly and then southeasterly across the Continental Shelf, and terminates on the outer shelf at about 85-m water depth landward of the head of the Hudson Canyon. Portions of the 150-kilometer-long valley were surveyed in 1996, ...

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GeoTIFF image of shaded-relief bathymetry, colored by backscatter intensity, of the sea floor offshore of Fire Island Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ...

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GeoTIFF image of shaded-relief bathymetry of the sea floor offshore of Fire Island Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ...

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GeoTIFF image of shaded-relief bathymetry, colored by backscatter intensity, of the sea floor southwest of Montauk Point, New York, in 1998 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ...

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GeoTIFF image of shaded-relief bathymetry of the sea floor southwest of Montauk Point, New York, in 1998 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ...

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GeoTIFF image of shaded-relief bathymetry, colored by backscatter intensity, of the sea floor offshore of Moriches Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ...

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GeoTIFF image of shaded-relief bathymetry of the sea floor offshore of Moriches Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ...

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GeoTIFF image of shaded-relief bathymetry, colored by backscatter intensity, of the sea floor offshore of Shinnecock Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ...

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GeoTIFF image of shaded-relief bathymetry of the sea floor offshore of Shinnecock Inlet, New York, in 1998 (3-m resolution, Mercator, WGS 84)

Surveys of the bathymetry and backscatter intensity of the sea floor south of Long Island, New York, were carried out in November 1998 using a Simrad EM1000 multibeam echosounder mounted on the Canadian Coast Guard ship Frederick G. Creed. The purpose of the multibeam echosounder surveys was to explore the bathymetry and backscatter intensity of the sea floor in several areas off the southern coast of Long Island along the 20-meter isobath. Survey areas offshore of Fire Island Inlet, Moriches Inlet, ...

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Contours--Offshore Pigeon Point, California

This part of DS 781 presents data for the bathymetric contours for several seafloor maps of the Offshore Pigeon Point map area, California. The vector data file is included in "Contours_OffshorePigeonPoint.zip", which is accessible from https://doi.org/10.5066/F7513W80. These data accompany the pamphlet and map sheets of Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., ...

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Contours--Offshore Aptos, California

This part of DS 781 presents data for the bathymetric contours for the Offshore of Aptos map area, California. The vector data file is included in "Contours_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, ...

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Transgressive Contours--Pigeon Point to Monterey, California

This part of DS 781 presents data for the transgressive contours for the depth-to-transition map of the Pigeon Point to Monterey, California, map region. The vector file is included in T "TransgressiveContours_PigeonPointToMonterey.zip," which is accessible from https://doi.org/10.5066/F7N29V0Z. As part of the USGS's California State Waters Mapping Project, a 50-m grid of sediment thickness for the seafloor within the limit of California’s State Waters between Pigeon Point and southern Monterey Bay was ...

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Contours--Monterey Canyon and Vicinity, California

This part of DS 781 presents bathymetric contours for several seafloor maps of the Monterey Canyon and Vicinity map area, California. The shapefile is included in "Contours_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.G., Davenport, C.W. ...

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CNTR10M - 10 meter bathymetric contours of the Channel Islands National Marine Sanctuary and Santa Barbara Bay. (UTM 10N, NAD83)

Data layer containing 10 meter bathymetric contours for the Channel Islands National Marine Sanctuary and Santa Barbara Bay. Data are derived from 1:250,000-scale National Oceanic and Atmospheric Administration (NOAA) charts and Monterey Bay Aquarium Research Institute (MBARI), Santa Barbara Bay Multibeam Data

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Bathymetric contours of the continental margin offshore of Washington, Oregon, and California based on data available in the late 1980s.

Bathymetric contours (contour interval 100 m) of the continental margin offshore of Washington, Oregon, and California (cowbat) were compiled from various sources available in the late 1980s and used to construct 1:1,000,000-scale maps (Chase and others, 1992a, 1992b; Grim and others, 1992). The contours range from 200 to 5300 m depth.

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6-m resolution image of shaded relief multibeam bathymetry in western Massachusetts Bay map Quadrangle 1, pseudo-colored by backscatter intensity (Q1_BACKPC.TIF)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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6-m resolution gray-scale image of shaded-relief multibeam bathymetry in western Massachusetts Bay map Quadrangle 3 (Q3_SRELIEF.TIF)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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Grey Toned Surface Model Image from the 150 meter grid of the Puerto Rico Trench (gtsurfmod.tif)

The Puerto Rico Trench is a tectonic plate boundary where the North American Plate slides by and descends under the Caribbean Plate. Although much of the trench lies within the United States of America's Exclusive Economic Zone (EEZ), surprisingly few surveys have been conducted there during the past 25 years. This data set is a grey toned surface model mosaic derived from the 150 meter grid made from the multibeam bathymetric data collected during the U.S. Geological Survey (USGS) science cruise 03008 in ...

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Sun Illuminated Color Image of the 150 meter grid of the Puerto Rico Trench (SUNILLUM.TIF)

Geologic features in the Puerto Rico trench are remotely sensed, monitored, collected, studied, and analyzed. This data set was colorized by depth and converted to sun illuminated raster imagery; it was collected and processed during the U.S. Geological Survey science cruise 03008 in collaboration with National Oceanic and Atmospheric Administration Research Cruise RB0303 from 18 February to 7 March 2003, Leg II of III. (Leg I and III: 20020924 to 20020930 and 20030828 to 20030904, respectively).

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Image of the 4-m Sun-illuminated Topography of the Sea Floor off Eastern Cape Cod (CAPENORTHSUN_GEO4M_WGS84.TIF, Geographic, WGS84)

This data set includes sun-illuminated of the sea floor offshore of eastern Cape Cod, Massachusetts. The data were collected with a multibeam sea floor mapping system during USGS survey 98015, conducted November 9 - 25, 1998. The surveys were conducted using a Simrad EM 1000 multibeam echo sounder mounted aboard the Canadian Coast Guard vessel Frederick G. Creed. This multibeam system utilizes 60 electronically aimed receive beams spaced at intervals of 2.5 degrees that insonify a strip of sea floor up to 7 ...

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Image of the 4-m Sun-illuminated Topography of the Sea Floor off Eastern Cape Cod (CAPESOUTHSUN_GEO4M_WGS84.TIF, Geographic, WGS84)

This data set includes sun-illuminated of the sea floor offshore of eastern Cape Cod, Massachusetts. The data were collected with a multibeam sea floor mapping system during USGS survey 98015, conducted November 9 - 25, 1998. The surveys were conducted using a Simrad EM 1000 multibeam echo sounder mounted aboard the Canadian Coast Guard vessel Frederick G. Creed. This multibeam system utilizes 60 electronically aimed receive beams spaced at intervals of 2.5 degrees that insonify a strip of sea floor up ...

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Color-Encoded Image of 3-m Gridded Hill-Shaded Bathymetry From Long Island Sound off Branford, Connecticut (H11043_GEO_3MBATHY.TIF, Geographic)

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ...

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Color-Encoded Image of 3-m Gridded Hill-Shaded Bathymetry From Long Island Sound off Branford Connecticut (H11043_UTM18_3MBATHY.TIF, UTM)

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ...

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Color-Encoded Image of 5-m Gridded Hill-Shaded Bathymetry From Long Island Sound off Milford, Connecticut (H11044_GEO_5MBATHY.TIF, Geographic)

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ...

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Color-Encoded Image of 5-m Gridded Hill-Shaded Bathymetry From Long Island Sound off Milford Connecticut (H11044_UTM18_5MBATHY.TIF, UTM)

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ...

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Color-Encoded Image of 5-m Gridded Hill-Shaded Bathymetry From Long Island Sound off Bridgeport, Connecticut (H11045_GEO_5MBATHY.TIF, Geographic)

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ...

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Color-Encoded Image of 5-m Gridded Hill-Shaded Bathymetry From Long Island Sound off Bridgeport, Connecticut (H11045_UTM18_5MBATHY.TIF, UTM)

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ...

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Color Shaded-Relief Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11255 in Long Island Sound (H11255_GEO_2MBATHY.TIF, Geographic)

Digital terrain models (DTMs) produced from multibeam bathymetric data provide valuable base maps for marine geological interpretations. These maps help define the geological variability of the seafloor (one of the primary controls of benthic habitat diversity); improve our understanding of the processes that control the distribution and transport of bottom sediments, and the distribution of benthic habitats and associated infaunal community structures; and provide a detailed framework for future research, ...

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Color Shaded-Relief GeoTIFF Image Showing the 1-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11076 in Quicks Hole, Elizabeth Islands, MA (H11076_GEO_1MMBES.TIF, Geographic)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Massachusetts Office of Coastal Zone Management (MA CZM), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of the Massachusetts coastline, show the composition and terrain of the seabed, and provide information on sediment ...

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Color Hill-Shaded GeoTIFF Image Showing the 2-m bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11250 in Eastern Long Island Sound (H11250_GEO_2MMBES.TIF, Geographic)

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ...

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Color Shaded-Relief GeoTIFF Image Showing the 3-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11079 in Great Round Shoal Channel, Offshore Massachusetts (H11079_3MUTM19_MB.TIF, UTM Zone 19)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Massachusetts Office of Coastal Zone Management (MA CZM), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of the Massachusetts coastline, show the composition and terrain of the seabed, and provide information on sediment ...

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Grayscale Shaded-Relief GeoTIFF Image Showing the 3-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11079 in Great Round Shoal Channel, Offshore Massachusetts (H11079_UTM_GSHS.TIF, UTM Zone 19)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Massachusetts Office of Coastal Zone Management (MA CZM), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of the Massachusetts coastline, show the composition and terrain of the seabed, and provide information on sediment ...

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3-m Hill-Shaded Bathymetric Grid of National Oceanic and Atmospheric Administration (NOAA) Survey H11079 of Great Round Shoal Channel (H11079_UTM_HS, UTM Zone 19)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Massachusetts Office of Coastal Zone Management (MA CZM), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of the Massachusetts coastline, show the composition and terrain of the seabed, and provide information on sediment ...

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4-m Hill-Shaded Bathymetric GeoTIFF Image of National Oceanic and Atmospheric Administration (NOAA) Survey H11320 in UTM Zone 19 (H11320_UTM_4M.TIF)

The United States Geological Survey (USGS) is working cooperatively with the National Oceanic and Atmospheric Administration (NOAA) to interpret the surficial geology in estuaries along the coast of the northeastern United States. The purpose of our present study is to define the sea floor morphology and sedimentary environments in an area of Rhode Island Sound using sidescan sonar imagery, multibeam bathymetry, and seismic records. The mosaic, bathymetry, and their interpretations serve many purposes, ...

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Color Hill-Shaded GeoTIFF Image Showing the 2-m bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11252 in Eastern Long Island Sound (H11252_2MUTM18_MB.TIF, UTM Zone 18)

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ...

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Color Hill-Shaded GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11361 in Eastern Long Island Sound (H11361_2MUTM18_MB.TIF, UTM Zone 18)

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ...

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Color Hill-Shaded GeoTIFF Image Showing the Composite 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Surveys H11252 and H11361 in Eastern Long Island Sound (SMR_COMP_2MUTM.TIF, UTM, Zone 18)

The U.S. Geological Survey, in cooperation with the National Oceanic and Atmospheric Administration and the Connecticut Department of Environmental Protection, has produced detailed geologic maps of the sea floor in Long Island Sound, a major East Coast estuary surrounded by the most densely populated region of the United States. These studies have built upon cooperative research with the State of Connecticut that was initiated in 1982. The current phase of this research program is directed toward studies ...

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Color GeoTIFF of the Bathymetry of National Oceanic and Atmospheric Administration (NOAA) Survey H11321 in Central Rhode Island Sound (H11321_GEO.TIF. Geographic)

The United States Geological Survey (USGS) is working cooperatively with the National Oceanic and Atmospheric Administration (NOAA) to interpret the surficial geology in estuaries along the coast of the northeastern United States. The purpose of our present study is to define the sea floor morphology and sedimentary environments in an area of central Rhode Island Sound using sidescan-sonar imagery, bathymetry data, and seismic records. The mosaic, bathymetry, and their interpretations serve many purposes, ...

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Grayscale GeoTIFF Image of the Bathymetry of National Oceanic and Atmospheric Administration (NOAA) Survey H11321 in Central Rhode Island Sound (H11321_UTM.TIF, UTM Zone 19)

The United States Geological Survey (USGS) is working cooperatively with the National Oceanic and Atmospheric Administration (NOAA) to interpret the surficial geology in estuaries along the coast of the northeastern United States. The purpose of our present study is to define the sea floor morphology and sedimentary environments in an area of central Rhode Island Sound using sidescan-sonar imagery, bathymetry data, and seismic records. The mosaic, bathymetry, and their interpretations serve many purposes, ...

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Color GeoTIFF Image of the 10-m Interpolated Bathymetric Grid of the Northern Part of National Oceanic and Atmospheric Administration (NOAA) Survey H11044 off Milford, Connecticut (H11044N_MB10M_UTM18.TIF, UTM Zone 18, WGS84)

During 2001 the NOAA Ship RUDE completed charting survey H11044 that covered a roughly 293 km2 area of the sea floor in north-central Long Island Sound, off Milford Connecticut. Although 100 percent coverage was achieved with sidescan sonar for charting purposes, only reconnaissance (spaced line) bathymetry was acquired with shallow-water multibeam and single-beam systems. Therefore, further processing was conducted at the USGS's Woods Hole Science Center to provide bathymetric datasets with more continuous ...

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Color Shaded-Relief GeoTIFF Image Showing the 25-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11346 in the vicinity of Edgartown Harbor, MA (H11346_MB25M_UTM19.TIF, UTM Zone 19, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Massachusetts Office of Coastal Zone Management (MA CZM), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of the Massachusetts coastline, shows the composition and terrain of the seabed, and provides information on sediment ...

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Color Shaded-Relief GeoTIFF Image Showing the Combined 4-m Multibeam and LIDAR Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Surveys H11442 and H11225 Offshore of Niantic, CT (NIANTIC_MBLIDAR_GEO.TIF, Geographic, WGS84)

Nearshore areas within Long Island Sound are of great interest to the Connecticut and New York research and management communities because of their ecological, recreational, and commercial importance. However, although advances in multibeam echosounder technology permit the construction of detailed digital terrain models of seafloor topography within deeper waters, limitations inherent with collecting multibeam data make using this technology in shallower waters (<10-m deep) more difficult and expensive. ...

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Color Shaded-Relief GeoTIFF Image Showing the Combined 4-m Multibeam and LIDAR Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Surveys H11441 and H11224 Offshore of New London, CT (NLONDON_MBLIDAR_GEO.TIF, Geographic, WGS84)

Nearshore areas within Long Island Sound are of great interest to the Connecticut and New York research and management communities because of their ecological, recreational, and commercial importance. However, although advances in multibeam echosounder technology permit the construction of detailed digital terrain models of seafloor topography within deeper waters, limitations inherent with collecting multibeam data make using this technology in shallower waters (<10-m deep) more difficult and expensive. ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11445 North of Plum Island, New York (H11445_MB2M_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the Connecticut Department of Environmental Protection and National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of Long Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11445 North of Plum Island, New York (H11445_MB2M_UTM.TIF, UTM Zone 18, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the Connecticut Department of Environmental Protection and National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of Long Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11251 Offshore of Rocky Point, New York (H11251_2MMB_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry and sidescan-sonar imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities in Long Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. During October 2008 NOAA ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11251 Offshore of Rocky Point, New York (H11251_2MMB_UTM18.TIF, UTM Zone 18, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry and sidescan-sonar imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities in Long Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. During October 2008 NOAA ...

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Color-shaded relief GeoTIFF image of interferometric sonar data collected by the USGS within Red Brook Harbor, MA, 2009 (RB_BathyShadedRelief_1m, 1-meter cell size)

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine resources, and ...

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Color-shaded relief GeoTIFF image of interferometric sonar data collected by the USGS within Red Brook Harbor, MA, 2009 (RB_BathyShadedRelief_5m, 5-meter cell size)

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine resources, and ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11446 North of Orient Point, New York (H11446_MB2M_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the Connecticut Department of Environmental Protection and National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of Long Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11446 North of Orient Point, New York (H11446_MB2M_UTM.TIF, UTM Zone 18, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the Connecticut Department of Environmental Protection and National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of Long Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11997 Offshore in Eastern Long Island Sound (H11997_2MMB_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry and sidescan-sonar imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities in Long Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. During October 2008 NOAA ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11997 Offshore in Eastern Long Island Sound (H11997_2MMB_UTM18.TIF, UTM Zone 18, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry and sidescan-sonar imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities in Long Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. During October 2008 NOAA ...

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Color Shaded-Relief GeoTIFF Image Showing the Combined 4-m Multibeam and LIDAR Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Surveys H11224, H11225, H11250, H11251, H11252, H11361, H11441, H11442, H11445, H11446, H11997, H11999, H12012, and H12013 offshore in eastern Long Island Sound and westernmost Block Island Sound (ELISCOMB_4MBAT_GEO.TIF, Geographic, WGS84)

The USGS, in cooperation with NOAA and the Connecticut DEP, is producing detailed maps of the seafloor in Long Island Sound. The current phase of this cooperative research program is directed toward analyzing how bathymetric relief relates to the distribution of sedimentary environments and benthic communities. As part of this program, digital terrain models (DTMs) from bathymetry collected as part of NOAA's hydrographic charting activities are converted into ESRI raster grids and imagery (primarily of 2-m ...

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Color Shaded-Relief GeoTIFF Image Showing the Combined 4-m Multibeam and LIDAR Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Surveys H11224, H11225, H11250, H11251, H11252, H11361, H11441, H11442, H11445, H11446, H11997, H11999, H12012, and H12013 Offshore in Eastern Long Island Sound and Westernmost Block Island Sound (ELISCOMB_4MBAT_UTM18.TIF, UTM Zone 18, NAD83)

The USGS, in cooperation with NOAA and the Connecticut DEP, is producing detailed maps of the seafloor in Long Island Sound. The current phase of this cooperative research program is directed toward analyzing how bathymetric relief relates to the distribution of sedimentary environments and benthic communities. As part of this program, digital terrain models (DTMs) from bathymetry collected as part of NOAA's hydrographic charting activities are converted into ESRI raster grids and imagery (primarily of 2-m ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11922 in Rhode Island Sound (H11922_2MMB_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities off southern New England, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. During July-August 2008 NOAA completed hydrographic ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11922 in Rhode Island Sound (H11922_2MMB_UTM19.TIF, UTM Zone 19, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities off southern New England, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. During July-August 2008 NOAA completed hydrographic ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11996 in Rhode Island Sound (H11996_MB2M_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of Rhode Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. Interpretations were derived from the ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11996 in Rhode Island Sound (H11996_MB2M_UTM.TIF, UTM Zone 19, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of Rhode Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. Interpretations were derived from the ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11999 North of Duck Pond Point, New York (H11999_MB2M_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the Connecticut Department of Environmental Protection and National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of Long Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11999 North of Duck Pond Point, New York (H11999_MB2M_UTM.TIF, UTM Zone 18, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the Connecticut Department of Environmental Protection and National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Imagery, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of Long Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic ...

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Color Shaded-Relief GeoTIFF Image Showing the 1-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12007 in the Vicinity of Cross Rip Channel, Nantucket Sound (H12007_1MMB_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities off southern New England, shows the character and terrain of the seabed, and provides information on sediment transport and benthic habitat. During April-May 2009 NOAA completed hydrographic survey ...

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Color Shaded-Relief GeoTIFF Image Showing the 1-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12007 in the Vicinity of Cross Rip Channel, Nantucket Sound (H12007_1MMB_UTM19.TIF, UTM Zone 19, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities off southern New England, shows the character and terrain of the seabed, and provides information on sediment transport and benthic habitat. During April-May 2009 NOAA completed hydrographic survey ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11995 in Rhode Island Sound (H11995_MB2M_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of Rhode Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. Interpretations were derived from the ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H11995 in Rhode Island Sound (H11995_MB2M_UTM.TIF, UTM Zone 19, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities along this part of Rhode Island Sound, shows the composition and terrain of the seabed, and provides information on sediment transport and benthic habitat. Interpretations were derived from the ...

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Color Shaded-Relief GeoTIFF Image Showing the Combined 4-m Multibeam Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Surveys H12009, H12010, H12011, H12015, H12033, H12137, and H12139 Offshore in Block Island Sound (BISOUND_4MMB_GEO.TIF, Geographic, WGS84)

The USGS, in cooperation with NOAA, is producing detailed maps of the seafloor off southern New England. The current phase of this cooperative research program is directed toward analyzing how bathymetric relief relates to the distribution of sedimentary environments and benthic communities. As part of this program, digital terrain models (DTMs) from bathymetry collected as part of NOAA's hydrographic charting activities are converted into ESRI raster grids and imagery, verified with bottom sampling and ...

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Color Shaded-Relief GeoTIFF Image Showing the Combined 4-m Multibeam Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Surveys H12009, H12010, H12011, H12015, H12033, H12137, and H12139 Offshore in Block Island Sound (BISOUND_4MMB_UTM19.TIF, UTM Zone 19, NAD83)

The USGS, in cooperation with NOAA, is producing detailed maps of the seafloor off southern New England. The current phase of this cooperative research program is directed toward analyzing how bathymetric relief relates to the distribution of sedimentary environments and benthic communities. As part of this program, digital terrain models (DTMs) from bathymetry collected as part of NOAA's hydrographic charting activities are converted into ESRI raster grids and imagery, verified with bottom sampling and ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12013 Off the Entrance to the Connecticut River in Northeastern Long Island Sound (H12013_2M_UTM18.TIF, UTM Zone 18, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Connecticut Department of Energy and Environmental Protection (CT DEEP), is producing detailed geologic maps of the coastal sea floor. Bathymetry and sidescan-sonar imagery, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities in Long Island Sound, shows the composition and terrain of the seabed, and provides ...

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Color Shaded-Relief GeoTIFF Image Showing the Combined 2-m and Interpolated 10-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12013 Off the Entrance to the Connecticut River in Northeastern Long Island Sound (H12013_INT2M_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Connecticut Department of Energy and Environmental Protection (CT DEEP), is producing detailed geologic maps of the coastal sea floor. Bathymetry and sidescan-sonar imagery, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities in Long Island Sound, shows the composition and terrain of the seabed, and provides ...

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Color Shaded-Relief GeoTIFF Image Showing the Combined 2-m and Interpolated 10-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12013 Off the Entrance to the Connecticut River in Northeastern Long Island Sound (H12013_INT2M_UTM18.TIF, UTM Zone 18, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Connecticut Department of Energy and Environmental Protection (CT DEEP), is producing detailed geologic maps of the coastal sea floor. Bathymetry and sidescan-sonar imagery, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities in Long Island Sound, shows the composition and terrain of the seabed, and provides ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12023 in Block Island Sound (H12023_MB2M_GEO.TIF, Geographic, WGS84)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetric and sidescan-sonar data, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of Block Island Sound, show the composition and terrain of the seabed, and provide information on sediment transport and benthic habitat. During June 2012, ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12023 in Block Island Sound (H12023_MB2M_UTM.TIF, UTM Zone 19, NAD83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetric and sidescan-sonar data, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of Block Island Sound, show the composition and terrain of the seabed, and provide information on sediment transport and benthic habitat. During June 2012, ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12012 Offshore in Northeastern Long Island Sound (UTM Zone 18, NAD83, H12012_2MMB_UTM18.TIF)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and the Connecticut Department of Energy and Environmental Protection (CT DEEP), has produced detailed geologic maps of the coastal sea floor. Bathymetry, originally collected by NOAA for charting purposes, provides a fundamental framework for research and management activities in Long Island Sound, shows the terrain of the seabed, and provides information on sediment transport and benthic ...

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Color Shaded-Relief GeoTIFF Image Showing the Combined 4-m Multibeam Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Surveys H11922, H11995, H11996, H12009, H12010, H12011, H12015, H12023, H12033, H12137, H12139, H12296, H12298, and H12299 Offshore in Rhode Island and Block Island Sounds (RICOMB_4MMB_GEO.TIF, Geographic, WGS 84)

Detailed bathymetric maps of the sea floor in Block Island and Rhode Island Sounds are of great interest to the New York, Rhode Island, and Massachusetts research and management communities because of this area's ecological, recreational, and commercial importance. Geologically interpreted digital terrain models (DTMs) from individual surveys provide important benthic environmental information, yet many applications require a geographically broader perspective. For example, individual surveys are of limited ...

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Color Shaded-Relief GeoTIFF Image Showing the Combined 4-m Multibeam Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Surveys H11922, H11995, H11996, H12009, H12010, H12011, H12015, H12023, H12033, H12137, H12139, H12296, H12298, and H12299 Offshore in Rhode Island and Block Island Sounds (RICOMB_4MMB_UTM19.TIF, UTM Zone 19, NAD 83)

Detailed bathymetric maps of the sea floor in Block Island and Rhode Island Sounds are of great interest to the New York, Rhode Island, and Massachusetts research and management communities because of this area's ecological, recreational, and commercial importance. Geologically interpreted digital terrain models (DTMs) from individual surveys provide important benthic environmental information, yet many applications require a geographically broader perspective. For example, individual surveys are of limited ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12296 in Block Island Sound (H12296_MB2M_GEO.TIF, Geographic, WGS 84)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetric and sidescan-sonar data, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of Block Island Sound, show the composition and terrain of the seabed, and provide information on sediment transport and benthic habitat. During June 2012, ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12296 in Block Island Sound (H12296_MB2M_UTM.TIF, UTM Zone 19, NAD 83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetric and sidescan-sonar data, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of Block Island Sound, show the composition and terrain of the seabed, and provide information on sediment transport and benthic habitat. During June 2012, ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12299 in Block Island Sound (UTM Zone 19, NAD 83, H12299_MB2M_UTM.TIF)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetric data, originally collected by NOAA for charting purposes, provide a fundamental framework for research and management activities along this part of Block Island Sound, show the composition and terrain of the seabed, and provide information on sediment transport and benthic habitat. During June 2013, bottom photographs and ...

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Color Shaded-Relief GeoTIFF Image Showing the 2-m Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12298 in Block Island Sound (UTM Zone 19, NAD 83, H12298_MB2M_UTM.TIF)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetric and sidescan-sonar data, originally collected by NOAA for charting purposes, provide a framework for research and management activities along western Block Island Sound, show the composition and terrain of the seabed, and provide information on sediment transport and benthic habitat. During June 2013, bottom photographs ...

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Color Shaded-Relief GeoTIFF Image Showing the Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Survey H12324 in Narragansett Bay (UTM Zone 19, NAD 83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration (NOAA), is producing detailed geologic maps of the coastal sea floor. Bathymetric data, originally collected by NOAA for charting purposes, provide a framework for research and management activities along southern Narragansett Bay, show the composition and terrain of the seabed, and provide information on sediment transport and benthic habitat. During September 2014, bottom photographs and surficial ...

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Post-Hurricane Florence Digital Elevation Models of coastal North Carolina

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 ...

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Post-Hurricane Florence RGB averaged orthoimagery of coastal North Carolina

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 ...

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Orthoimagery of Eastern Dry Rocks coral reef, Florida, 2021

A seabed orthoimage was developed from underwater images collected at Eastern Dry Rocks coral reef near Key West, Florida, in May 2021 using the SQUID-5 camera system. The underwater images were processed using Structure-from-Motion (SfM) photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 800x160 meters (0.12 square kilometers) in size, and it was created using image-mosaicking methods and saved as a tiled, 5-mm resolution raster.

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Bathymetric digital elevation model (DEM) of Eastern Dry Rocks coral reef, Florida, 2021

A digital elevation model (DEM) was created from underwater images collected at Eastern Dry Rocks coral reef near Key West, Florida, in May 2021 using the SQUID-5 camera system. The underwater images were processed using Structure-from-Motion (SfM) photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was derived in Metashape (ver. 1.6.5) from the point cloud, but it excludes the 'low noise' class. The DEM covers a rectangular area of seafloor ...

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GNSS locations of seabed images collected at Eastern Dry Rocks coral reef, Florida, 2021

This text file (SQUID5_EDR_2021_Image_Locations.txt) provides the GNSS antenna location for underwater images collected at Eastern Dry Rocks coral reef, near Key West, Florida, in May 2021, using the SQUID5 Structure-from-Motion (SfM) system, a towed-surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey. The GNSS antenna location for the time of each image capture is presented with greater precision than is stored in the individual image's EXIF header due to ...

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Point cloud data of Eastern Dry Rocks coral reef, Florida, 2021

A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Eastern Dry Rocks coral reef near Key West, Florida, in May 2021 using the SQUID-5 camera system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, RGB colors, Metashape-computed confidence values, and a two-class classification ('unclassified' and 'low noise') derived from the confidence values. LAS (and its compressed form, LAZ) is an open format ...

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Overlapping seabed images collected at Eastern Dry Rocks coral reef, Florida, 2021

Underwater images totaling 138,733 in number were collected at Eastern Dry Rocks coral reef, near Key West, Florida, in May 2021, using the SQUID5 Structure-from-Motion (SfM) system, a towed-surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey. The images are organized in zipped files grouped by survey line. The SQUID-5 records images as TIFF (.tif) format to maintain the highest resolution and bit depth. Each image includes EXIF metadata, containing GNSS ...

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Digital surface model representing Head of the Meadow Beach, Truro on March 10, 2022

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 ...

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Orthomosaic representing Head of the Meadow Beach, Truro on March 10, 2022

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 ...

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Digital elevation model (DEM) of Looe Key, Florida, 2021

A digital elevation model (DEM) was created from underwater images collected at Looe Key, Florida, in July 2021 using the SQUID-5 camera system. The underwater images were processed using Structure-from-Motion (SfM) photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.6.6) from the point cloud, and includes points from both classes. The DEM covers a rectangular area of seafloor approximately 720x100 meters (0.072 ...

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GNSS locations of seabed images collected at Looe Key, Florida, 2021

The text file "SQUID5_LKR_2021_Image_Locations.txt" provides the GNSS antenna location for underwater images collected at Looe Key, Florida, in July 2021, using the SQUID5 Structure-from-Motion (SfM) system, a towed-surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey. The GNSS antenna location for the time of each image capture is presented with greater precision than is stored in the individual image EXIF headers due to decimal place limitations of the EXIF ...

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Orthoimagery of Looe Key, Florida, 2021

A seabed orthoimage was developed from underwater images collected at Looe Key, Florida, in July 2021 using the SQUID-5 camera system. The underwater images were processed using Structure-from-Motion (SfM) photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 720x100 meters (0.072 square kilometers) in size. It was created using image-mosaicking methods and saved as a tiled GeoTIFF raster at 5-millimeter resolution.

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Point cloud data of Looe Key, Florida, 2021

A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Looe Key, Florida, in July 2021 using the SQUID-5 camera system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, and RGB colors derived from the color-corrected imagery. LAS (and its compressed form, LAZ) is an open format developed for the efficient use of point cloud lidar data.

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Overlapping seabed images collected at Looe Key, Florida, 2021

A total of 94,567 underwater images were collected at Looe Key, Florida, in July 2021, using the SQUID5 Structure-from-Motion (SfM) system, a towed-surface vehicle with five downward-looking underwater cameras developed by the U.S. Geological Survey. The images are organized in zipped files grouped by survey line. The SQUID-5 records images in the Tagged Image File Format format to maintain the highest resolution and bit depth. Each image includes Exchangeable Image File (EXIF) metadata, containing Global ...

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Digital surface model representing Marconi Beach, Wellfleet on March 11, 2022

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 ...

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Orthomosaic representing Marconi Beach, Wellfleet, MA March 11, 2022

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 ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2019-08-30 to 2019-09-02, Pre-Hurricane Dorian

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 ...

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RGB-averaged orthoimagery of coastal North Carolina, from 2019-08-30 to 2019-09-02, Pre-Hurricane Dorian

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 ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian

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 ...

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RGB-averaged orthoimagery of coastal North Carolina, from 2019-09-08 to 2019-09-13, Post-Hurricane Dorian

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 ...

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RGB-averaged orthoimagery of coastal North Carolina, on 2019-10-11, one-month post-Hurricane Dorian

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 ...

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Digital elevation models (DEMs) of coastal North Carolina, on 2019-11-26, two-months Post-Hurricane Dorian

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 ...

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RGB-averaged orthoimagery of coastal North Carolina, on 2019-11-26, two-months Post-Hurricane Dorian

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 ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2020-02-08 to 2020-02-09

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 ...

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RGB-averaged orthoimagery of coastal North Carolina, from 2020-02-08 to 2020-02-09

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 ...

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Digital elevation models (DEMs) of coastal North Carolina, from 2020-05-08 to 2020-05-09

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 ...

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Digital elevation models of the coast of Alaska from Icy Cape to Cape Prince of Wales, 2016

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 ...

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Orthoimagery of the coast of Alaska from Icy Cape to Cape Prince of Wales, 2016

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 ...

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Elevation point clouds of the coast of Alaska from Icy Cape to Cape Prince of Wales, 2016

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 ...

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Tile index for Alaska coastal orthoimagery and elevation data: Icy Cape to Cape Prince of Wales, 2016

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 ...

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Digital surface model (DSM) and digital elevation model (DEM) of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01

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 ...

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Ground control point locations for the UAS survey of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01

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 ...

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Orthomosaic imagery of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01

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. ...

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Topographic point cloud of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01

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, ...

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High resolution structure from motion digital surface models representing three sites on North Core Banks, NC in October 2022

These data map in high detail surficial cross-sections of North Core Banks, a barrier island in Cape Lookout National Seashore, NC, in October 2022. U.S. Geological Survey field efforts are part of an interagency agreement with the National Park Service to monitor the recovery of the island from Hurricanes Florence (2018) and Dorian (2019). Three sites of outwash, overwash, and pond formation were targeted for extensive vegetation ground-truthing, sediment samples, bathymetric mapping with a remote ...

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Digital elevation models (DEMs) of coastal North Carolina, on 2019-10-11, one month Post-Hurricane Dorian

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 ...

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Digital Surface Models (DSMs) of the Whale's Tail Marsh region, South San Francisco Bay, CA

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. ...

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Orthomosaic images of the Whale's Tail Marsh region, South San Francisco Bay, CA

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 ...

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Bathymetric digital elevation model (DEM) of Lake Tahoe near Dollar Point

Underwater images collected near Dollar Point in Lake Tahoe, California, were processed using Structure-from-Motion (SfM) photogrammetry techniques into a classified 3D point cloud. The DEM was derived in Metashape (ver. 1.6.4) from the point cloud, but it excludes the 'high noise' class. The DEM data were output as a geoTIFF raster at 25-mm resolution.

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Orthoimagery of Lake Tahoe near Dollar Point

Lakebed orthoimagery was developed from underwater images collected near Dollar Point in Lake Tahoe, California, and processed using Structure-from-Motion (SfM) photogrammetry techniques. The orthoimages were developed using both image-mosaic and image-averaging methods, which were then output as 5-mm resolution rasters. In general, the "Mosaic" product is somewhat sharper in resolution but will include some distinct seam lines and noticeable differences in image quality across the image. The "Average" ...

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Digital Surface Model representing Marconi Beach, Wellfleet, MA on March 22, 2023

The data in this release re-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 ...

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Orthomosaic representing Marconi Beach, Wellfleet, MA on March 22, 2023

The data in this release re-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 ...

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Digital Surface Model representing Head of the Meadow Beach, Truro, MA on March 10, 2023

The data in this release re-map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide updated environmental context for the 2020 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2022-015-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-01, which are two video cameras aimed ...

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Orthomosaic representing Head of the Meadow Beach, Truro, MA on March 10, 2023

The data in this release re-map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide updated environmental context for the 2020 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2022-015-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-01, which are two video cameras aimed ...

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Orthomosaic representing Head of the Meadow Beach, Truro from images collected during field activity 2021-014-FA on February 4, 2021

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 ...

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Orthomosaic representing Marconi Beach, Wellfleet from images acquired during field activity 2021-022-FA on March 17, 2021

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 ...

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Low-altitude aerial imagery collected from a Helikite at Marconi Beach, Wellfleet, MA on March 22, 2023

The data in this release re-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 ...

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RGB-averaged orthoimagery of coastal North Carolina, from 2020-05-08 to 2020-05-09

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 ...

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

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

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

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

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

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

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

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

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Digital elevation model (DEM) of Big Pine Ledge, Florida, 2021

A digital elevation model (DEM) was created from underwater images collected at Big Pine Ledge, Florida, in July 2021 using the SQUID-5 camera system. The underwater images were processed using Structure-from-Motion (SfM) photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.6.6) from the point cloud, and includes points from both classes. The DEM covers a rectangular area of seafloor approximately 650x120 meters (0 ...

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Orthoimagery of Big Pine Ledge, Florida, 2021

A seabed orthoimage was developed from underwater images collected at Big Pine Ledge, Florida, in July 2021 using the SQUID-5 camera system. The underwater images were processed using Structure-from-Motion (SfM) photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 650x120 meters (0.078 square kilometers) in size. It was created using image-averaging methods and saved as a tiled GeoTIFF raster at 5-millimeter resolution.

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Point cloud data of Big Pine Ledge, Florida, 2021

A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Big Pine Ledge, Florida, in July 2021 using the SQUID-5 camera system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, and RGB colors derived from the color-corrected imagery. LAS (and its compressed form, LAZ) is an open format developed for the efficient use of point cloud lidar data.

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Point cloud data of Lake Tahoe near Dollar Point

Three-dimensional point clouds (LAZ format) were developed from underwater images collected near Dollar Point in Lake Tahoe, California, and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, RGB colors, Metashape-computed confidence values, and a two-class classification ('unclassified' and 'high noise') derived from the confidence values. LAZ is an open format developed for the efficient use of point cloud lidar data. A description of the LAZ ...

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SfM digital surface model and orthomosaic representing Head of the Meadow Beach, Truro, MA on March 20, 2024

The data in this release re-map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide updated environmental context for the 2020 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is 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-01, which are two video cameras aimed at the beach. In February and March 2024, U.S. ...

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Town Neck Beach, Massachusetts, 10 cm 2016-2017 Digital Elevation Models

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 ...

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Town Neck Beach, Massachusetts, 5 cm 2016-2017 Orthomosaics

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 ...

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Low-altitude aerial imagery collected from a Helikite at Marconi Beach, Wellfleet, MA on March 22, 2024

The data in this release re-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 2024-016-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 two video cameras aimed at the beach (CoastCam CACO-02). In ...

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Structure from motion GCPs, digital surface model, and orthomosaic representing Marconi Beach, Wellfleet, MA on March 22, 2024

The data in this release re-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 2024-016-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 two video cameras aimed at the beach (CoastCam CACO-02). In ...

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Digital elevation model (DEM) of Big Pine Ledge, Florida, 2022

A digital elevation model (DEM) was created from underwater images collected at Big Pine Ledge (BPL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.8.5) from the point cloud and includes points from both classes. The DEM covers a ...

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Orthoimagery of Big Pine Ledge, Florida, 2022

A seabed orthoimage was developed from underwater images collected at Big Pine Ledge (BPL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 800x160 meters (m) (0.12 square kilometers [km]) in size. It was created using image-averaging methods and saved as a tiled Geographic Tagged Image ...

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Orthomosaic of Big Pine Ledge, Florida, 2022

A seabed orthoimage was developed from underwater images collected at Big Pine Ledge (BPL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 800x160 meters (m) (0.12 square kilometers [km]) in size. It was created using image-mosaicking methods and saved as a tiled Geographic Tagged ...

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Point cloud data of Big Pine Ledge, Florida, 2022

A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Big Pine Ledge (BPL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, and RGB colors derived from the color-corrected imagery. LIDAR Aerial Survey files (LAS) – and its compressed form, LAZ – is an open format ...

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Digital Elevation Model (DEM) of Summerland Ledge, Florida, 2022

A digital elevation model (DEM) was created from underwater images collected at Summerland Ledge (SL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.6.6) from the point cloud and includes points from both classes. The DEM covers a ...

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Orthoimagery of Summerland Ledge, Florida, 2022

A seabed orthoimage was developed from underwater images collected at Summerland Ledge (SL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 450x180 meters (m) (0.081 square kilometers [km]) in size. It was created using image-averaging methods and saved as a Geographic Tagged Image ...

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Orthomosaic of Summerland Ledge, Florida, 2022

A seabed orthoimage was developed from underwater images collected at Summerland Ledge (SL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 450x180 meters (m) (0.081 square kilometers [km]) in size. It was created using image-mosaicing methods and saved as a Geographic Tagged Image ...

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Point cloud data of Summerland Ledge, Florida, 2022

A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Summerland Ledge (SL), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, and RGB colors derived from the color-corrected imagery. LIDAR Aerial Survey files (LAS) - and its compressed form, LAZ - is an open format ...

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High Resolution Digital Elevation Model (DEM) of Looe Key, Florida, 2022

A digital elevation model (DEM) was created from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.6.6) from the point cloud and includes points from both classes. The DEM covers a rectangular ...

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Quicklook Digital Elevation Model (DEM) of Looe Key, Florida, 2022

A digital elevation model (DEM) was created from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques into a classified two-class ('unclassified' and 'low noise') 3D point cloud. The DEM was created in Metashape (ver. 1.6.6) from the point cloud and includes points from both classes. The DEM covers a rectangular ...

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Orthoimagery of Looe Key, Florida, 2022

A seabed orthoimage was developed from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 850x160 meters (m) (0.13 square kilometers [km]) in size. It was created using image-averaging methods and saved as Geographic Tagged Image File Format ...

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Quicklook Orthoimage of Looe Key, Florida, 2022

A seabed orthoimage was developed from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 850x160 meters (m) (0.13 square kilometers [km]) in size. This "quicklook" version of the dataset was created using image-averaging methods and saved as ...

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Orthomosaic of Looe Key, Florida, 2022

A seabed orthoimage was developed from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. The underwater images were processed using SfM photogrammetry techniques. The orthoimage covers a rectangular area of seafloor approximately 850x160 meters (m) (0.13 square kilometers [km]) in size. It was created using image-mosaicking methods and saved as Geographic Tagged Image File Format ...

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Point cloud data of Looe Key, Florida, 2022

A three-dimensional point cloud (LAZ format) was developed from underwater images collected at Looe Key (LKR), Florida, in July 2022 using the SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system and processed using Structure-from-Motion (SfM) photogrammetry techniques. Point cloud data include x,y,z positions, and RGB colors derived from the color-corrected imagery. LIDAR Aerial Survey files (LAS) - and its compressed form, LAZ - is an open format developed for ...

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Digital surface models representing Nauset Light Beach, Eastham, MA on September 14 and 20, 2023, pre and post Hurricane Lee

The data in this release map Marconi Beach, Head of the Meadow Beach, and Nauset Light Beach, in Cape Cod National Seashore (CACO), Massachusetts, before and after Hurricane Lee in September 2023. U.S Geological Survey personnel conducted field surveys to collect topographic data using global navigation satellite systems (GNSS) at all three beaches. In addition, at Nauset Light Beach, an uncrewed aerial system (UAS) was used to collect images with a Ricoh GRII camera for use in structure from motion ...

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Orthomosaics representing Nauset Light Beach, Eastham, MA on September 14 and 20, 2023, pre and post Hurricane Lee

The data in this release map Marconi Beach, Head of the Meadow Beach, and Nauset Light Beach, in Cape Cod National Seashore (CACO), Massachusetts, before and after Hurricane Lee in September 2023. U.S Geological Survey personnel conducted field surveys to collect topographic data using global navigation satellite systems (GNSS) at all three beaches. In addition, at Nauset Light Beach, an uncrewed aerial system (UAS) was used to collect images with a Ricoh GRII camera for use in structure from motion ...

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Time Series of Structure-from-Motion Products - Point Clouds: Little Dauphin Island and Pelican Island, Alabama, September 2018 to April 2019

Aerial imagery acquired with a small unmanned aircraft system (sUAS), in conjunction with surveyed ground control points (GCP) visible in the imagery, can be processed with structure-from-motion (SfM) photogrammetry techniques to produce high-resolution orthomosaics, three-dimensional (3D) point clouds and digital elevation models (DEMs). This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides UAS survey data products consisting of ...

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GNSS locations of lakebed images collected near Dollar Point, Lake Tahoe, CA, March 10 and 11, 2021

This text file (2021-607-FA_Image_Locations.txt) provides the GNSS antenna location for underwater images collected near Dollar Point, Lake Tahoe, CA, using a recently developed towed-surface vehicle with multiple downward-looking underwater cameras. The GNSS antenna location for the time of each image capture is presented with greater precision than is stored in the individual image’s EXIF header due to decimal place limitations of the EXIF format.

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Overlapping lakebed images collected near Dollar Point, Lake Tahoe, CA, March 10 and 11, 2021

Underwater images were collected near Dollar Point, Lake Tahoe, CA, using a recently developed towed-surface vehicle with multiple downward-looking underwater cameras. The images are organized in zipped files grouped by survey line. The SQUID-5 system records images as TIFF (.tif) format to maintain the highest resolution and bit depth. Each image includes EXIF metadata, containing GNSS date, time, and latitude and longitude of the GNSS antenna mounted on the towed surface vehicle, copyright, keywords, and ...

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Aerial Imagery of the North Carolina Coast: 2019-08-30 and 2019-09-02, Pre-Hurricane Dorian

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 ...

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Aerial Imagery of the North Carolina Coast: 2019-09-08 to 2019-09-13, Post-Hurricane Dorian

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 ...

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Aerial Imagery of the North Carolina Coast: 2019-10-11

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 ...

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Aerial Imagery of the North Carolina Coast: 2019-11-26

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 ...

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Aerial Imagery of the North Carolina Coast: 2020-02-08 to 2020-02-09

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 ...

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Aerial Imagery of the North Carolina Coast: 2020-05-08 to 2020-05-09

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 ...

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Time Series of Structure-from-Motion Products - Digital Elevation Models: Little Dauphin Island and Pelican Island, Alabama, September 2018 to April 2019

Aerial imagery acquired with a small unmanned aircraft system (sUAS), in conjunction with surveyed ground control points (GCP) visible in the imagery, can be processed with structure-from-motion (SfM) photogrammetry techniques to produce high-resolution orthomosaics, three-dimensional (3D) point clouds and digital elevation models (DEMs). This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides UAS survey data products consisting of DEMs ...

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Time Series of Structure-from-Motion Products - Multispectral Orthomosaics: Little Dauphin Island and Pelican Island, Alabama, September 2018 to April 2019

Aerial imagery acquired with a small unmanned aircraft system (sUAS), in conjunction with surveyed ground control points (GCP) visible in the imagery, can be processed with structure-from-motion (SfM) photogrammetry techniques to produce high-resolution orthomosaics, three-dimensional (3D) point clouds and digital elevation models (DEMs). This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides UAS survey data products consisting of ...

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Time Series of Structure-from-Motion Products - RGB Orthomosaics: Little Dauphin Island and Pelican Island, Alabama, September 2018 to April 2019

Aerial imagery acquired with a small unmanned aircraft system (sUAS), in conjunction with surveyed ground control points (GCP) visible in the imagery, can be processed with structure-from-motion (SfM) photogrammetry techniques to produce high-resolution orthomosaics, three-dimensional (3D) point clouds and digital elevation models (DEMs). This dataset, prepared by the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC), provides UAS survey data products consisting of red ...

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Digital surface models of Pea Island National Wildlife Refuge DUNEX Site, North Carolina in September and October 2021

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 ...

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Orthomosaics of Pea Island National Wildlife Refuge DUNEX Site, North Carolina in September and October 2021

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 ...

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MONT95C - Bathymetry contours of the southern Monterey Bay area between Moss Landing and Monterey, California

Derived contours at 10-m intervals are from data collected by the USGS with a multibeam (Simrad EM1000) sidescan sonar system in the southern Monterey Bay between Moss Landing and Monterey, California in 1995 (USGS Field Activity P1-95-MB). This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program Monterey Bay National Marine Sanctuary Project (see this and other older Monterey Bay USGS works archived ...

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Coastal Features Extracted from Landsat Satellite Imagery, Delaware Bay, New Jersey to Shinnecock Bay, New York, 2008-2022

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 ...

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10-m interval contours of smoothed multibeam bathymetry of Massachusetts Bay (MB_10MCTR9X9.SHP, Geographic, NAD83)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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5-m interval contours of smoothed multibeam bathymetry of Massachusetts Bay (MB_5MCTR9X9.SHP, Geographic, NAD83)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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1-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 1 (Q1_1MCTR.SHP)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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5-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 1 (Q1_5MCTR.SHP)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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1-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 2 (Q2_1MCTR.SHP)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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5-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 2 (Q2_5MCTR.SHP)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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1-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 3 (Q3_1MCTR.SHP)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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5-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangle 3 (Q3_5MCTR.SHP)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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1-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangles 1-3 (WMB_1MCTR.SHP)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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10 m bathymetric contours for the Southwest Washington Study area (BATHY)

Two 21-day field operations were conducted in 1997 and 1998 in the estuaries and on the inner continental shelf off the northern Oregon and southern Washington coast. These cruises aboard the R/V Corliss were run in order to generate reconnaissance maps of the seafloor geology and the shallow subsurface stratigraphy using sidescan-sonar and seismic-reflection mapping techniques. The 1998 cruise also collected sediment grab samples, bottom photographs, and video images to verify the sidescan-sonar imagery ...

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1-m bathymetric contours derived from single-beam echosounder data collected within the New York Bight by the U.S. Geological Survey, 1995 - 1998 (Esri polyline shapefile, Geographic, WGS84, Esri binary grid UTM Zone 18N)

These data represent single beam echo sounder (trackline) bathymetry collected in May 1995, May 1996, September 1996, May 1997, and October 1998 during five USGS cruises within the New York Bight region. Trackline spacing during these cruises was 300 meters. These data have been corrected for tidal fluctuations and distance of the transducer below the water line. All values are stored in meters. These data are referenced to Mean Lower Low Water.

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10-meter bathymetric contours from multibeam bathymetry in the East and West Flower Garden regions, northwestern Gulf of Mexico outer shelf (polyline shapefile)

This shapefile shows the 10 meter contour interval based on the 5-meter multibeam bathymetry (Dartnell and Gardner, 1999) from the Flower Garden Banks region.

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Bathymetric Contours within the inner shelf of Long Bay, South Carolina (CON_1M, 1 meter interval: Polyline shapefile)

In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining this ...

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Contours at Base of Onshore Quaternary Sediments for the region of Grand Strand, South Carolina(ONSHORE_CON, Polygon shapefile)

In 1999, the U.S. Geological Survey (USGS), in partnership with the South Carolina Sea Grant Consortium, began a study to investigate processes affecting shoreline change along the northern coast of South Carolina, focusing on the Grand Strand region. Previous work along the U.S. Atlantic coast shows that the structure and composition of older geologic strata located seaward of the coast heavily influences the coastal behavior of areas with limited sediment supply, such as the Grand Strand. By defining ...

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10 meter bathymetric contours of the Cape Ann - Salisbury Beach MA Survey Area (BATHCNTR_10M, geographic, WGS84)

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey, Coastal and Marine Geology Program, Woods Hole Science Center. Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine reserves, and ...

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1-meter contours produced from bathymetric data collected by the U.S. Geological Survey offshore of the Chandeleur Islands, LA, 2006-2007 (cont_1m, polyline)

In 2006 and 2007, the U.S. Geological Survey, in partnership with Louisiana Department of Natural Resources and the University of New Orleans, conducted geologic mapping to characterize the sea floor and shallow subsurface stratigraphy offshore of the Chandeleur Islands in Eastern Louisiana. The mapping was carried out during two cruises on the R/V Acadiana. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (234 kHz), Klein 3000 dual frequency sidescan sonar, and an ...

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5-meter contours produced from bathymetric data collected by the U.S. Geological Survey off the southern shore of Martha's Vineyard, MA, 2007 (ESRI POLYLINE SHAPEFILE, CON_5M)

The USGS Woods Hole Science Center conducted a nearshore geophysical survey offshore of the southern coast of Martha's Vineyard, in the vicinity of the Martha's Vineyard Coastal Observatory (MVCO) in August 2007. This mapping program was part of a larger research effort supporting the Office of Naval Research (ONR) Ripples Directed-Research Initiative (DRI) studies at MVCO by providing data collection and modeling. The geophysical data will be used to provide initial conditions for wave and circulation ...

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10 meter bathymetric contours of the Duxbury-Hull MA Survey Area (DH_BATHCNTR_10m shapefile, Geographic, WGS84)

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, delineating marine ...

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Bathymetric depth contours at 5 meter intervals of interferometric sonar data collected offshore of Massachusetts within northern Cape Cod Bay (CCB_5MCNTR Esri Shapefile, Geographic, WGS84).

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat ...

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5-meter bathymetric contours generated from swath bathymetric data collected by the U.S. Geological Survey within the St. Clair River between Michigan and Ontario, Canada, 2008 (ESRI VECTOR SHAPEFILE, CON_5M)

In 2008, the U.S. Geological Survey (USGS), Woods Hole Coastal and Marine Science Center (WHCMSC), in cooperation with the U.S. Army Corps of Engineers conducted a geophysical and sampling survey of the riverbed of the Upper St. Clair River between Port Huron, MI, and Sarnia, Ontario, Canada. The objectives were to define the Quaternary geologic framework of the St. Clair River to evaluate the relationship between morphologic change of the riverbed and underlying stratigraphy. This report presents the ...

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1-meter contours produced from swath bathymetry collected by the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL offshore of the Gulf Islands, MS, 2010 (ESRI polyline shapefile, tmunro_1m_bathycontours_MLLW.shp)

In 2010, the U.S. Geological Survey in Woods Hole, MA and St. Petersburg, FL, in partnership with the U.S. Army Corps of Engineers, Mobile District conducted geologic mapping to characterize the seafloor and shallow subsurface stratigraphy offshore of the Gulf Islands of Mississippi. The mapping was carried out during two cruises in March, 2010 on the R/V Tommy Munro of Biloxi, MS. Data were acquired with the following equipment: an SEA Ltd SwathPlus interferometric sonar (both 234 kHz and 468 kHz systems), ...

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Interpolated swath bathymetry contours collected by the U.S. Geological Survey - Woods Hole Coastal and Marine Science Center surrounding the nearshore of the Elizabeth Islands, MA, 2010 (ei_contours_1m_dd, ESRI polyline shapefile)

These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ...

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Depth contours derived from swath bathymetry data collected in Buzzards Bay by the U.S. Geological Survey and the National Oceanic and Atmospheric Administration offshore of Massachusetts in 2004, 2009, 2010, and 2011 (BB_5mCntr Esri Polyline Shapefile, Geographic, WGS84).

These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish habitat ...

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Bathymetric depth contours at 5 meter intervals derived from interferometric sonar data collected offshore of Massachusetts within Vineyard Sound by the U.S. Geological Survey in 2009, 2010, and 2011 (VS_5MCNTR_V2, Esri Shapefile, Geographic, WGS84).

These data were collected under a cooperative agreement with the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of sea-floor geology are important first steps toward protecting fish habitat, ...

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Interpolated swath bathymetry contours collected by the U.S. Geological Survey surrounding the nearshore of the Elizabeth Islands and sand shoals of Vineyard Sound, MA, 2007-2011 (Esri polyline shapefile, Geographic, WGS 84, All_contour5m.shp)

These data were collected under a cooperative agreement between the Massachusetts Office of Coastal Zone Management (CZM) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). Initiated in 2003, the primary objective of this program is to develop regional geologic framework information for the management of coastal and marine resources. Accurate data and maps of seafloor geology are important first steps toward protecting fish ...

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Polyline shapefile of a portion of the 1-meter (m) contours in quadrangle 6 of the Stellwagen Bank Survey Area offshore of Boston, Massachusetts necessary to show small features not displayed by 5-m contours - based on bathymetry data collected by the U.S. Geological Survey from 1994-1996 (Geographic, NAD 83)

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration's National Marine Sanctuary Program, has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary region since 1993. The area is approximately 3,700 square kilometers (km2) and is subdivided into 18 quadrangles. Seven maps, at a scale of 1:25,000, of quadrangle 6 (211 km2) depict seabed topography, backscatter, ruggedness, geology, substrate mobility, mud content, ...

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5 m Bathymetric Contours for Long Island Sound (LIS1992)

This bathymetric contour data set was derived from a gridded data set obtained from URI (B.Tyce, G. Hatcher). They used the "Gridder" program to obtain the grid. This gridded data set was generated from the original NOS soundings from 9 track tape that was cleaned up and edited at URI. This work was done with the intention of producing the color poster called "Long Island Sound Estuary" (Connecticut Dept. of Environmental Protection"), 1993. The accuracy is questionable.

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1 m Digital Bathymetric Contours from NOAA Charts as Organized for the LISSGIS Library (LISBATHY)

The Long Island Sound Study (LISS) compiled data from a number of different sources, integrated new data, and assembled a comprehensive spatial database for areas of the States of Connecticut, New York, and portions of Rhode Island which border Long Island Sound.

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CCALBATC - bathymetric contours for the central California region between Point Arena and Point Sur.

CCALBATC consists of bathymetric contours at 10-m and 50-m intervals for the area offshore of central California between Point Arena to the north and Point Sur to the south. The lines were digitized from 1:250,000-scale NOAA charts. This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program Monterey Bay National Marine Sanctuary Project (see this and other older Monterey Bay USGS works archived at https: ...

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NOSBATC - bathymetric contour data for the Monterey Bay region from Point Ano Nuevo to Point Sur, California based on NOAA/NOS data (UTM)

This dataset contains bathymetric contours for the greater Monterey Bay area between Point Ano Nuevo to the north and Point Sur to the south. Contours are provided at 10-m intervals to a depth of 200 m and 100-m intervals to maximum depth. The data from which the contours were derived were hydrographic survey points published by NOAA NOS in 1998. This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program ...

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Coastal Features Extracted from Landsat Satellite Imagery, Northern Chandeleur Islands, Louisiana, 1984-2019

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 ...

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Contoured Bathymetry for Lake Maurepas, Louisiana (MAURCONT)

This is the contoured bathymetry for Lake Maurepas created for USGS Professional Paper 1634 by Laura Hayes using Vertical Mapper.

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Contoured Bathymetry for Lake Pontchartrain, Louisiana (PONTCONT)

This is the contoured bathymetry for Lake Pontchartrain created for USGS Professional Paper 1634 by Laura Hayes using Vertical Mapper.

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5-m interval contours of smoothed multibeam bathymetry in western Massachusetts Bay map Quadrangles 1-3 (WMB_5MCTR.SHP)

The U.S. Geological Survey has conducted geologic mapping to characterize the sea floor offshore of Massachusetts. The mapping was carried out using a Simrad Subsea EM 1000 Multibeam Echo Sounder on the Frederick G. Creed on four cruises conducted between 1994 and 1998. The mapping was conducted in cooperation with the National Oceanic and Atmospheric Administration (NOAA) and with support from the Canadian Hydrographic Service and the University of New Brunswick. The long-term goal of this mapping ...

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New York Bight and Gulf of Maine bathymetric contours (NY_GOME_CONTOURS)

This bathymetric shapefile contains 10 m contours for the continental shelf and 100 m beyond the 200 m shelf edge. The contours have been derived from the National Oceanic and Atmospheric Administration (NOAA), National Geophysical Data Center (NGDC), Coastal Relief Models volume 1 and 2.

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1 m digital bathymetric contours from NOAA charts as organized for the Long Island Sound Study Geographic Information System (LISSGIS) library (LISBATHY.SHP)

The Long Island Sound Study (LISS) compiled data from a number of different sources, integrated new data, and assembled a comprehensive spatial database for areas of the States of Connecticut, New York, and portions of Rhode Island which border Long Island Sound.

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10 meter bathymetric contours of the Gulf of the Farallones region (10mCONTOUR)

In 1989, the U.S. Geological Survey (USGS) began a major geologic and oceanographic investigation of the Gulf of the Farallones continental shelf system, designed to evaluate and monitor human impacts on the marine environment (Karl and others, 2002). The study region is located off the central California coast, adjacent to San Francisco Bay and encompasses the Gulf of the Farallones National Marine Sanctuary. Geologic mapping of this area included the use of various remote sensing and sampling techniques ...

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500 meter bathymetric contours of the Gulf of the Farallones region (500mCONTOUR)

In 1989, the U.S. Geological Survey (USGS) began a major geologic and oceanographic investigation of the Gulf of the Farallones continental shelf system, designed to evaluate and monitor human impacts on the marine environment (Karl and others, 2002). The study region is located off the central California coast, adjacent to San Francisco Bay and encompasses the Gulf of the Farallones National Marine Sanctuary. Geologic mapping of this area included the use of various remote sensing and sampling techniques ...

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Digital Raster Graphic (DRG) image of U.S. Geological Survey standard series topographic map of Rincon, Puerto Rico (rincon_drg.tif)

The Digital Raster Graphic (DRG) is a raster image of a scanned USGS topographic map including the collar information, georeferenced to the UTM grid. This version of the Digital Raster Graphic (DRG) has been clipped to remove the collar (white border of the map) and has been reprojected to geographic coordinates.

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Simulation and visualization of coastal tsunami impacts from the SAFRR tsunami source - Maximum tsunami elevation model of Half Moon Bay, California

A high-resolution raster dataset of simulated maximum tsunami elevations in Half Moon Bay, California, based on the Science Application for Risk Reduction (SAFRR) tsunami scenario

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Simulation and visualization of coastal tsunami impacts from the SAFRR tsunami source - Maximum tsunami velocity model of Half Moon Bay, California

A high-resolution raster dataset of simulated maximum tsunami velocities in Half Moon Bay, California, based on the Science Application for Risk Reduction (SAFRR) tsunami scenario.

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Simulation and visualization of coastal tsunami impacts from the SAFRR tsunami source - Maximum tsunami elevation model of Oakland/Alameda, California

A high-resolution raster dataset of simulated maximum tsunami elevations in the Oakland and Alameda area of California based on the Science Application for Risk Reduction (SAFRR) tsunami scenario

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Simulation and visualization of coastal tsunami impacts from the SAFRR tsunami source - Maximum tsunami velocity model of Oakland/Alameda, California

A high-resolution raster dataset of simulated maximum tsunami velocities in the Oakland and Alameda area of California based on the Science Application for Risk Reduction (SAFRR) tsunami scenario.

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Simulation and visualization of coastal tsunami impacts from the SAFRR tsunami source - Maximum tsunami elevation model of Santa Cruz, California

A high-resolution raster dataset of simulated maximum tsunami elevations in Santa Cruz, California, based on the Science Application for Risk Reduction (SAFRR) tsunami scenario.

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Simulation and visualization of coastal tsunami impacts from the SAFRR tsunami source - Maximum tsunami velocity model of Santa Cruz, California

A high-resolution raster dataset of simulated maximum tsunami velocities in Santa Cruz, California, based on the Science Application for Risk Reduction (SAFRR) tsunami scenario.

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Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2008

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

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Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2010

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

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Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2014

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

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Barrier island geomorphology and seabeach amaranth metrics at 50-m alongshore transects, and 5-m cross-shore points for 2008 — Assateague Island, MD and VA.

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

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Assateague Island Seabeach Amaranth Survey Data — 2001 to 2018

Seabeach amaranth (Amaranthus pumilus) is a federally threatened plant species that was once prevalent on beaches of the U.S. mid-Atlantic coast. For much of the 20th century, seabeach amaranth was absent and thought to be extinct along this coast presumably due to development and recreational pressure. Few plants were observed over much of the 20th century and the species was federally listed as endangered in 1993. To re-establish a population, the Natural Resources staff at Assateague Island National ...

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Marsh Shorelines of the Massachusetts Coast from 2013-14 Topographic Lidar Data

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 ...

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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2010–2011

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

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DisOcean: Distance to the ocean: Cedar Island, VA, 2010

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

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ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2010

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

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2010–2011

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

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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2012–2013

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

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DisOcean: Distance to the ocean: Cedar Island, VA, 2012

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

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ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2012

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

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2012–2013

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

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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Cedar Island, VA, 2013–2014

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

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DisOcean: Distance to the ocean: Cedar Island, VA, 2014

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

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ElevMHW: Elevation adjusted to local mean high water: Cedar Island, VA, 2014

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

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Cedar Island, VA, 2013–2014

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

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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2010

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

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DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2010

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

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ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2010

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

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Edwin B. Forsythe NWR, NJ, 2010

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

Info
DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2012

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

Info
DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2012

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

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ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2012

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Edwin B. Forsythe NWR, NJ, 2012

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

Info
DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Edwin B. Forsythe NWR, NJ, 2013–2014

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

Info
DisOcean: Distance to the ocean: Edwin B. Forsythe NWR, NJ, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Edwin B. Forsythe NWR, NJ, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Edwin B. Forsythe NWR, NJ, 2013–2014

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

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DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2010–2011

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

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DisOcean: Distance to the ocean: Fire Island, NY, 2010

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

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ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2010

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

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2010–2011

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

Info
DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2012

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

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DisOcean: Distance to the ocean: Fire Island, NY, 2012

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

Info
ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2012

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2012

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

Info
DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Fire Island, NY, 2014–2015

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

Info
DisOcean: Distance to the ocean: Fire Island, NY, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Fire Island, NY, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Fire Island, NY, 2014–2015

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

Info
DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Rockaway Peninsula, NY, 2010–2011

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

Info
ElevMHW: Elevation adjusted to local mean high water: Rockaway Peninsula, NY, 2010

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2010–2011

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

Info
DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Rockaway Peninsula, NY, 2012

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

Info
DisOcean: Distance to the ocean: Rockaway Peninsula, NY, 2012

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

Info
ElevMHW: Elevation adjusted to local mean high water: Rockaway Peninsula, NY, 2012

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2012

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

Info
DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Rockaway Peninsula, NY, 2013–2014

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

Info
DisOcean: Distance to the ocean: Rockaway Peninsula, NY, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Rockaway Peninsula, NY, 2014

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

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters (landcover, geomorphic setting, substrate type, vegetation density, and vegetation type): Rockaway Peninsula, NY, 2013–2014

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

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2013-14 Massachusetts Lidar-Derived Dune Crest Point Data

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 ...

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2013-14 Massachusetts Lidar-Derived Dune Toe Point Data

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 ...

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Mean High Water Shorelines for the Outer Cape of Massachusetts from Nauset Inlet to Race Point (1998-2005)

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

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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assateague Island, MD & VA, 2014

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

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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Assateague Island, MD & VA, 2014

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

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DisOcean: Distance to the ocean: Assateague Island, MD & VA, 2014

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

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ElevMHW: Elevation adjusted to local mean high water: Assateague Island, MD & VA, 2014

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

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Assateague Island, MD & VA, 2014

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

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assateague Island, MD & VA, 2014

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

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SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Assateague Island, MD & VA, 2014

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

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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Assawoman Island, VA, 2014

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

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DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Assawoman Island, VA, 2014

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

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DisOcean: Distance to the ocean: Assawoman Island, VA, 2014

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

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ElevMHW: Elevation adjusted to local mean high water: Assawoman Island, VA, 2014

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

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Assawoman Island, VA, 2014

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

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Assawoman Island, VA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Assawoman Island, VA, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cape Hatteras, NC, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Cape Hatteras, NC, 2014

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

Info
DisOcean: Distance to the ocean: Cape Hatteras, NC, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Cape Hatteras, NC, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cape Hatteras, NC, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Hatteras, NC, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Cape Hatteras, NC, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cape Lookout, NC, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Cape Lookout, NC, 2014

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

Info
DisOcean: Distance to the ocean: Cape Lookout, NC, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Cape Lookout, NC, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cape Lookout, NC, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Lookout, NC, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Cape Lookout, NC, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Coast Guard Beach, MA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Coast Guard Beach, MA, 2013-2014

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

Info
DisOcean: Distance to the ocean: Coast Guard Beach, MA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Coast Guard Beach, MA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Coast Guard Beach, MA, 2013-2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Coast Guard Beach, MA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Coast Guard Beach, MA, 2013-2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cobb Island, VA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Cobb Island, VA, 2014

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

Info
DisOcean: Distance to the ocean: Cobb Island, VA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Cobb Island, VA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cobb Island, VA, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cobb Island, VA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Cobb Island, VA, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fisherman Island, VA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Fisherman Island, VA, 2014

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

Info
DisOcean: Distance to the ocean: Fisherman Island, VA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Fisherman Island, VA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fisherman Island, VA, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fisherman Island, VA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Fisherman Island, VA, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Metompkin Island, VA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Metompkin Island, VA, 2014

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

Info
DisOcean: Distance to the ocean: Metompkin Island, VA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Metompkin Island, VA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Metompkin Island, VA, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Metompkin Island, VA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Metompkin Island, VA, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Monomoy Island, MA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Monomoy Island, MA, 2013-2014

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

Info
DisOcean: Distance to the ocean: Monomoy Island, MA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Monomoy Island, MA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Monomoy Island, MA, 2013-2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Monomoy Island, MA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Monomoy Island, MA, 2013-2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Myrtle Island, VA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Myrtle Island, VA, 2014

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

Info
DisOcean: Distance to the ocean: Myrtle Island, VA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Myrtle Island, VA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Myrtle Island, VA, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Myrtle Island, VA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Myrtle Island, VA, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Parramore Island, VA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Parramore Island, VA, 2014

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

Info
DisOcean: Distance to the ocean: Parramore Island, VA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Parramore Island, VA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parramore Island, VA, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Parramore Island, VA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Parramore Island, VA, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Parker River, MA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Parker River, MA, 2014

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

Info
DisOcean: Distance to the ocean: Parker River, MA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Parker River, MA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Parker River, MA, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Parker River, MA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Parker River, MA, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rhode Island National Wildlife Refuge, RI, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Rhode Island National Wildlife Refuge, RI, 2014

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

Info
DisOcean: Distance to the ocean: Rhode Island National Wildlife Refuge, RI, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Rhode Island National Wildlife Refuge, RI, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rhode Island National Wildlife Refuge, RI, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Rhode Island National Wildlife Refuge, RI, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Rhode Island National Wildlife Refuge, RI, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Ship Shoal Island, VA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Ship Shoal Island, VA, 2014

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

Info
DisOcean: Distance to the ocean: Ship Shoal Island, VA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Ship Shoal Island, VA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Ship Shoal Island, VA, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Ship Shoal Island, VA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Ship Shoal Island, VA, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Smith Island, VA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Smith Island, VA, 2014

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

Info
DisOcean: Distance to the ocean: Smith Island, VA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Smith Island, VA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Smith Island, VA, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Smith Island, VA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Smith Island, VA, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Wreck Island, VA, 2014

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

Info
DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Wreck Island, VA, 2014

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

Info
DisOcean: Distance to the ocean: Wreck Island, VA, 2014

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

Info
ElevMHW: Elevation adjusted to local mean high water: Wreck Island, VA, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Wreck Island, VA, 2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Wreck Island, VA, 2014

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

Info
SupClas, GeoSet, SubType, VegDen, VegType: Categorical landcover rasters of landcover, geomorphic setting, substrate type, vegetation density, and vegetation type: Wreck Island, VA, 2014

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

Info
Paleoshorelines--Monterey Canyon and Vicinity Map Area, California

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 ...

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cedar Island, VA, 2010

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cedar Island, VA, 2012

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cedar Island, VA, 2012–2013

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

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cedar Island, VA, 2012

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

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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cedar Island, VA, 2014

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

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Cedar Island, VA, 2013–2014

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

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cedar Island, VA, 2014

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

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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2010

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

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010

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

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Edwin B. Forsythe NWR, NJ, 2010

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2012

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2012

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Edwin B. Forsythe NWR, NJ, 2012

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2014

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

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2013–2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Edwin B. Forsythe NWR, NJ, 2014

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

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DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2010

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

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fire Island, NY, 2010–2011

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

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shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2010

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2012

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fire Island, NY, 2012

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2012

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Fire Island, NY, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Fire Island, NY, 2014–2015

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Fire Island, NY, 2014

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rockaway Peninsula, NY, 2010

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

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points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rockaway Peninsula, NY, 2010–2011

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Rockaway Peninsula, NY, 2010

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rockaway Peninsula, NY, 2012

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rockaway Peninsula, NY, 2012

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Rockaway Peninsula, NY, 2012

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

Info
DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Rockaway Peninsula, NY, 2014

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

Info
points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Rockaway Peninsula, NY, 2013–2014

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

Info
shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Rockaway Peninsula, NY, 2014

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

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Remote Sensing Coastal Change Simple Data Distribution Service

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

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

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

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

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

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Imagery from USGS CoastCam deployed at Madeira Beach, Florida

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

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USGS CoastCam at Tres Palmas, Rincón, Puerto Rico: Timestack Imagery and Coordinate Data

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, ...

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USGS CoastCam at Isla Verde, Puerto Rico: 2018-2019 Timestack Imagery and Coordinate Data

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 ...

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USGS CoastCam at Waiakāne, Moloka'i, Hawai'i: 2018 Timestack Imagery and Coordinate Data

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 ...

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USGS CoastCam at Isla Verde, Puerto Rico: 2018-2019 Intrinsic and Extrinsic Calibration Data

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 ...

Info
USGS CoastCam at Tres Palmas, Rincón, Puerto Rico: Intrinsic and Extrinsic Calibration Data

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 ...

Info
USGS CoastCam at Waiakāne, Moloka'i, Hawai'i: 2018 Intrinsic and Extrinsic Calibration Data

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 ...

Info
USGS CoastCam at Sand Key, Florida: Intrinsic and Extrinsic Calibration Data (Camera 1)

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 ...

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USGS CoastCam at Sand Key, Florida: Intrinsic and Extrinsic Calibration Data (Camera 2)

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, ...

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USGS CoastCam at Madeira Beach, Florida: Timestack Imagery and Coordinate Data

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 ...

Info
USGS CoastCam at Sand Key, Florida: Timestack Imagery and Coordinate Data (Camera 2)

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 ...

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2D micromodel studies of pore-throat clogging by pure fine-grained sediments and natural sediments from NGHP-02, offshore India

Fine-grained sediments, or “fines,” are nearly ubiquitous in natural sediments, even in the predominantly coarse-grained sediments that host gas hydrates. Fines within these sandy sediments can be mobilized and subsequently clog flow pathways while methane is being extracted from gas hydrate as an energy resource. Using two-dimensional (2D) micromodels to test the conditions in which clogging occurs provides insights for choosing production operation parameters that optimize methane recovery in the ...

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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-06-26

Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ...

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USGS CoastCam at DUNEX: Intrinsic and Extrinsic Calibration Data (Camera 1)

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. ...

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USGS CoastCam at DUNEX: Intrinsic and Extrinsic Calibration Data (Camera 2)

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. ...

Info
USGS CoastCam at DUNEX: Timestack Imagery and Coordinate Data (Camera 1)

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. ...

Info
USGS CoastCam at DUNEX: Timestack Imagery and Coordinate Data (Camera 2)

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. ...

Info
Unprocessed aerial imagery from 9 December 2015 coastal survey of Central California.

This is a set of 1132 oblique aerial photogrammetric images and their derivatives, collected from Capitola to Pajaro Dunes with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 26 January 2016 coastal survey of Central California.

This is a set of 1836 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 5 February 2016 coastal survey of Central California.

This is a set of 3494 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 2 March 2016 coastal survey of Central California.

This is a set of 1309 oblique aerial photogrammetric images and their derivatives, collected from Santa Cruz to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 8 March 2016 coastal survey of Central California.

This is a set of 2753 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 15 September 2016 coastal survey of Central California.

This is a set of 1600 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

Info
Unprocessed aerial imagery from 26 September 2016 coastal survey of Central California.

This is a set of 1569 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ano Nuevo with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 1 December 2016 coastal survey of Central California.

This is a set of 3234 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 20 December 2016 coastal survey of Central California.

This is a set of 3036 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 25 January 2017 coastal survey of Central California.

This is a set of 4521 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Cape San Martin with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 22 February 2017 coastal survey of Central California.

This is a set of 4808 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Lucia with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 8 March 2017 coastal survey of Central California.

This is a set of 5642 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 5 April 2017 coastal survey of Central California.

This is a set of 5044 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Cape San Martin with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 8 May 2017 coastal survey of Central California.

This is a set of 1975 oblique aerial photogrammetric images and their derivatives, collected from Pedro Point to Sunset Beach with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 12 May 2017 coastal survey of Central California.

This is a set of 628 oblique aerial photogrammetric images and their derivatives, collected from SeaCliff Beach to Fort Ord with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 17 May 2017 coastal survey of Central California.

This is a set of 3045 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 19 May 2017 coastal survey of Central California.

This is a set of 3164 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 27 May 2017 coastal survey of Central California.

This is a set of 642 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 31 May 2017 coastal survey of Central California.

This is a set of 410 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 13 June 2017 coastal survey of Central California.

This is a set of 757 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 26 June 2017 coastal survey of Central California.

This is a set of 5069 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 18 December 2017 coastal survey of Central California.

This is a set of 2948 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 21 December 2017 coastal survey of Central California.

This is a set of 2072 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 29 January 2018 coastal survey of Central California.

This is a set of 5365 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 7 March 2018 coastal survey of Central California.

This is a set of 5355 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 28 May 2018 coastal survey of Central California.

This is a set of 3550 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 5 June 2018 coastal survey of Central California.

This is a set of 1533 oblique aerial photogrammetric images and their derivatives, collected from Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

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Unprocessed aerial imagery from 10 September 2018 coastal survey of Central California.

This is a set of 5846 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 23 February 2019 coastal survey of Central California.

This is a set of 4734 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 4 March 2019 coastal survey of Central California.

This is a set of 2541 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 11 March 2019 coastal survey of Central California.

This is a set of 1967 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 10 June 2019 coastal survey of Central California.

This is a set of 5042 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 15 October 2019 coastal survey of Central California.

This is a set of 3777 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 31 October 2019 coastal survey of Central California.

This is a set of 1911 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 29 November 2019 coastal survey of Central California.

This is a set of 1782 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Davenport with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 30 November 2019 coastal survey of Central California.

This is a set of 1444 oblique aerial photogrammetric images and their derivatives, collected from Davenport to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 20 January 2020 coastal survey of Central California.

This is a set of 3072 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 25 January 2020 coastal survey of Central California.

This is a set of 1880 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 9 March 2020 coastal survey of Central California.

This is a set of 1979 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 19 March 2020 coastal survey of Central California.

This is a set of 4835 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 19 April 2020 coastal survey of Central California.

This is a set of 2889 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 5 July 2020 coastal survey of Central California.

This is a set of 1890 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 30 September 2020 coastal survey of Central California.

This is a set of 3862 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 15 October 2020 coastal survey of Central California.

This is a set of 1982 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 10 January 2021 coastal survey of Central California.

This is a set of 1896 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 11 January 2021 coastal survey of Central California.

This is a set of 3796 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

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Unprocessed aerial imagery from 29 January 2021 coastal survey of Central California.

This is a set of 4919 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 3 March 2021 coastal survey of Central California.

This is a set of 2049 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 26 March 2021 coastal survey of Central California.

This is a set of 5626 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 8 September 2021 coastal survey of Central California.

This is a set of 2678 oblique aerial photogrammetric images and their derivatives, collected from PigeonPt to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 18 December 2021 coastal survey of Central California.

This is a set of 4722 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 20 January 2022 coastal survey of Central California.

This is a set of 2066 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 4 February 2022 coastal survey of Central California.

This is a set of 2269 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 12 March 2022 coastal survey of Central California.

This is a set of 2098 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 9 June 2022 coastal survey of Central California.

This is a set of 4595 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Big Sur with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 12-13 September 2022 coastal survey of Central California.

This is a set of 3661 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey (x2) with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 1 January 2023 coastal survey of Central California.

This is a set of 2076 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 5 January 2023 coastal survey of Central California.

This is a set of 2105 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 16 January 2023 coastal survey of Central California.

This is a set of 2763 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 23 January 2023 coastal survey of Central California.

This is a set of 5039 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 1 February 2023 coastal survey of Central California.

This is a set of 2943 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 8 February 2023 coastal survey of Central California.

This is a set of 1939 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 2 March 2023 coastal survey of Central California.

This is a set of 1839 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 3 March 2023 coastal survey of Central California.

This is a set of 2758 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 13 March 2023 coastal survey of Central California.

This is a set of 2195 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 16 March 2023 coastal survey of Central California.

This is a set of 2915 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 17 March 2023 coastal survey of Central California.

This is a set of 2077 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 6 April 2023 coastal survey of Central California.

This is a set of 2374 vertical aerial photogrammetric images and their derivatives, collected from Half Moon Bay to Santa Cruz with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 8 June 2023 coastal survey of Central California.

This is a set of 2123 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 10 October 2023 coastal survey of Central California.

This is a set of 3929 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 11 October 2023 coastal survey of Central California.

This is a set of 4930 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 26 October 2023 coastal survey of Central California.

This is a set of 2869 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 23 December 2023 coastal survey of Central California.

This is a set of 4772 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 29 December 2023 coastal survey of Central California.

This is a set of 1821 oblique aerial photogrammetric images and their derivatives, collected from Ano Nuevo to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 1 January 2024 coastal survey of Central California.

This is a set of 2876 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 12 January 2024 coastal survey of Central California.

This is a set of 1965 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 9 February 2024 coastal survey of Central California.

This is a set of 4787 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 23 February 2024 coastal survey of Central California.

This is a set of 2323 oblique aerial photogrammetric images and their derivatives, collected from Monterey to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 24 February 2024 coastal survey of Central California.

This is a set of 3059 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 7 March 2024 coastal survey of Central California.

This is a set of 2161 oblique aerial photogrammetric images and their derivatives, collected from Natural Bridges to Monterey with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 6 April 2024 coastal survey of Central California.

This is a set of 2286 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 17 June 2024 coastal survey of Central California.

This is a set of 5140 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 18 August 2024 coastal survey of Central California.

This is a set of 2003 oblique aerial photogrammetric images and their derivatives, collected from Point Lobos to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 6 January 2023 coastal-landslides survey of Central California.

This is a set of 8762 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 12 January 2023 coastal-landslides survey of Central California.

This is a set of 11207 oblique aerial photogrammetric images and their derivatives, collected from San Francisco to Ragged Point with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

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Unprocessed aerial imagery from 4-5 November 2020 CZU-fire survey of Central California.

This is a set of 11776 near-nadir aerial photogrammetric images and their derivatives, collected from CZU fire with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

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Unprocessed aerial imagery from 26 January 2017 landslides survey of Central California.

This is a set of 4889 oblique aerial photogrammetric images and their derivatives, collected from San Francisco Bay area with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 23 February 2017 landslides survey of Central California.

This is a set of 5954 oblique aerial photogrammetric images and their derivatives, collected from San Francisco Bay area with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 29 March 2018 coastal survey of Central and southern California.

This is a set of 1160 oblique aerial photogrammetric images and their derivatives, collected from Mud Creek Slide to Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera ...

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Unprocessed aerial imagery from 13 October 2018 coastal survey of Northern California to Washington.

This is a set of 11805 oblique aerial photogrammetric images and their derivatives, collected from OR-WA border to Mussel Rock CA with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 19 April 2024 coastal survey of Northern California to Washington.

This is a set of 14032 oblique aerial photogrammetric images and their derivatives, collected from Hoh Head to Cape Mendocino with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 25 September 2016 coastal survey of Oregon and Washington.

This is a set of 1712 oblique aerial photogrammetric images and their derivatives, collected from Cape Falcon to Cascade Head with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 28 September 2017 coastal survey of Oregon and Washington.

This is a set of 2060 oblique aerial photogrammetric images and their derivatives, collected from OR-WA border to Nestucca River OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 3 August 2020 coastal survey of Oregon and Washington.

This is a set of 2324 oblique aerial photogrammetric images and their derivatives, collected from Taholah WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 3 September 2020 coastal survey of Oregon and Washington.

This is a set of 2158 oblique aerial photogrammetric images and their derivatives, collected from NW WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded ...

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Unprocessed aerial imagery from 29 August 2022 coastal survey of Oregon and Washington.

This is a set of 2413 oblique aerial photogrammetric images and their derivatives, collected from Taholah WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 1 June 2023 coastal survey of Oregon and Washington.

This is a set of 10139 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea WA to Seaside OR with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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PCMSC PlaneCam – Field data from periodic and event-response surveys of the U.S. West Coast.

This is an ongoing collection of aerial oblique and near-nadir images, ancillary data, and derivatives, from aerial surveys of coastal and near-coastal environments with a crewed light aircraft using the "PCMSC PlaneCam," a mounted fixed-lens DSLR camera with an attached consumer-grade GPS for time-keeping and approximate position, and a Global Navigation Satellite System (GNSS) for precise positioning. Data are collected and produced primarily for coastal monitoring using structure-from-motion ...

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Unprocessed aerial imagery from 28 September 2016 coastal survey of Southern California.

This is a set of 2671 oblique aerial photogrammetric images and their derivatives, collected from ptConception to Ventura with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 1 March 2017 coastal survey of Southern California.

This is a set of 2979 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Ventura with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 27 December 2017 coastal survey of Southern California.

This is a set of 2392 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Santa Barbara with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 13 September 2018 coastal survey of Southern California.

This is a set of 2062 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 6 May 2020 coastal survey of Southern California.

This is a set of 2167 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 18 September 2020 coastal survey of Southern California.

This is a set of 1968 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 2 March 2022 coastal survey of Southern California.

This is a set of 2212 oblique aerial photogrammetric images and their derivatives, collected from Santa Barbara Channel with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, ...

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Unprocessed aerial imagery from 28 September 2022 coastal survey of Southern California.

This is a set of 2032 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

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Unprocessed aerial imagery from 2 October 2022 coastal survey of Southern California.

This is a set of 1108 oblique aerial photogrammetric images and their derivatives, collected from Santa Rosa Island with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by ...

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Unprocessed aerial imagery from 8 March 2023 coastal survey of Southern California.

This is a set of 2006 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

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Unprocessed aerial imagery from 12 October 2023 coastal survey of Southern California.

This is a set of 2013 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Port Hueneme with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 5 January 2024 coastal survey of Southern California.

This is a set of 2061 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

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Unprocessed aerial imagery from 12 February 2024 coastal survey of Southern California.

This is a set of 2032 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

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Unprocessed aerial imagery from 23 February 2024 coastal survey of Southern California.

This is a set of 2371 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

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Unprocessed aerial imagery from 18 March 2024 coastal survey of Southern California.

This is a set of 2076 oblique aerial photogrammetric images and their derivatives, collected from Point Conception to Point Mugu with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number ...

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Unprocessed aerial imagery from 23 January 2018 Thomas-fire survey of Southern California.

This is a set of 4838 oblique aerial photogrammetric images and their derivatives, collected from Montecito with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

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Unprocessed aerial imagery from 19 April 2023 thomas-fire survey of Southern California.

This is a set of 3086 vertical aerial photogrammetric images and their derivatives, collected from Montecito with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

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Unprocessed aerial imagery from 4 August 2020 coastal survey of Washington.

This is a set of 645 oblique aerial photogrammetric images and their derivatives, collected from Elwha river mouth to Ediz Hook CG with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Unprocessed aerial imagery from 28 August 2022 coastal survey of Washington.

This is a set of 4116 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

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Unprocessed aerial imagery from 29 August 2022 coastal survey of Washington.

This is a set of 4281 oblique and near nadir aerial photogrammetric images and their derivatives, collected from Elwha river mouth to Ediz Hook CG with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the ...

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Unprocessed aerial imagery from 6 July 2024 coastal survey of Washington.

This is a set of 7809 oblique aerial photogrammetric images and their derivatives, collected from Salish Sea with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial number, preceded by the ...

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Unprocessed aerial imagery from 31 August 2024 coastal survey of Washington.

This is a set of 6976 oblique aerial photogrammetric images and their derivatives, collected from Juan de Fuca Strait to Grays Harbor with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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Laboratory Observations of Oscillatory Flow Over Sand Ripples: Image Metadata

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 ...

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Laboratory Observations of Oscillatory Flow Over Sand Ripples: Velocity Metadata

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 ...

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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 1967-10-18

Presented here is a point cloud produced by the U.S. Geological Survey (USGS) from historical U.S. Air Force vertical aerial imagery, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was downloaded from USGS Eros Data Center and processed using structure-from-motion ...

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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-03-08

Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ...

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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-05-19

Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point Cloud Coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ...

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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-05-27

Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ...

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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-06-13

Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ...

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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-10-12

Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using a UAS-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. The point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Ricoh GR camera in DNG format and processed using structure-from-motion photogrammetry ...

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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-12-07

Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using a UAS-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. Point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Ricoh GR camera in DNG format and processed using structure-from-motion photogrammetry with ...

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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2017-12-21

Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. Point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ...

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Structure-from-motion point cloud of Mud Creek, Big Sur, California, 2018-01-29

Presented here is a point cloud collected by the U.S. Geological Survey (USGS) using an oblique plane-mounted camera system, covering the area of the Mud Creek landslide on California State Route 1 (SR1), Mud Creek, Big Sur, California. Point cloud is referenced to previously published lidar data and contains RGB information as well as XYZ. Point cloud coordinates are in NAD83 UTM Zone 10 meters. Imagery was collected with a Nikon D800 camera in RAW format and processed using structure-from-motion ...

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Shorelines Derived from Continuous Video-Imagery at the NASA-Kennedy Space Center, Florida From August 2011 to July 2012

In 2010, a video camera was installed near the northern boundary of the National Aeronautics and Space Administration-Kennedy Space Center (NASA-KSC) property along the Atlantic coast of Florida. A region extending 1 kilometer (km) to the south of the camera was established as the region of interest for the video image observations. During every daylight hour of camera operation from August 8, 2011 to July 24, 2012, a time exposure (timex) image product was created by averaging pixel color intensity for all ...

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California State Waters Map Series--Offshore of Monterey Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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Offshore Pigeon Point_Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Point Conception to Hueneme Canyon Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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Offshore Scott Creek Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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Offshore Aptos Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Pigeon Point to Monterey Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Point Conception Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Gaviota Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Monterey Canyon and Vicinity Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Point Sur to Point Arguello Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Punta Gorda to Point Arena Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Bodega Head Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Bolinas to Pescadero Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Bolinas Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Carpinteria Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Coal Oil Point Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Drakes Bay Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Fort Ross Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Half Moon Bay Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Hueneme Canyon Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Pacifica Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Point Reyes Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Refugio Beach Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Salt Point to Drakes Bay Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Salt Point Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of San Francisco Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Santa Barbara Channel Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Santa Barbara Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Tomales Point Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Ventura Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of Santa Cruz Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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California State Waters Map Series--Offshore of San Gregorio Web Services

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for Cape Cod Bay, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the north shore of Martha's Vineyard, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the south shore of Martha's Vineyard, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the north shore of Nantucket, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the south shore of Nantucket, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the North Shore of MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the Outer Cape of MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the southern shoreline of Cape Cod, MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the South Coast of MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Uncertainty table for lidar-derived shorelines used when calculating rates in the Digital Shoreline Analysis System software for the South Shore of MA

The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast. The shoreline position and change rate are used to inform management decisions regarding the erosion of coastal resources. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates at 40-meter intervals along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using ...

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Local radiocarbon reservoir age (Delta-R) variability from the nearshore and open-ocean environments of the Florida Keys reef tract during the Holocene and associated U-series and radiocarbon data (Marine13 Radiocarbon Calibration Curve)

Holocene-aged corals from reef cores collected throughout the Florida Keys reef tract (FKRT) were dated using a combination of U-series and radiocarbon techniques to quantify the millennial-scale variability in the local radiocarbon reservoir age (ΔR) of the shallow water environments of south Florida. ΔR provides a measure of the deviation of local radiocarbon concentrations of marine environments from the global average and can be used as a tracer of oceanic circulation and local hydrology. U.S. ...

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Local radiocarbon reservoir age (ΔR) variability from the nearshore and open-ocean environments of the Florida Keys reef tract during the Holocene and associated U-series and radiocarbon data (Marine20 Radiocarbon Calibration Curve)

68 Holocene-aged corals from reef cores collected throughout the Florida Keys reef tract (FKRT) were dated using a combination of U-series and radiocarbon techniques to quantify the millennial-scale variability in the local radiocarbon reservoir age (ΔR) of the shallow water environments of south Florida. ΔR provides a measure of the deviation of local radiocarbon concentrations of marine environments from the global average and can be used as a tracer of oceanic circulation and local hydrology. U.S. ...

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Underwater video footage, March 2014, Faga'alu Bay, Tutuila Island, American Samoa

Underwater video imagery was collected in March 2014 in the nearshore waters of Faga'alu Bay on the Island of Tutuila, American Samoa, as part of the U.S. Geological Survey Coastal and Marine Geology Program's Pacific Coral Reefs Project. Included here are 40 video files in .mpg format and an Environmental Systems Research Institute (ESRI) shapefile with location (navigation) points every two seconds.

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Digital seafloor character data of the Gulf of Alaska from historical National Ocean Service (NOS) smooth sheets

This data release provides seafloor-characteristics point data across the Gulf of Alaska, as digitized directly from National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) smooth sheets published from 1892 to 2001, and archived at the National Geophysics Data Center (NGDC). Geo-rectification and digitization methods were adapted from Zimmermann and Benson (2013). Each location includes information for the smooth sheet number (H#####), a unique site number location, latitude, ...

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List of NOS smooth sheets used in USGS Gulf of Alaska Digitization Project

This table lists the NOS smooth sheets included in the associated shapefile (GulfofAlaskaDigitizationProject_NOSSeafloorCharacter.zip; N = 329, plus insets), the number of samples for each smooth sheet, the year of collection (1892 to 2001), and the smooth sheet scale (from 1:2,000 to 1:600,000). Smooth sheets are available through the National Geophysics Data Center’s online data portal (NDGC, http://www.ngdc.noaa.gov).

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Still-image frame grabs and benthic habitat interpretation of underwater video footage, March 2014, Faga`alu Bay, American Samoa

Underwater video was collected in March 2014 in the nearshore waters of Faga`alu Bay on the island of Tutuila, American Samoa, as part of the U.S. Geological Survey Coastal and Marine Geology Program's Pacific Coral Reefs Project. This dataset includes 2,119 still images extracted from the video footage every 10 seconds and an Environmental Systems Research Institute (ESRI) shapefile of individual still-image locations with benthic habitat interpretations for each image.

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The absolute and relative composition of Holocene reef cores collected between 1976 and 2017 from the Florida Keys reef tract

This data release provides a summary of the absolute percent composition of all recovered material and relative percent composition of coral taxa in the Holocene-aged intervals of 61 coral-reef cores collected throughout the Florida Keys reef tract (FKRT) housed in the USGS Core Archive in St. Petersburg, FL (Estimated ages for distinct depths within each core are also provided; those ages were either measured by radiometric dating of coral samples at those depths or estimated by linear interpolation ...

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Grain-Size and Data Analysis Results from Sediment Samples Collected at Crocker Reef, Florida, Between 2017 and 2019

Sediment samples were collected from undisturbed sections of the seafloor around Crocker Reef, Florida. Crocker Reef is a barrier reef located in the northern portion of the Florida Reef Tract that has been classified by Kellogg and others (2015) as a senile or dead reef consisting of areas of sand and rubble with only scattered stony coral colonies. Samples were collected from November 2017 to April 2019 to help ground truth coincident instrumentation deployed during the same time interval, which was used ...

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Time Series of Autonomous Carbonate System Parameter Measurements from Crocker Reef, Florida, USA

This dataset contains carbonate system data collected by scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center to investigate the effects of carbon cycling, coastal and ocean acidification at Crocker Reef located along the Florida Keys Reef Tract, in Southeast Florida, USA. These data were collected using an autonomous instrument called the Ocean Carbon System version 1 (OCSv1) deployed on the seafloor at Crocker Reef. The OCSv1 consists of five sensors ...

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Time Series of Autonomous Carbonate System Parameter Measurements in Eastern Gulf of Mexico near Tampa Bay, Florida, USA

This dataset contains carbonate system data collected by scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center to investigate the effects of carbon cycling, coastal and ocean acidification in the Gulf of Mexico near the Tampa Bay estuary located in west central Florida, USA. These data were collected using an autonomous instrument called the Ocean Carbon System version 3 (OCSv3) deployed on the University of South Florida (USF), Coastal Ocean Monitoring and ...

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Time Series of Autonomous Carbonate System Parameter Measurements in Eastern Gulf of Mexico near Tampa Bay, Florida, USA (Version 2.0)

This dataset contains carbonate system data collected by scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center to investigate the effects of carbon cycling, coastal and ocean acidification in the Gulf of Mexico near the Tampa Bay estuary located in west central Florida, USA. These data were collected using an autonomous instrument called the Ocean Carbon System version 3 (OCSv3) deployed on the University of South Florida (USF), Coastal Ocean Monitoring and ...

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Wetland-Change Data Derived from Landsat Imagery, Assateague Island to Metompkin Island, Maryland and Virginia, 1984 to 2015: Land-cover Change Analysis

This U.S. Geological Survey (USGS) data release includes geospatial datasets that were created for the analysis of Virginia and Maryland Atlantic coastal wetland changes over time. Wetland change was determined by assessing two metrics: wetland persistence and land-cover switching. Because seasonal water levels, beach width, and vegetation differences can affect change analyses, only images acquired during the spring (March, April, and May) were included in the wetland-change metrics (N=10). Land-cover ...

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Land-Cover Data Derived from Landsat Satellite Imagery, Assateague Island to Metompkin Island, Maryland and Virginia, 1985 and 2015

This U.S. Geological Survey (USGS) data release includes geospatial datasets that were created to analyze wetland changes along the Virginia and Maryland Atlantic coasts between 1984 and 2015. Wetland change was determined by assessing two metrics: wetland persistence and land-cover switching. Because seasonal water levels, beach width, and vegetation differences can affect change analyses, only images acquired during the spring (March, April, and May) were included in the wetland-change metrics (N=10). ...

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Discrete Carbonate System Parameter Measurements in Middle Tampa Bay, Florida and the Eastern Gulf of Mexico, USA

This dataset contains carbonate system data collected by scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center to investigate the effects of carbon cycling, coastal and ocean acidification on the Tampa Bay estuary located in west central Florida and eastern Gulf of Mexico. Discrete seawater samples were collected periodically (every few weeks to months) at repeat monitoring locations. Water samples were analyzed by the USGS Carbon Analytical Laboratory in St. ...

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Time Series of Autonomous Carbonate System Parameter Measurements in Middle Tampa Bay, Florida, USA

This dataset contains carbonate system data collected by scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center to investigate the effects of carbon cycling, coastal and ocean acidification on the Tampa Bay estuary located in west central Florida, USA. These data were collected using an autonomous instrument called the Ocean Carbon System version 2 (OCSv2) deployed on the seafloor in Tampa Bay. The OCSv2 consists of four sensors integrated into a Sea-Bird ...

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Time Series of Autonomous Carbonate System Parameter Measurements in Middle Tampa Bay, Florida, USA (version 2.0, August 2019)

This dataset contains carbonate system data collected by scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center to investigate the effects of carbon cycling, coastal and ocean acidification on the Tampa Bay estuary located in west central Florida, USA. These data were collected using an autonomous instrument called the Ocean Carbon System version 2 (OCSv2) deployed on the seafloor in Tampa Bay. The OCSv2 consists of four sensors integrated into a Sea-Bird ...

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Time Series of Autonomous Carbonate System Parameter Measurements in Middle Tampa Bay, Florida, USA (version 3.0, March 2021)

This dataset contains carbonate system data collected by scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center to investigate the effects of carbon cycling, coastal and ocean acidification on the Tampa Bay estuary located in west central Florida, USA. These data were collected using an autonomous instrument called the Ocean Carbon System version 2 (OCSv2) deployed on the seafloor in Tampa Bay. The OCSv2 consists of four sensors integrated into a Sea-Bird ...

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Time Series of Autonomous Carbonate System Parameter Measurements in Middle Tampa Bay, Florida, USA (version 4.0, June 2022)

This dataset contains carbonate system data collected by scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center to investigate the effects of carbon cycling, coastal and ocean acidification on the Tampa Bay estuary located in west central Florida, USA. These data were collected using an autonomous instrument called the Ocean Carbon System version 2 (OCSv2) deployed on the seafloor in Tampa Bay. The OCSv2 consists of four sensors integrated into a Sea-Bird ...

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Discrete Carbonate System Parameter Measurements in Tampa Bay, Florida, USA

This dataset contains carbonate system data collected by scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center to investigate the effects of carbon cycling, coastal and ocean acidification on the Tampa Bay estuary located in west central Florida. Discrete seawater samples were collected along spatial transects at one to four hour intervals over 24-hour time periods. Water samples were analyzed at the USGS Carbon Analytical Laboratory in St. Petersburg Florida. ...

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Time Series of Autonomous Carbonate System Parameter Measurements in Tampa Bay, Florida, USA

This dataset contains carbonate system data collected by scientists from the U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center to investigate the effects of carbon cycling, coastal and ocean acidification on the Tampa Bay estuary located in west central Florida, USA. These data were collected using an autonomous instrument called the Ocean Carbon System (OCS) deployed on the seafloor in Tampa Bay. The OCS consists of five sensors integrated into a Sea-Bird Scientific (Satlantic) ...

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Wetland-Change Data Derived from Landsat Imagery, Assateague Island to Metompkin Island, Maryland and Virginia, 1984 to 2015: Wetland Persistence Analysis

This U.S. Geological Survey (USGS) data release includes geospatial datasets that were created for the analysis of Virginia and Maryland Atlantic coastal wetland changes over time. Wetland change was determined by assessing two metrics: wetland persistence and land-cover switching. Because seasonal water levels, beach width, and vegetation differences can affect change analyses, only images acquired during the spring (March, April, and May) were included in the wetland-change metrics (N=10). To assess ...

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Oceanographic Time Series Data: Northeast Atlantic Outer Continental Shelf, Gulf of Maine and Georges Bank Marine Sanctuary

Time-series oceanographic data for the Northeast Atlantic outer continental shelf, Gulf of Maine and Georges Bank collected by the U.S. Geological Survey (USGS) or used in conjunction with USGS projects. These data are stored as NetCDF files using conventions developed by National Oceanic and Atmospheric Administration (NOAA) Pacific Marine Environmental Laboratory (PMEL) lab to be compatible with their EPIC system. Variables present in the files include: ocean current, temperature, pressure, conductivity, ...

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