Remote sensing

Acquiring information about a natural feature or phenomenon, such as the Earth's surface, without actually being in contact with it. USGS remote sensing is usually carried out with airborne or spaceborne sensors or cameras.
This category is also used for airborne imaging, photogrammetry, satellite imaging, and space-borne sensing.

861 results listed by similarity [list alphabetically]
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 ...

Info
Digital image mosaics of the nearshore coastal waters of Kukio on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains an image mosaic of the Kukio area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded ...

Info
Digital image mosaic of the nearshore coastal waters of La'au Point on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the La'au Point area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Maunalua Bay on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Maunalua Bay area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of the Napili-Honokowai area on the northwest coast of Maui generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains an image mosaic of the Napili-Honokowai area on the northwest coast of Maui. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). The image mosaic has been geometrically corrected using lidar data. Also available is a lower-resolution 'browse' image, and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Pala'au on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Pala'au area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Pala'au on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Pala'au area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Portlock on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Portlock area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Puko'o on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Puko'o area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

Info
Digital shaded-relief image mosaic of the nearshore coastal waters of southcentral Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southcentral Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief ...

Info
Digital shaded-relief image mosaic of the nearshore coastal waters southeast Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southeast Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief image. ...

Info
Digital shaded-relief image mosaic of the nearshore coastal waters southwest Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a shaded-relief image mosaic of the nearshore coastal waters along southwest Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) and scanned in at 1-meter resolution. Several of the 1-meter-resolution images have been merged together and combined with lidar bathymetry data to create a large shaded-relief image. ...

Info
Digital image mosaic of the nearshore coastal waters of Umipa'a on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Umipa'a area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Waiakane on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Waiakane area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Wai'alae on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Wai'alae area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaics of the nearshore coastal waters of Waikiki on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Waikiki area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters from Waikiki to Portlock on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic from Waikiki to Portlock along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography. These five image mosaics were then combined into one larger mosaic and resampled to 1-meter resolution.

Info
Shaded-relief image mosaic of the nearshore coastal waters from Waikiki to Portlock on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic from Waikiki to Portlock along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography. These five image mosaics were then combined into one larger mosaic, resampled to 1-meter resolution, and merged with lidar bathymetry data to produce the shaded-relief image.

Info
Digital image mosaics of the nearshore coastal waters of Waikoloa on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains an image mosaic of the Waikoloa area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded ...

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
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). ...

Info
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. ...

Info
Digital image mosaics of the nearshore coastal waters of selected areas on the island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains image mosaics generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). These four image mosaics have 1.0 meter-per-pixel resolution, and intermittently cover approximately 53 km (33 mi) of shallow, coastal waters along the west, Kona coast, of the island of Hawai'i, including (from north to south) the Kawaihae, Waikoloa, Kukio, and Kailua-Kona areas. ...

Info
Digital image mosaics of the nearshore coastal waters of selected areas on the island of Maui generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains an image mosaic generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) of the Napili-Honokowai area along the northwest coast of Maui. The area is downloadable as a zip file (napili_honokowai_1m.zip) and includes a high-resolution (1.0 meter per pixel) digital image mosaic, as well as a lower-resolution 'browse' image and associated metadata.

Info
Digital image mosaics of the nearshore coastal waters of selected areas on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains digital image mosaics along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography and are presented in one zip file (oahu_1ft.zip) that also contains lower-resolution 'browse' graphics of each image mosaic area, as well as associated metadata. All of the digital image areas (from Waikiki to Portlock) were ...

Info
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 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 ...

Info
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, ...

Info
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
Shallow Along Reef Track Imaging System (sATRIS) Images – Dry Tortugas, Florida, 2009

Underwater digital images, single-beam bathymetry, and global positioning system (GPS) data were collected June 13-14, 2009 at Pulaski Shoal within Dry Tortugas National Park, Florida, USA. A total of 195,406 images of the seafloor and water column were collected along pre-defined transect lines and organized into 3 sets: track1, track2, and track3. This data release contains a subset of those images (32,135 images), all of which were used for benthic habitat classification, and contain GPS data. The data ...

Info
Shallow Along Track Reef Imaging System (sATRIS) Images – Dry Tortugas, Florida, 2011

Underwater digital images, single-beam bathymetry, and global positioning system (GPS) data were collected July 13 to July 17, 2011 within Dry Tortugas National Park, Florida, USA. A total of 272,828 images of the seafloor and water column were collected along pre-defined transect lines and organized into 14 sets, track1-track14. This data release contains a subset of those images (43,991 images), all of which were used for benthic habitat classification and contain GPS data. The data were collected using ...

Info
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 ...

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
Digital image mosaics of the nearshore coastal waters of selected areas on the island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains image mosaics generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). These four image mosaics have 1.0 meter-per-pixel resolution, and intermittently cover approximately 53 km (33 mi) of shallow, coastal waters along the west, Kona coast, of the island of Hawai'i, including (from north to south) the Kawaihae, Waikoloa, Kukio, and Kailua-Kona areas. ...

Info
Digital image mosaics of the nearshore coastal waters of selected areas on the island of Maui generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains an image mosaic generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS) of the Napili-Honokowai area along the northwest coast of Maui. The area is downloadable as a zip file (napili_honokowai_1m.zip) and includes a high-resolution (1.0 meter per pixel) digital image mosaic, as well as a lower-resolution 'browse' image and associated metadata.

Info
Digital image mosaics of the nearshore coastal waters of selected areas on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains digital image mosaics along the south coast of Moloka'i. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Pala'au, Umipa'a, Kaunakakai, Kamiloloa, Kawela, Kamalo, and Kalaeloa, were generated from 1:10K aerial photography, and are presented in one zip file (molokai_1ft.zip) that also contains lower-resolution 'browse' graphics of each image-mosaic area, as well as associated metadata. Digital mosaics at 1-meter resolution, including the ...

Info
Digital image mosaics of the nearshore coastal waters of selected areas on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains digital image mosaics along the southeast coast of O'ahu. Digital mosaics at 1-foot (0.3048-meter) resolution, including the areas of Waikiki, Diamond Head, Wai'alae, Maunalua Bay, and Portlock, were generated from 1:10K aerial photography and are presented in one zip file (oahu_1ft.zip) that also contains lower-resolution 'browse' graphics of each image mosaic area, as well as associated metadata. All of the digital image areas (from Waikiki to Portlock) were ...

Info
Digital image mosaic of the nearshore coastal waters of Diamond Head on the island of O'ahu generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel (0.3048 meter-per-pixel) resolution of the Diamond Head area on the southeast coast of O'ahu. This image mosaic was generated using digitized 1:10K natural color photographs collected by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Haleolono Point on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Haleolono Point area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

Info
Digital image mosaics of the nearshore coastal waters of Kailua-Kona on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains an image mosaic with 1.0 meter-per-pixel resolution of the Kailua-Kona area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial ...

Info
Digital image mosaics of the nearshore coastal waters of Kalaeloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kalaeloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Kamalo on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamalo area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Kamalo on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kamalo area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Kamiloloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kamiloloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Kamiloloa on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kamiloloa area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

Info
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 ...

Info
Digital image mosaic of the nearshore coastal waters of Kaunakakai on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kaunakakai area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Kaunakakai on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kaunakakai area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

Info
Digital image mosaics of the nearshore coastal waters of Kawaihae on the Island of Hawai'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains an image mosaic of the Kawaihae area on the west 'Kona' coast of the island of Hawai'i. This image mosaic was generated using digitized 1:24K natural color photographs collected in June 2000 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Two versions of the image mosaic are available--one with and one without a lidar bathymetry shaded-relief image digitally combined with the aerial photography mosaic results. The shaded ...

Info
Coastal Land-Cover Data Derived 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 ...

Info
Digital image mosaic of the nearshore coastal waters of Kawela on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1.0 foot-per-pixel resolution of the Kawela area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:10K natural color photographs collected in January 2000 by Air Survey Hawai'i, Inc. for the U.S. Geological Survey. Also available is a lower-resolution 'browse' graphic of the image mosaic area and associated metadata.

Info
Digital image mosaic of the nearshore coastal waters of Kawela on the island of Moloka'i generated using aerial photographs and SHOALS airborne lidar bathymetry data

This portion of the data release contains a digital image mosaic with 1 meter-per-pixel resolution of the Kawela area on the south coast of Moloka'i. This image mosaic was generated using digitized 1:35K natural color photographs collected in September 1993 by the National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). Also available is a lower-resolution 'browse' graphic of the image mosaic and associated metadata.

Info
Coastal Land-Cover Data Derived 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 ...

Info
Topobathy grid representing the backshore to the nearshore at Head of the Meadow Beach, Truro from data collected on March 10 and 18, 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 ...

Info
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 ...

Info
Topobathy grid representing the backshore to the nearshore environment at Marconi Beach, Wellfleet from data taken during field activity 2021-022-FA on March 10 and 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 ...

Info
Tables of file names, times, and locations of images collected during unmanned aerial systems (UAS) flights over Coast Guard Beach, Nauset Spit, Nauset Inlet, and Nauset Marsh, Cape Cod National Seashore, Eastham, Massachusetts on 1 March 2016 (text files)

These text files contain tables of the file names, times, and locations of images obtained from an unmanned aerial systems (UAS) flown in the Cape Cod National Seashore. The objective of the fieldwork was to evaluate the quality and cost of mapping from UAS images. Low-altitude (approximately 120 meters above ground level) digital images were obtained from cameras in a fixed-wing unmanned aerial vehicle (UAV) flown from the lawn adjacent to the Coast Guard Beach parking lot on 1 March, 2016. The UAV was a ...

Info
Ground control point locations associated with images collected during unmanned aerial systems (UAS) flights over Coast Guard Beach, Nauset Spit, Nauset Inlet, and Nauset Marsh, Cape Cod National Seashore, Eastham, Massachusetts on 1 March 2016 (Text file and photos)

This dataset documents the locations of ground control points associated with images obtained from unmanned aerial systems (UAS) flown in the Cape Cod National Seashore. Most of the ground control points were temporary targets placed by the U.S. Geological Survey field crew, but four were man-made features already in place, and two were points selected a posteriori from preliminary orthophotomosaics. Photographs of the four in-place features are included in this dataset, as are images showing the location ...

Info
Low-altitude aerial imagery obtained with unmanned aerial systems (UAS) flights over Coast Guard Beach, Nauset Spit, Nauset Inlet, and Nauset Marsh, Cape Cod National Seashore, Eastham, Massachusetts on 1 March 2016 (JPEG images)

This dataset contains images obtained from unmanned aerial systems (UAS) flown in the Cape Cod National Seashore. The objective of the field work was to evaluate the quality and cost of mapping from UAS images. Low-altitude (approximately 120 meters above ground level) digital images were obtained from cameras in a fixed-wing unmanned aerial vehicle (UAV) flown from the lawn adjacent to the Coast Guard Beach parking lot on 1 March, 2016. The UAV was a Skywalker X8 flying wing operated by Raptor Maps, Inc., ...

Info
Independent transect point locations (coordinates only) associated with images collected during unmanned aerial systems (UAS) flights over Coast Guard Beach, Nauset Spit, Nauset Inlet, and Nauset Marsh, Cape Cod National Seashore, Eastham, Massachusetts on 1 March 2016 (Text file)

This dataset contains the locations of independent survey points acquired on the same day that images were obtained from unmanned aerial systems (UAS) flown in the Cape Cod National Seashore. The overall objective of the field work was to evaluate the quality and cost of mapping from UAS images. Low-altitude (approximately 120 meters above ground level) digital images were obtained from cameras in a fixed-wing unmanned aerial vehicle (UAV) flown from the lawn adjacent to the Coast Guard Beach parking lot on ...

Info
Orthomosaic images from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017

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

Info
5-m backscatter mosaic from south and west of Martha's Vineyard and north of Nantucket produced from sidescan-sonar and interferometric backscatter datasets

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

Info
Location of bottom photographs along with images collected in 2012 by the U.S. Geological Survey in the Connecticut River during field activity 2012-024-FA (point shapefile and JPEG images)

A geophysical and geological survey was conducted at the mouth of the Connecticut River from Old Saybrook to Essex, Connecticut, in September 2012. Approximately 230 linear kilometers of digital Chirp subbottom (seismic-reflection) and 234-kilohertz interferometric sonar (bathymetric and backscatter) data were collected along with sediment samples, riverbed photographs, and (or) video at 88 sites within the geophysical survey area. Sediment grab samples were collected at 72 of the 88 sampling sites, video ...

Info
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 ...

Info
30-m Topography and bathymetry grid produced from swath interferometric, multibeam, and lidar datasets (navd_bath_30m Esri binary grid, UTM Zone 19N, WGS84)

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 ...

Info
10-m Bathymetry grid produced from lead-line and single-beam sonar soundings, swath interferometric, multibeam, and lidar datasets (bb_navd88_10m, Esri binary grid, UTM Zone 19N, WGS84)

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 ...

Info
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 ...

Info
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 ...

Info
10-m Bathymetry grid of Vineyard and western Nantucket Sounds produced from lead-line and single-beam sonar soundings, swath-interferometric, multibeam, and lidar datasets (Esri binary grid, 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 ...

Info
Orthomosaic images from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, July 2021

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

Info
Chimney Bluffs camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Chimney Bluffs, New York in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Chimney Bluffs State Park, New York. This data release includes images tagged with locations determined from ...

Info
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 ...

Info
True color and multispectral aerial imagery collected from UAS operations at 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 ...

Info
Location of bottom photographs along with images collected in 2014 by the U.S. Geological Survey offshore of Fire Island, NY (JPEG images and Esri point shapefile, Geographic, WGS 84)

The U.S. Geological Survey (USGS) conducted a geophysical and sampling survey in October 2014 that focused on a series of shoreface-attached ridges offshore of western Fire Island, NY. Seismic-reflection data, surficial grab samples and bottom photographs and video were collected along the lower shoreface and inner continental shelf. The purpose of this survey was to assess the impact of Hurricane Sandy on this coastal region. These data were compared to seismic-reflection and surficial sediment data ...

Info
Topobathy grid representing the backshore to the nearshore at Marconi Beach, Wellfleet from data collected on March 11 and 16, 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 ...

Info
Charles Point camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
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 ...

Info
Footprints of Lidar Datasets Published at the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center Since 2001

U.S. Geological Survey (USGS) staff created geographic information system (GIS) footprints to show the extent of light detection and ranging (lidar) datasets published by the USGS St. Petersburg Coastal and Marine Science Center (SPCMSC), since 2001. These lidar datasets were published as LAS, XYZ, or Digital Elevation Model (DEM) outputs of coastal, submerged and/or terrestrial topography in USGS Data Series (DS), Open-File Reports (OFR), and data releases (DR). Please see the publications listed in the ...

Info
Bathymetric data and grid of offshore Marconi Beach, Wellfleet, MA on March 20, 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 ...

Info
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 ...

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

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

Info
Greig Street camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
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, ...

Info
Bathymetric data and grid of offshore Head of the Meadow Beach, Truro, on March 18, 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 ...

Info
Bathymetric data and grid of offshore Head of the Meadow Beach, Truro, MA on April 7, 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 ...

Info
Lake Bluffs camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
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.

Info
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 ...

Info
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.

Info
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, ...

Info
Photomicrograph Images of Sediment Samples Collected at Crocker Reef, Florida, 2013-2014

Understanding the processes that govern whether a coral reef is accreting (growing) or dissolving are fundamental to questions of reef health and resiliency. A total of 52 surficial sediment samples were collected within a 1-km x 1-km area around Crocker Reef in the Florida Keys, USA, between 2013 and 2014. Samples 1-35 were collected in July 2013 and samples 36-52 were collected in July 2014. The samples were processed using conventional, published techniques (see process step section) to yield grain size ...

Info
Grainsize and Mineralogy Data of Sediments Samples Collected at Crocker Reef, Florida, 2013-2014

Understanding the processes that govern whether a coral reef is accreting (growing) or dissolving are fundamental to questions of reef health and resiliency. A total of 52 surficial sediment samples were collected within a 1-km x 1-km area around Crocker Reef in the Florida Keys, USA, between 2013 and 2014. Samples 1-35 were collected in July 2013 and samples 36-52 were collected in July 2014. The samples were processed using conventional, published techniques (see process step 2) to yield grain size and ...

Info
Shallow ATRIS (sATRIS) Images Crocker Reef, Florida, 2014

Underwater digital images, single-beam bathymetry, and global positioning system (GPS) data were collected June 24-25, 2014, within a 1-kilkometer (km) x 1-km area around Crocker Reef in the Florida Keys, USA. A total of 91,206 images of the seafloor and water column were collected along pre-defined transect lines and organized into three sets: track1, track2, and track3. This data release contains a subset of those images (25,485 images), all of which were used for benthic habitat classification, and ...

Info
Sodus North camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
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 ...

Info
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 ...

Info
08ACH03_last_return_metadata: EAARL Coastal Topography-Louisiana, Alabama, and Florida, June 2008

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

Info
Terrestrial-Based Lidar Beach Topography of Fire Island, New York, May 2015 - DEM data

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collected terrestrial-based light detection and ranging (T-lidar) elevation data at Fire Island, New York. The data were collected on May 18, 2015 as part of the ongoing beach monitoring within Hurricane Sandy Supplemental Project GS2-2B, and will be used to document and assess the morphological storm response and post-storm ...

Info
Terrestrial-Based Lidar Beach Topography of Fire Island, New York, May 2015 - XYZ Data

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collected terrestrial-based light detection and ranging (T-lidar) elevation data at Fire Island, New York. The data were collected on May 18, 2015 as part of the ongoing beach monitoring within Hurricane Sandy Supplemental Project GS2-2B, and will be used to document and assess the morphological storm response and post-storm ...

Info
ANGD2014_BE_z20_n88g12A_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for Coastal Topography—Anegada, British Virgin Islands, 2014

A digital elevation model (DEM) mosaic was produced for Anegada, British Virgin Islands, from remotely sensed, geographically referenced elevation measurements collected by Watershed Sciences, Inc. (WSI)/Quantum Spatial using an Optech Orion M300 (1064-nm wavelength) lidar sensor on January 21, 2014.

Info
ANGD2014_EAARLB_z20_v09g12A_metadata: Lidar-Derived Seamless (Bare Earth and Submerged) Point Cloud for Coastal Topography—Anegada, British Virgin Islands, 2014

ASCII XYZ point cloud data for a portion of the environs of Anegada, British Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected March 19-20, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The ...

Info
ANGD2014_EAARLB_z20_v09g12A_mosaic_metadata: Lidar-Derived Seamless (Bare Earth and Submerged) Digital Elevation Model (DEM) Mosaic for Coastal Topography—Anegada, British Virgin Islands, 2014

A seamless (bare earth and submerged) topography Digital Elevation Model (DEM) mosaic for a portion of the submerged environs of Anegada, British Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected March 19-20, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ...

Info
ASIS2015_HRJQ_BE_z18_n88g12B_classified_metadata: Lidar-Derived Classified Bare-Earth Point-Cloud for Coastal Topography—Assateague Island, Maryland and Virginia, Post-Hurricane Joaquin, 26 November 2015

Binary point-cloud data were produced for Assateague Island, Maryland and Virginia, post-Hurricane Joaquin, from remotely sensed, geographically referenced elevation measurements collected by Quantum Spatial using a Leica ALS70 (1064-nm wavelength) lidar sensor.

Info
BITH2014_BeaumontLNRUnits_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Beaumont and Lower Neches River Units, Texas, 2014

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Beaumont and Lower Neches River Units of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 22, 23, 25, 26, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced ...

Info
BITH2014_BeaumontLNRUnits_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Beaumont and Lower Neches River Units, Texas, 2014

A first-surface topography Digital Elevation Model (DEM) mosaic for the Beaumont and Lower Neches River Units of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 22, 23, 25, 26, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental ...

Info
BITH2014_BigSandyCreekCorridorUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Corridor Unit, Texas, 2014

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Big Sandy Creek Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 29, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a ...

Info
Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012: Lidar point-cloud data (LAS)

Binary point-cloud data were produced for a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines, post-Hurricane Sandy (Sandy was an October 2012 hurricane that made landfall as an extratropical cyclone on the 29th), from remotely sensed, geographically referenced elevation measurements collected by Photo Science, Inc. (Delaware, Maryland, Virginia, and North Carolina) and Woolpert, Inc. (Fire Island, New York) using airborne lidar sensors.

Info
Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012: Lidar and digital elevation model (DEM) tile index

This data represents the tile index for lidar data collected for the U.S. Geological Survey in November 2012 following Hurricane Sandy, which made landfall in the eastern United States on October 29th, 2012. The lidar LAS and derived-digital elevation model (DEM) data are divided into these tiles and filenames match the tile number. The index shows the extent of data collection (portions of the coastline of New York, Delaware, Maryland, Virginia, and North Carolina) and provides tile names to aid in ...

Info
BITH2014_BigSandyCreekCorridorUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Corridor Unit, Texas, 2014

A first-surface topography Digital Elevation Model (DEM) mosaic for the Big Sandy Creek Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 29, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B) ...

Info
BITH2014_BigSandyCreekUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Unit, Texas, 2014

A bare-earth topography digital elevation model (DEM) mosaic for the Big Sandy Creek Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ranging ...

Info
BITH2014_BigSandyCreekUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Big Sandy Creek Unit, Texas, 2014

A first-surface topography digital elevation model (DEM) mosaic for the Big Sandy Creek Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ...

Info
BITH2014_CanyonlandsUNRCorridorUnits_EAARLB_BE_z15_n88g12A_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for EAARL-B Topography—Big Thicket National Preserve: Canyonlands and Upper Neches River Corridor Units, Texas, 2014

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Canyonlands and Upper Neches River Corridor Units of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 21, 23, 25, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced ...

Info
BITH2014_LanceRosierUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Lance Rosier Unit, Texas, 2014

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Lance Rosier Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 15, 21, 22, 25, 26, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed ...

Info
BITH2014_LanceRosierUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Lance Rosier Unit, Texas, 2014

A first-surface topography Digital Elevation Model (DEM) mosaic for the Lance Rosier Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 15, 21, 22, 25, 26, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a ...

Info
BITH2014_LittlePineIslandBayouCorridorUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for EAARL-B Topography—Big Thicket National Preserve: Little Pine Island Bayou Corridor Unit, Texas, 2014

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Little Pine Island Bayou Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 15, 21, 22, 26, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar ...

Info
BITH2014_LittlePineIslandBayouCorridorUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: Lidar-Derived First-Surface Digital Elevation Model (DEM) Mosaic for EAARL-B Topography—Big Thicket National Preserve: Little Pine Island Bayou Corridor Unit, Texas, 2014

A first-surface topography Digital Elevation Model (DEM) mosaic for the Little Pine Island Bayou Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 15, 21, 22, 26, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar ...

Info
Beach Topography—Fire Island, New York, Post-Hurricane Sandy, April 2013: Ground Based Lidar (ASCII XYZ Point Data)

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in Florida and the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina, collaborated to gather alongshore ground-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on April 10, 2013, to characterize beach topography following substantial erosion that occurred during Hurricane Sandy, which made landfall on October 29, 2012, and multiple, ...

Info
BITH2014_LowerNechesRiverCorridorUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Lower Neches River Corridor Unit, Texas, 2014

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Lower Neches River Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 23, 25, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne ...

Info
BITH2014_LowerNechesRiverCorridorUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Lower Neches River Corridor Unit, Texas, 2014

A first-surface topography Digital Surface Model (DSM) mosaic for the Lower Neches River Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 19, 21, 23, 25, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne ...

Info
BITH2014_MenardCreekCorridorUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Menard Creek Corridor Unit, Texas, 2014

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Menard Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 21 and 22, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging ...

Info
National Assessment of Hurricane-Induced Coastal Erosion Hazards: Gulf of Mexico Bradenton Beach to Clearwater Beach, Florida Mean (interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines mean beach slopes along the United States Southeast Gulf of Mexico from Bradenton Beach to Clearwater Beach, Florida for data collected at various times between 1998 and 2010.

Info
National Assessment of Hurricane-Induced Coastal Erosion Hazards: Gulf of Mexico Bradenton Beach to Clearwater Beach, Florida Raw (non-interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines beach slopes along the United States Southeast Gulf of Mexico from Bradenton Beach to Clearwater Beach, Florida for data collected at various times between 1998 and 2010.

Info
BITH2014_MenardCreekCorridorUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Menard Creek Corridor Unit, Texas, 2014

A first-surface topography Digital Surface Model (DSM) mosaic for the Menard Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 21 and 22, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging ...

Info
BITH2014_NBJGBUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Neches Bottom and Jack Lore Baygall Unit, Texas, 2014

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Neches Bottom and Jack Lore Baygall Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 21, 23, 25, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne ...

Info
BITH2014_NBJGBUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Neches Bottom and Jack Lore Baygall Unit, Texas, 2014

A first-surface topography Digital Elevation Model (DEM) mosaic for the Neches Bottom and Jack Lore Baygall Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 21, 23, 25, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne ...

Info
BITH2014_TurkeyCreekUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Turkey Creek Unit, Texas, 2014

A bare-earth topography digital elevation model (DEM) mosaic for the Turkey Creek Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 25, 26, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed ...

Info
Massachusetts Mean (interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines mean beach slopes for Massachusetts for data collected at various times between 2000 and 2013.

Info
Massachusetts raw (non-interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines beach slopes along the United States Northeast Atlantic Ocean for Massachusetts for data collected at various times between 2000 and 2013

Info
BITH2014_TurkeyCreekUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Turkey Creek Unit, Texas, 2014

A first-surface topography digital elevation model (DEM) mosaic for the Turkey Creek Unit of Big Thicket National Preserve in Texas, was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 25, 26, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a ...

Info
BITH2014_VillageCreekCorridorUnit_EAARLB_BE_z15_n88g12A_mosaic_metadata: EAARL-B Topography-Big Thicket National Preserve: Village Creek Corridor Unit, Texas, 2014

A bare-earth topography Digital Elevation Model (DEM) mosaic for the Village Creek Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 23, 26, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL ...

Info
Topographic Lidar Survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013 -- Classified Point Data

A topographic lidar survey was conducted July 12-14, 2013 over Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana. Lidar data exchange format (LAS) 1.2 formatted classified point data files were generated based on these data. Photo Science, Inc. was contracted by the U.S. Geological Survey (USGS) to collect and process the lidar data. The lidar data were collected at a nominal pulse spacing (NPS) of 1.0 meter (m). The horizontal projection and datum of the data are ...

Info
BITH2014_VillageCreekCorridorUnit_EAARLB_FS_z15_n88g12A_mosaic_metadata: EAARL-B Topography—Big Thicket National Preserve: Village Creek Corridor Unit, Texas, 2014

A first-surface topography Digital Surface Model (DSM) mosaic for the Village Creek Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 19, 21, 22, 23, 26, 27, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar ...

Info
Topographic Lidar Survey of the Alabama, Mississippi, and Southeast Louisiana Barrier Islands, from September 5 to October 11, 2012 -- Classified Point Data

This Data Series Report contains lidar elevation data collected September 5 to October 11, 2012, for the barrier islands of Alabama, Mississippi and southeast Louisiana, including the coast near Port Fourchon. Most of the data were collected September 5-10, 2012, with a reflight conducted on October 11, 2012, to increase point density in some areas. Lidar data exchange format (LAS) 1.2 formatted point data files were generated based on these data. The point cloud data were processed to extract bare earth ...

Info
Topobathymetric Lidar Survey of Breton and Gosier Islands, Louisiana, January 16 and 18, 2014 - Point-cloud Data

This dataset contains binary point-cloud data, produced from remotely sensed, geographically referenced topobathymetric measurements collected by Photo Science, Inc., encompassing the Breton and Gosier Island, LA study areas. The original area of interest was buffered by 100 meters to ensure complete coverage, resulting in approximately 75 square miles of lidar data. The Breton Island Lidar project called for the planning, acquisition, processing, and derivative products of topobathymetric lidar data, ...

Info
Topographic Lidar Survey of the Chandeleur Islands, Louisiana, February 6, 2012 -- Classified Point Data

This Data Series Report contains lidar elevation data collected February 6, 2012, over the Chandeleur Islands, Louisiana. LAS 1.2 formatted point data files were generated based on these data. The point cloud data were processed to extract bare earth data; therefore, the point cloud data are classified into only these classes: 1 and 17-unclassified, 2-ground, 9-water, and 10-breakline proximity. Digital Aerial Solutions, LLC, was contracted by the USGS to collect and process these data. The lidar data were ...

Info
National Assessment of Hurricane-Induced Coastal Erosion Hazards: Southeast Atlantic Salvo to Duck, North Carolina Mean (interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives features of beach morphology from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines mean beach slopes along the United States Southeast Atlantic Ocean from Salvo to Duck, North Carolina for data collected at various times between 1996 and 2012.

Info
National Assessment of Hurricane-Induced Coastal Erosion Hazards: Southeast Atlantic Salvo to Duck, North Carolina Raw (non-interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives features of beach morphology from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines beach slopes along the United States Southeast Atlantic Ocean from Salvo to Duck, North Carolina for data collected at various times between 1996 and 2012.

Info
New Jersey Mean (interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines mean beach slopes for New Jersey for data collected at various times between 2007 and 2014.

Info
New Jersey raw (non-interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines beach slopes along the United States Northeast Atlantic Ocean for New Jersey for data collected at various times between 2007 and 2014

Info
ds765_General_metadata: Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012

Derived products of a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines, post-Hurricane Sandy (Sandy was an October 2012 hurricane that made landfall as an extratropical cyclone on the 29th), were produced by the U.S. Geological Survey (USGS) from remotely sensed, geographically referenced elevation measurements collected by Photo Science, Inc. (Delaware, Maryland, Virgina, and North Carolina) and Woolpert, Inc. (Fire Island, New York) using airborne lidar sensors. Post ...

Info
ds765_metadata: Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012

Dune features (dune crest and toe elevations) and mean-high-water shoreline data for a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines, post-Hurricane Sandy (Sandy was an October 2012 hurricane that made landfall as an extratropical cyclone on the 29th), were produced by the U.S. Geological Survey (USGS) from remotely sensed, geographically referenced elevation measurements collected by Photo Science and Woolpert using using airborne lidar sensors. Binary point-cloud ...

Info
DS888-metadata: EAARL-B Coastal Topography—Fire Island, New York, pre-Hurricane Sandy, 2012: Seamless (Bare Earth and Submerged)

American Standard Code Information Interchange XYZ and binary point-cloud data, as well as a seamless (bare-earth and submerged) digital elevation model for part of Fire Island, New York, pre-Hurricane Sandy (October 2012 hurricane), were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ranging system ...

Info
FIIS2002_EAARLA_BE_z18_n88g99_metadata: Lidar-Derived Bare-Earth XYZ for EAARL Coastal Topography—Fire Island, New York, 2002

ASCII XYZ data for Fire Island, New York, was produced from remotely sensed, geographically referenced elevation measurements collected October 25 and November 8, 2002 by the U.S. Geological Survey, in cooperation with the National Park Service (NPS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the first-generation Experimental Advanced Airborne Research Lidar (EAARL-A), a pulsed laser ranging system mounted onboard an aircraft to ...

Info
1-meter resolution image mosaic representing sidescan sonar data collected by the U.S. Geological Survey during field activity 2016-030-FA offshore Sandwich Beach, MA in June 2016 (24-bit GeoTIFF, UTM Zone 19N, NAD83-HARN)

The objectives of the survey were to provide bathymetric and sidescan sonar data for sediment transport studies and coastal change model development for ongoing studies of nearshore coastal dynamics along Sandwich Town Neck Beach, MA. Data collection equipment used for this investigation are mounted on an unmanned surface vehicle (USV) uniquely adapted from a commercially sold gas-powered kayak and termed the "jetyak". The jetyak design is the result of a collaborative effort between USGS and Woods Hole ...

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

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

Info
4-meter resolution bathymetric grid representing single beam data collected by the U.S. Geological Survey during field activity 2016-030-FA offshore Sandwich Beach, MA in June 2016 (32-bit GeoTIFF, UTM Zone 19N, NAD83-HARN)

The objectives of the survey were to provide bathymetric and sidescan sonar data for sediment transport studies and coastal change model development for ongoing studies of nearshore coastal dynamics along Sandwich Town Neck Beach, MA. Data collection equipment used for this investigation are mounted on an unmanned surface vehicle (USV) uniquely adapted from a commercially sold gas-powered kayak and termed the "jetyak". The jetyak design is the result of a collaborative effort between USGS and Woods Hole ...

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

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

Info
Bathymetric data and grid of offshore Marconi Beach, Wellfleet, MA on April 23, 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 ...

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

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

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

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

Info
Shallow ATRIS Seafloor Images - West Turtle Shoal Patch Reef, Rawa PatchReef, Dustan Rocks Patch Reef, and Thor Patch Reef, Florida, 2011

Underwater digital images, single-beam bathymetry, and global-positioning system (GPS) data were collected September 29-30, 2011 around Dustan Rocks Patch Reef, Thor Patch Reef, West Turtle Shoal Patch Reef, and Rawa Patch Reef in the Florida Keys. A total of 101,734 images were collected, covering 4672 square meteres (m2) of reef habitat. This data release contains a subset of 1,420 images, organized into four sets: Track1, Track2, Track3, and Track4. These images were used for coral bleaching assessments ...

Info
CRKR2014_EAARLB_z17_n88g12A_metadata: EAARL-B Submerged Topography—Crocker Reef, Florida, 2014

ASCII XYZ point cloud data for a portion of the submerged environs of Crocker Reef, Florida, were produced from remotely sensed, geographically referenced elevation measurements collected on April 13 and 22, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. ...

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

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

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

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

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

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

Info
National Assessment of Hurricane-Induced Coastal Erosion Hazards: Southeast Atlantic Miami to Jupiter, Florida Mean (interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines mean beach slopes along the United States Southeast Atlantic Ocean from Miami to Jupiter, Florida for data collected at various times between 1999 and 2009.

Info
National Assessment of Hurricane-Induced Coastal Erosion Hazards: Southeast Atlantic Miami to Jupiter, Florida Raw (non-interpolated) Beach Slope Point Data

The National Assessment of Coastal Change Hazards project derives beach morphology features from lidar elevation data for the purpose of understanding and predicting storm impacts to our nation's coastlines. This dataset defines beach slopes along the United States Southeast Atlantic Ocean from Miami to Jupiter, Florida for data collected at various times between 1999 and 2009.

Info
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 ...

Info
Footprints and producers of source data used to create central portion of the high-resolution (1 m) San Francisco Bay, California, digital elevation model (DEM)

Polygon shapefile showing the footprint boundaries, source agency origins, and resolutions of compiled bathymetric digital elevation models (DEMs) used to construct a continuous, high-resolution DEM of the central portion of San Francisco Bay.

Info
Image showing bathymetry data for the coastal region of Rincon, Puerto Rico (rincon_lidar.tif)

These data were collected by the SHOALS (Scanning Hydrographic Operational Airborne Lidar Survey) system which consists of an airborne laser transmitter/receiver capable of measuring 400 soundings per second. The system operates from a deHavilland DHC-6 Twin Otter flying at altitudes between 200 and 400 meters with a ground speed of about 100 knots. The SHOALS system also includes a ground-based data processing system for calculating acurate horizontal position and water depth. Lidar is an acronym for ...

Info
4-m Grid of Combined Multibeam and LIDAR Bathymetry from National Oceanic and Atmospheric Administration (NOAA) Surveys H11442 and H11225 offshore of Niantic, Connecticut (NIANTIC_GEO, 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. ...

Info
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. ...

Info
4-m Grid of Combined Multibeam and LIDAR Bathymetry from National Oceanic and Atmospheric Administration (NOAA) Surveys H11441, H11442, H11224, and H11225 offshore of New London and Niantic, Connecticut (NLNB_GEO, 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. ...

Info
Color Shaded-Relief GeoTIFF Image Showing the Combined 4-m Multibeam and LIDAR Bathymetry Generated from National Oceanic and Atmospheric Administration (NOAA) Surveys H11442, H11441, H11224, and H11225 Offshore of New London and Niantic, CT (NLNB_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. ...

Info
4-m Grid of Combined Multibeam and LIDAR Bathymetry from National Oceanic and Atmospheric Administration (NOAA) Surveys H11441, H11442, H11224, and H11225 offshore of New London and Niantic, Connecticut (NLNB_UTM, UTM Zone 18, NAD83)

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. ...

Info
4-m Grid of Combined Multibeam and LIDAR Bathymetry from National Oceanic and Atmospheric Administration (NOAA) Surveys H11441 and H11224 offshore of New London, Connecticut (NLONDON_GEO, 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. ...

Info
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. ...

Info
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 ...

Info
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 ...

Info
4-m Grid of the Combined 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_GEO, 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 ...

Info
4-m Grid of the Combined 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_UTM, 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 ...

Info
True color and multispectral ortho products created from UAS operations at 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 ...

Info
Footprints and producers of source data used to create northern portion of the high-resolution (1 m) San Francisco Bay, California, digital elevation model (DEM)

Polygon shapefile showing the footprint boundaries, source agency origins, and resolutions of compiled bathymetric digital elevation models (DEMs) used to construct a continuous, high-resolution DEM of the northern portion of San Francisco Bay.

Info
Digital elevation model (DEM) of northern San Francisco Bay, California, created using bathymetry data collected between 1999 and 2016 (MLLW)

A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the northern portion of San Francisco Bay, which includes San Pablo Bay, Carquinez Strait, and portions of Suisun Bay, was constructed from bathymetric surveys collected from 1999 to 2016. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and ...

Info
Digital elevation model (DEM) of northern San Francisco Bay, California, created using bathymetry data collected between 1999 and 2016 (NAVD88)

A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the northern portion of San Francisco Bay, which includes San Pablo Bay, Carquinez Strait, and portions of Suisun Bay, was constructed from bathymetric surveys collected from 1999 to 2016. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and ...

Info
Orthophotomosaic images (natural color) of the north coast of Barter Island, Alaska acquired on July 05 2015 (GeoTIFF image; 8-cm resolution)

Aerial photographs were collected from a small, fixed-wing aircraft over the coast of Barter Island, Alaska on July 05 2015. Precise aircraft position information and structure-from-motion photogrammetric methods were combined to a derive high-resolution orthophotomosaic. This orthophotomosaic contain 3-band, 8-bit, unsigned raster data (red/green/blue; file format-GeoTIFF) with a ground sample distance (GSD) resolution of 8 cm. The file employs Lempel-Ziv-Welch (LZW) compression. This orthophotomosaic was ...

Info
Lidar_MHW_Shorelines_1998_2014.shp - Mean High Water (MHW) Shorelines Extracted from Lidar Data for Dauphin Island, Alabama from 1998 to 2014.

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

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

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

Info
Orthomosaic images from UAS surveys of the upper reservoir delta at Jenkinson Lake, El Dorado County, California

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

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

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

Info
08ACH03_first_return_metadata: EAARL Coastal Topography-Louisiana, Alabama, and Florida, June 2008

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

Info
CENCAL1853_1910 - Vectorized Shoreline of Central California Derived from 1853-1910 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

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

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

Info
CENCAL1929_1942 - Vectorized Shoreline of Central Califonia Derived from 1929-1942 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

Info
CENCAL1945_1976 - Vectorized Shoreline of Central California Derived from 1945-1976 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

Info
CENCAL_1998_2002 - Vectorized Shoreline of Central California Derived from 1998-2002 Lidar Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

Info
ASIS2015_HRJQ_BE_z18_n88g12B_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for Coastal Topography—Assateague Island, Maryland and Virginia, Post-Hurricane Joaquin, 26 November 2015

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

Info
BITH2014_CanyonlandsUNRCorridorUnits_EAARLB_FS_z15_n88g12A_mosaic_metadata: Lidar-derived First-Surface Digital Elevation Model (DEM) Mosaic for EAARL-B Topography—Big Thicket National Preserve: Canyonlands and Upper Neches River Corridor Units, Texas, 2014

A first-surface topography Digital Elevation Model (DEM) mosaic for the Canyonlands and Upper Neches River Corridor Units of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 11, 15, 17, 18, 21, 23, 25, and 29, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced ...

Info
CACO2002_EAARLA_BE_z19_n88g12B_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: Bare Earth

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

Info
CACO2002_EAARLA_BE_z19_n88g12B_mosaic_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: Bare Earth

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

Info
CACO2002_EAARLA_FS_z19_n88g12B_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: First Surface

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

Info
CACO2002_EAARLA_FS_z19_n88g12B_mosaic_metadata: EAARL Coastal Topography--Cape Cod National Seashore, Massachusetts, 2002: First Surface

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

Info
NORCAL1854_1880 - Vectorized Shoreline of Northern California from 1854-1880 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

Info
NORCAL1928_1936 - Vectorized Shoreline of Northern California Derived from 1928-1936 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a compilation of data from one or ...

Info
NORCAL1952_1971 - Vectorized Shoreline of Northern California Derived from 1952-1971 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

Info
NORCAL2002 - Vectorized Shoreline of Northern California Derived from 2002 Lidar Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

Info
CSV file of names, times, and locations of images collected by an unmanned aerial system (UAS) flying over Black Beach, Falmouth, Massachusetts on 18 March 2016

Imagery acquired with unmanned aerial systems (UAS) and coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Survey worked in collaboration with members of the Marine Biological Laboratory and Woods Hole Analytics at Black ...

Info
Low-altitude aerial imagery obtained with unmanned aerial systems (UAS) flights over Black Beach, Falmouth, Massachusetts on 18 March 2016 (JPEG images)

Imagery acquired with unmanned aerial systems (UAS) and coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Survey worked in collaboration with members of the Marine Biological Laboratory and Woods Hole Analytics at Black ...

Info
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 ...

Info
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 ...

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

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

Info
CRKR2014_EAARLB_z17_n88g12A_mosaic_metadata: EAARL-B Submerged Topography—Crocker Reef, Florida, 2014

A submerged topography digital elevation model (DEM) mosaic for a portion of the submerged environs of Crocker Reef, Florida, was produced from remotely sensed, geographically referenced elevation measurements collected on April 13 and 22, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation ...

Info
EasternLA2008_EAARLA_BE_n88g03_metadata: EAARL Coastal Topography–Eastern Louisiana Barrier Islands, 09 March 2008: Bare Earth

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

Info
EasternLA2008_EAARLA_BE_n88g03_mosaic_metadata: EAARL Coastal Topography–Eastern Louisiana Barrier Islands, 09 March 2008: Bare Earth

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

Info
FIIS2002_EAARLA_BE_z18_n88g99_mosaic_metadata: Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for EAARL Coastal Topography—Fire Island, New York, 2002

A digital elevation model (DEM) mosaic for Fire Island, New York, was produced from remotely sensed, geographically referenced elevation measurements collected October 25 and November 8, 2002 by the U.S. Geological Survey, in cooperation with the National Park Service (NPS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the first-generation Experimental Advanced Airborne Research Lidar (EAARL-A), a pulsed laser ranging system mounted ...

Info
SOCAL1852_1889 - Vectorized Shoreline of Southern California Derived from 1852-1889 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

Info
SOCAL1920_1934 - Vectorized Shoreline of Southern California Derived from 1920-1934 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

Info
SOCAL_1971_1976 - Vectorized Shoreline of Southern California Derived from 1971-1976 Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

Info
SOCAL_1998 - Vectorized Shoreline of Southern California Derived from 1998 Lidar Source Data

There are critical needs for a nationwide compilation of reliable shoreline data. To meet these needs, the U.S. Geological Survey (USGS) has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. Each shoreline may represent a ...

Info
KEYS2016_SM_z17_n88g12B_classified_metadata: Coastal Topography-Upper Florida Keys Reef Tract, Florida, 26-30 June 2016

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

Info
KEYS2016_SM_z17_n88g12B_mosaic_metadata: Coastal Topography-Upper Florida Keys Reef Tract, Florida, 26-30 June 2016

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

Info
LINY2011_HRIR_BE_z18_n88g09_classified_metadata: Coastal Topography—Long Island, New York, Post-Hurricane Irene, 30 August 2011

Binary point-cloud data were produced for Long Island, New York, from remotely sensed, geographically referenced elevation measurements collected by Woolpert, Inc. using an Leica ALS50-II lidar sensor flown on a Cessna 404 aircraft. These data were collected post-Hurricane Irene on August 30, 2011.

Info
LINY2011_HRIR_BE_z18_n88g09_mosaic_metadata: Coastal Topography—Long Island, New York, Post-Hurricane Irene, 30 August 2011

A digital elevation model (DEM) mosaic was produced for Long Island, New York, from remotely sensed, geographically referenced elevation measurements collected by Woolpert, Inc. using an Leica ALS50-II lidar sensor flown on a Cessna 404 aircraft. These data were collected post-Hurricane Irene on August 30, 2011.

Info
STCR2014_EAARLB_v09g12B_metadata: EAARL-B Submerged Topography–Saint Croix, U.S. Virgin Islands, 2014

ASCII XYZ point cloud data for a portion of the submerged environs of Saint Croix, U.S. Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected on March 11, 19, and 21, 2014 by the U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration (NOAA) Coral Reef Conservation Program. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a ...

Info
STCR2014_EAARLB_v09g12B_mosaic_metadata: EAARL-B Submerged Topography–Saint Croix, U.S. Virgin Islands, 2014

A submerged topography Digital Elevation Model (DEM) mosaic for a portion of the submerged environs of Saint Croix, U.S. Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected on March 11, 19, and 21, 2014 by the U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration (NOAA) Coral Reef Conservation Program. Elevation measurements were collected over the area using the second-generation Experimental Advanced ...

Info
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.

Info
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 ...

Info
Multispectral aerial imagery collected during uncrewed aircraft systems (UAS) operations: Plum Island Estuary and Parker River NWR (PIEPR), Massachusetts, November 14, 2017 and March 28, 2019

Low-altitude (80 and 100 meters above ground level) digital images were collected by the USGS Woods Hole Coastal and Marine Science Center (WHCMSC) Aerial Imaging and Mapping Group (AIMG) over an area of the Plum Island Estuary and Parker River National Wildlife Refuge (NWR) in Massachusetts on November 14, 2017 and March 28, 2019 to document marsh stability over time and quantify sediment movement. A 3DR Solo uncrewed aircraft systems (UAS) was equipped with either a Ricoh GR II digital camera for true ...

Info
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 ...

Info
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 ...

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

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

Info
Orthomosaic images of the middle and lower Elwha River, Washington, 2012 to 2017

This dataset presents 28 georeferenced orthomosaic images of the middle and lower reaches of the Elwha River. Each mosaic image was created by stitching together thousands of individual photographs that were matched based on numerous unique tie points shared by the photographs. The individual photographs were taken by a plane-mounted camera during multiple flights over the study area spanning 2012 to 2017. Because each mosaic is orthogonal to the earth's surface and is georeferenced to real-world ...

Info
Bathymetric grid representing single beam data during field activity 2020-015-FA offshore Head of the Meadow Beach, Truro MA on March 10, 2020

The data in this release map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide environmental context for the camera calibration information for the 2019 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2020-015-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 the CoastCam, which are ...

Info
Digital surface model representing Head of the Meadow Beach, Truro from images taken during field activity 2020-015-FA on March 6, 2020

The data in this release map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide environmental context for the camera calibration information for the 2019 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2020-015-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 the CoastCam, which are ...

Info
True color aerial imagery collected during uncrewed aircraft systems (UAS) operations: Plum Island Estuary and Parker River NWR (PIEPR), Massachusetts, November 14, 2017 and March 28, 2019

Low-altitude (80 and 100 meters above ground level) digital images were collected by the USGS Woods Hole Coastal and Marine Science Center (WHCMSC) Aerial Imaging and Mapping Group (AIMG) over an area of the Plum Island Estuary and Parker River National Wildlife Refuge (NWR) in Massachusetts on November 14, 2017 and March 28, 2019 to document marsh stability over time and quantify sediment movement. A 3DR Solo uncrewed aircraft systems (UAS) was equipped with either a Ricoh GR II digital camera for true ...

Info
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 ...

Info
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 ...

Info
Beach Topography—Fire Island, New York, Post-Hurricane Sandy, April 2014: Ground Based Lidar (ASCII XYZ Point Data)

The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) and the U.S. Army Corps of Engineers Field Research Facility (USACE-FRF) of Duck, NC collaborated to gather alongshore ground-based lidar beach topography at Fire Island, NY. This high-resolution elevation dataset was collected on April 1, 2014, and is part of the USGS's ongoing beach monitoring effort under Hurricane Sandy Supplemental Project GS2-2B. This USGS Data Release includes the resulting processed elevation ...

Info
Lidar Bathymetry Data of Cape Canaveral, Florida, (2014) in XYZ ASCII text file format

The Cape Canaveral Coastal System (CCCS) is a prominent feature along the Southeast U.S. coastline and is the only large cape south of Cape Fear, North Carolina. Most of the CCCS lies within the Merritt Island National Wildlife Refuge and included in its boundaries are the Cape Canaveral Air Force Station (CCAFS), NASA’s Kennedy Space Center (KSC), and a large portion of Canaveral National Seashore. The actual promontory of the modern cape falls within the jurisdictional boundaries of the CCAFS. These ...

Info
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 ...

Info
Bathymetric data and grid of offshore Head of the Meadow Beach, Truro, MA on February 9, 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. ...

Info
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 ...

Info
Topobathy grid representing the backshore to the nearshore at Head of the Meadow Beach, Truro from data taken during field activity 2020-015-FA on March 6 and 10, 2020

The data in this release map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide environmental context for the camera calibration information for the 2019 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2020-015-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 the CoastCam, which are ...

Info
Bathymetric data during field activity 2021-014-FA offshore Head of the Meadow Beach, Truro MA on February 11, 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 ...

Info
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 ...

Info
Aerial imagery from UAS survey of the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23

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

Info
Single-beam bathymetric data in Pea Island National Wildlife Refuge, North Carolina in November 2020 and April, September, and October 2021

The data in this part of the release are bathymetry data collected in the nearshore using single-beam echosounders mounted on surf capable self-righting electric autonomous survey vehicles at the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge (PINWR) and at the Basnight Bridge (BB), NC. In November 2020, April, September, and October 2021, USGS and Woods Hole Oceanographic Institute (WHOI) scientists conducted multiple field surveys to collect the bathymetry as ...

Info
Digital surface model (DSM) for the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23

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

Info
Ground control point locations for UAS survey of the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23

This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during the Unmanned Aerial System (UAS) survey on of the Liberty Island Conservation Bank Wildlands restoration site in the Sacramento-San Joaquin Delta on 2018-10-23. The GCPs were used to establish ground control for the survey and consisted of 24 small (80 x 80 centimeter) square tarps with black-and-white cross patterns placed ...

Info
Orthomosaic imagery for the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23

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

Info
Seafloor character from lidar data-Santa Barbara Channel

Seafloor character was derived from interpretations of lidar data available for the mainland coast within the study area from the California State Waters Mapping Program (Johnson and others, 2012; Johnson and others, 2013a; Johnson and others, 2013b; Johnson and others, 2013c). The number of substrate classes was reduced because rugosity could not be derived for all areas. References Cited: Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Greene, H.G., Krigsman, L ...

Info
Topographic point cloud for the Liberty Island Conservation Bank Wildlands restoration site, Sacramento-San Joaquin Delta, California, 2018-10-23

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

Info
St. Petersburg Coastal and Marine Science Center Geoscience Data Viewer Metadata

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

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
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 ...

Info
Braddock East camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ...

Info
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 ...

Info
Topobathy grid representing the backshore to the nearshore environment at Head of the Meadow Beach, Truro from data collected during field activity 2021-014-FA on February 4 and 11, 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 ...

Info
Bathymetric data and grid representing single-beam data offshore Marconi Beach, Wellfleet, MA on March 16, 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 ...

Info
Braddock West camera locations and attitudes for low-altitude aerial images collected during unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ...

Info
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 ...

Info
Structure-from-Motion point clouds from the Florida Keys, 2019

Structure-from-Motion (SfM) point clouds were created from seafloor images collected using the new 5-camera system SfM Quantitative Underwater Imaging Device with Five Cameras (SQUID-5). Images were collected in July 2019 by towing the SQUID-5 in 3 to 4 meters of water off of Islamorada in the Florida Keys during 3 days. The five cameras were synchronized together and with a survey-grade Global Positioning System (GPS). Images were collected over diverse benthic settings, including living and senile reefs, ...

Info
Structure-from-Motion underwater photos from the Florida Keys, 2019

Underwater photos were collected using a new 5-camera system, the Structure-from-Motion (SfM) Quantitative Underwater Imaging Device with Five Cameras (SQUID-5). Images were collected in July 2019 by towing the SQUID-5 in 3 to 4 meters of water off of Islamorada in the Florida Keys. The five cameras were synchronized together and with a survey-grade Global Positioning System (GPS). Images were collected over diverse benthic settings, including living and senile reefs, rubble, and sand. The images are ...

Info
Structure-from-Motion (SfM) surface models derived from seafloor video from the Channel Islands, California

Structure-from-Motion (SfM) surface models were created using seafloor video collected over a visible fault scarp in the Channel Islands, California, during a 2016 U.S. Geological Survey (USGS) field activity. Four SfM surface models were created, each with a different combination of locating, scaling, and optimizing methods. Video imagery was collected using the USGS Pacific Coastal and Marine Science Center's BOBSled, equipped with high-definition (720p) video cameras (video published in Coastal and ...

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

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

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

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

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

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

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
Topographic digital surface model (DSM) for Whiskeytown Lake and surrounding area, 2018-12-02

This portion of the data release presents a digital surface model (DSM) and hillshade of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2018-12-02. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been removed from the data. In addition, data artifacts resulting from noise and vegetation in the original ...

Info
Orthomosaic imagery for Whiskeytown Lake and surrounding area, northern California, 2018-12-02

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

Info
Topographic digital surface model (DSM) for Whiskeytown Lake and surrounding area, 2019-06-03

This portion of the data release presents a digital surface model (DSM) and hillshade of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2019-06-03. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been removed from the data. In addition, data artifacts resulting from noise and vegetation in the original ...

Info
Orthomosaic imagery for Whiskeytown Lake and surrounding area, expanded AOI, 2019-06-03

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

Info
Orthomosaic imagery for Whiskeytown Lake and surrounding area, 2019-06-03

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

Info
Topographic digital surface model (DSM) for Whiskeytown Lake and surrounding area, 2020-11-10

This portion of the data release presents a digital surface model (DSM) and hillshade of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2020-11-10. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been removed from the data. In addition, data artifacts resulting from noise and vegetation in the original ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

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

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

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

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

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

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

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

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

Info
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 ...

Info
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 ...

Info
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 ...

Info
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) ...

Info
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 ...

Info
NANP1M.TIF - North Anacapa Passage sidescan sonar backscatter image in nearshore Benthic Habitat mapping Project S. California map Series. (UTM 10N, NAD83)

The sidescan sonar image of the nearshore seafloor (0 to 100 m water depths) of the North Anacapa Passage area was mosaicked from data collected in 2000. A Klein 2000 sidescan system was used for geophysical surveying. A Triton Elics Isis brand side-scan data recording system was used on the cruise. The 1998 survey was navigated with a Leica Differential Global Positioning System (DGPS) which provided a ship position with accuracy of 1-5 m in DGPS mode. At times during the cruise differential signal was ...

Info
SANA1M.TIF - South Anacapa Island sidescan sonar backscatter image in nearshore Benthic Habitat mapping Project S. California map Series. (UTM 10N, NAD83)

The sidescan sonar image of the nearshore seafloor (0 to 100 m water depths) of the South Anacapa area was mosaicked from data collected in 1999 and 2000. A Klein 2000 sidescan system was used for geophysical surveying. A Triton Elics Isis brand side-scan data recording system was used on the cruise. The survey was navigated with a Leica Differential Global Positioning System (DGPS) which provided a ship position with accuracy of 1-5 m in DGPS mode. At times during the cruise differential signal was ...

Info
SANP1M.TIF - South Anacapa Passage sidescan sonar backscatter image in nearshore Benthic Habitat mapping Project S. California map Series. (UTM 10N, NAD83)

The sidescan sonar image of the nearshore seafloor (0 to 100 m water depths) of the southern Anacapa Passage area was mosaicked from data collected in 1999 and 2000. A Klein 2000 sidescan system was used for geophysical surveying. A Triton Elics Isis brand side-scan data recording system was used on the cruise. The 2000 survey was navigated with a Leica Differential Global Positioning System (DGPS) which provided a ship position with accuracy of 1-5 m in DGPS mode. At times during the cruise differential ...

Info
SECRU1M.TIF - Southeast Santa Cruz sidescan sonar backscatter image in nearshore Benthic Habitat mapping Project S. California map Series. (UTM 10N, NAD83)

The sidescan sonar image of the nearshore seafloor (0 to 100 m water depths) of the Southeast Santa Cruz area was mosaicked from data collected in 1999. A Klein 2000 sidescan system was used for geophysical surveying. A Triton Elics Isis brand side-scan data recording system was used on the cruise. The 1998 survey was navigated with a Leica Differential Global Positioning System (DGPS) which provided a ship position with accuracy of 1-5 m in DGPS mode. At times during the cruise differential signal was ...

Info
Post-Hurricane Florence Aerial Imagery: Cape Fear to Duck, North Carolina, October 6-8, 2018

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

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
Baseline_BackBarrier.shp - Baseline Along the Back-Barrier (North-Facing) Coast of Dauphin Island, Alabama, Generated to Calculate Shoreline Change Rates.

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

Info
Baseline_OpenOcean.shp - Baseline Along the Open-Ocean (South-Facing) Coast of Dauphin Island, Alabama, Generated to Calculate Shoreline Change Rates.

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

Info
Lidar-Derived Bare-Earth XYZ for EAARL Coastal Topography—Cape Hatteras, North Carolina, Post-Hurricane Isabel, 2003

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

Info
Lidar-Derived Bare-Earth XYZ for EAARL Coastal Topography—Cape Hatteras, North Carolina, Pre-Hurricane Isabel, 2003

ASCII XYZ data for Cape Hatteras, North Carolina, were produced from remotely sensed, geographically referenced elevation measurements collected pre-Hurricane Isabel on September 16, 2003 by the U.S. Geological Survey, in cooperation with the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the first-generation Experimental Advanced Airborne Research Lidar (EAARL-A), a pulsed laser ranging system mounted onboard an aircraft to measure ground ...

Info
Lidar-Derived Classified Point-Cloud for Coastal Topography—Chandeleur Islands, Louisiana, 23-25 June 2016

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

Info
Lidar-Derived Seamless Digital Elevation Model (DEM) Mosaic for Coastal Topography—Chandeleur Islands, Louisiana, 23-25 June 2016

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

Info
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 ...

Info
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 ...

Info
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 ...

Info
Distribution of Benthic Habitats at Crocker Reef, Florida, 2014

The distribution of benthic habitats for a 1-kilometer (km) x 1-km area around Crocker Reef in the Florida Keys, USA, is based upon underwater digital images of the seafloor collected on June 24 and 25, 2014 (Zawada and others, 2016). The imagery was collected using the U.S. Geological Survey (USGS) shallow Along-Track Reef-Imaging System (sATRIS), a boat-based, pole-mounted sensor package for mapping shallow-water benthic environments. The polygons contained in the shapefile included in this data release, ...

Info
EAARL Coastal Topography–Eastern Louisiana Barrier Islands, 09 March 2008: First Surface

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

Info
EAARL Coastal Topography–Eastern Louisiana Barrier Islands Barrier Islands, 09 March 2008: First Surface

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

Info
Calibrated EAARL-B Submerged Topography--Fort Lauderdale, Florida, 2014 (GEOID12A)

Binary point-cloud data of a portion of the submerged environs of Fort Lauderdale, Florida, were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency ...

Info
Calibrated EAARL-B Submerged Topography--Fort Lauderdale, Florida, 2014 (WGS84)

Binary point-cloud data of a portion of the submerged environs of Fort Lauderdale, Florida, were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency ...

Info
Uncalibrated EAARL-B Submerged Topography--Fort Lauderdale, Florida, 2014 (GEOID12A)

Binary point-cloud data of a portion of the submerged environs of Fort Lauderdale, Florida, were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency ...

Info
Uncalibrated EAARL-B Submerged Topography--Fort Lauderdale, Florida, 2014 (WGS84)

Binary point-cloud data of a portion of the submerged environs of Fort Lauderdale, Florida, were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency ...

Info
EAARL Coastal Topography–Texas, Post-Hurricane Ike, 2008: Bare Earth

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

Info
EAARL Coastal Topography–Texas, Post-Hurricane Ike, 2008: First Surface

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

Info
EAARL Coastal Topography–Northwest Florida, Post-Hurricane Katrina, 2005: Bare Earth

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

Info
EAARL Coastal Topography–Northwest Florida, Post-Hurricane Katrina, 2005: First Surface

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

Info
Time Series of Structure-from-Motion Products - Digital Elevation Models: Madeira Beach, Florida, July 2017 to June 2018

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 ...

Info
Time Series of Structure-from-Motion Products - Orthomosaics: Madeira Beach, Florida, July 2017 to June 2018

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 ...

Info
Time Series of Structure-from-Motion Products - Point Clouds: Madeira Beach, Florida, July 2017 to June 2018

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 ...

Info
Time Series of Aerial Imagery from Small Unmanned Aircraft Systems and Associated Ground Control Points: Madeira Beach, Florida, July 2017 to June 2018 (Aerial Imagery)

Aerial imagery acquired with a small unmanned aircraft system (sUAS), in conjunction with surveyed ground control points (GCPs) 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 consisting of aerial ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polyline: Combined Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polyline: Combined Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (dates_meta.txt)

Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polygon: Combined Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polygon: Combined Dates) is a polygon shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polygon: Individual Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Cat Island, Mississippi (Polygon: Individual Dates) is a dataset consisting of 268 polygon shapefiles representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polyline: Combined Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polyline: Combined Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polyline: Individual Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polygon: Combined Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polygon: Combined Dates) is a polygon shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polygon: Individual Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Dauphin Island, Alabama (Polygon: Individual Dates) is a dataset consisting of 223 polygon shapefiles representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polyline: Combined Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polyline: Combined Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polyline: Individual Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polygon: Combined Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polygon: Combined Dates) is a polygon shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polygon: Individual Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Horn Island, Mississippi (Polygon: Individual Dates) is a dataset consisting of 254 polygon shapefiles representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polyline: Combined Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polyline: Combined Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polyline: Individual Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polygon: Combined Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polygon: Combined Dates) is a polygon shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polygon: Individual Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Petit Bois Island, Mississippi (Polygon: Individual Dates) is a dataset consisting of 271 polygon shapefiles representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polyline: Combined Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polyline: Combined Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polyline: Individual Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polyline: Individual Dates) is a line shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polygon: Combined Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polygon: Combined Dates) is a polygon shapefile representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from these images and can indicate ...

Info
Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polygon: Individual Dates)

Shorelines Extracted from 1984-2015 Landsat Imagery: Ship Island, Mississippi (Polygon: Individual Dates) is a dataset consisting of 280 polygon shapefiles representing shorelines generated from satellite imagery that was collected from 1984 to 2015. The sample frequency of satellite imagery is much higher, and the coverage much greater, than most routine high-resolution topographic surveys. Certain aspects of barrier island morphology, such as island size, shape and position, can be determined from ...

Info
EAARL Coastal Topography–Texas, Post-Hurricane Rita, 2005: Bare Earth

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

Info
EAARL Coastal Topography–Texas, Post-Hurricane Rita, 2005: First Return

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

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial Systems Flights Over Town Neck Beach, in Sandwich, Massachusetts, on January 9, 2017

Low-altitude (80-100 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained from a camera mounted on a small unmanned aerial system (UAS; also known as a drone). Imagery was collected at close to low tide on seven days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial Systems Flights Over Town Neck Beach, in Sandwich, Massachusetts, on January 25, 2017

Low-altitude (80-100 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained from a camera mounted on a small unmanned aerial system (UAS; also known as a drone). Imagery was collected at close to low tide on seven days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial Systems Flights Over Town Neck Beach, in Sandwich, Massachusetts, on February 14, 2017

Low-altitude (80-100 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained from a camera mounted on a small unmanned aerial system (UAS; also known as a drone). Imagery was collected at close to low tide on seven days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial Systems Flights Over Town Neck Beach, in Sandwich, Massachusetts, on March 16, 2017

Low-altitude (80-100 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained from a camera mounted on a small unmanned aerial system (UAS; also known as a drone). Imagery was collected at close to low tide on to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which were ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial Systems Flights Over Town Neck Beach, in Sandwich, Massachusetts, on April 28, 2017

Low-altitude (80-100 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained from a camera mounted on a small unmanned aerial system (UAS; also known as a drone). Imagery was collected at close to low tide to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which were located ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial Systems Flights Over Town Neck Beach, in Sandwich, Massachusetts, on May 4, 2017

Low-altitude (80-100 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained from a camera mounted on a small unmanned aerial system (UAS; also known as a drone). Imagery was collected at close to low tide on seven days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial Systems Flights Over Town Neck Beach, in Sandwich, Massachusetts, on September 18, 2017

Low-altitude (80-100 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained from a camera mounted on a small unmanned aerial system (UAS; also known as a drone). Imagery was collected at close to low tide to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ground, which were located ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial Systems Flights Over Town Neck Beach, in Sandwich, Massachusetts, on March 30, 2016

Low-altitude (30-120 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained with a series of cameras mounted on small unmanned aerial systems (UAS, also known as a drone). Imagery was collected at close to low tide on five days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial System Flights Over Town Neck Beach, in Sandwich, Massachusetts, on September 21, 2016

Low-altitude (30-120 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained with a series of cameras mounted on small unmanned aerial systems (UAS, also known as a drone). Imagery was collected at close to low tide on five days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial System Flights Over Town Neck Beach, in Sandwich, Massachusetts, on January 22, 2016

Low-altitude (30-120 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained with a series of cameras mounted on small unmanned aerial systems (UAS, also known as a drone). Imagery was collected at close to low tide on five days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial Systems Flights Over Town Neck Beach, in Sandwich, Massachusetts, on January 25, 2016

Low-altitude (30-120 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained with a series of cameras mounted on small unmanned aerial systems (UAS, also known as a drone). Imagery was collected at close to low tide on five days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ...

Info
Geotagged Low-Altitude Aerial Imagery From Unmanned Aerial System Flights Over Town Neck Beach, in Sandwich, Massachusetts, on February 11, 2016

Low-altitude (30-120 meters above ground level) digital images of Town Neck Beach in Sandwich, Massachusetts, were obtained with a series of cameras mounted on small unmanned aerial systems (UAS, also known as a drone). Imagery was collected at close to low tide on five days to observe changes in beach and dune morphology. The images were geolocated by using the single-frequency geographic positioning system aboard the UAS. Ground control points (GCPs) were established by using temporary targets on the ...

Info
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 ...

Info
Low-altitude aerial imagery collected from a Helikite at the Pea Island National Wildlife Refuge DUNEX Site, North Carolina in September and October 2021

The data in this part of the release are images of the beach for use in structure from motion that were taken with a camera attached to a helium filled balloon-kite (Helikite). During September and October 2021, USGS and Woods Hole Oceanographic Institute (WHOI) scientists conducted multiple field surveys to collect an elevation time series at the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge, NC. Agisoft Metashape (v. 1.8.1) was used to create orthomosaics and ...

Info
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 ...

Info
Sidescan sonar bathymetry products at the Pea Island National Wildlife Refuge DUNEX Site, North Carolina in October 2021

The data in this section of the release characterizes the nearshore bathymetry collected in October 2021 by USGS and Woods Hole Oceanographic Institute (WHOI) scientists using a self-righting electric uncrewed surface vehicle with a sidescan sonar attached. Data collection occured at the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge (PINWR). DUNEX is a multi-agency, academic, and non-governmental organization collaborative community experiment designed to study ...

Info
Topobathy Products in Pea Island National Wildlife Refuge, North Carolina in November 2020 and April, September, and October 2021

The data in this part of the release characterize the beach and nearshore environment at the USGS DUring Nearshore Event eXperiment (DUNEX) site on Pea Island National Wildlife Refuge (PINWR) and at the Basnight Bridge (BB), NC. In November 2020, April, September, and October 2021, USGS and Woods Hole Oceanographic Institute (WHOI) scientists conducted multiple field surveys to collect a topobathy elevation time series. Bathymetry for topobathy products was collected in the nearshore using a single-beam ...

Info
2010-2022 New Jersey and New York Beach Volumes

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

Info
2010-2022 New Jersey and New York Beach Shoreline Change

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

Info
2018 Puerto Rico USACE Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2001 Gulf Coast USGS/NASA ATM Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2005 East Coast (DE, MD, NJ, NY, NC, and VA) USACE NCMP Topobathy Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2012 Post-Hurricane Sandy Long Island, New York USACE Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2016 USACE Post-Hurricane Matthew Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2016 Massachusetts NOAA Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2017 Georgia through New York USACE NCMP Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2017 Florida West Coast NOAA Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2018 Alabama and Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2018 Florida USGS Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2018 East Coast (VA, NC, SC) USACE NCMP Post-Florence Topobathy Lidar-Derived Dune Crest, Toe, and Shoreline

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

Info
2018 East Coast (NC) USACE NCMP Topobathy Lidar Derived Dune Crest, Toe and Shoreline

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

Info
2018 Mississippi and Alabama USACE Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2019 North Carolina and Virginia USACE Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2019 North Carolina and Virginia Post-Dorian USACE Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2020 New Jersey and New York USACE Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2021 New York State Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2022 New Jersey and New York USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
2020 New Jersey USACE USGS Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
1998 MA, NY, MD, and VA USGS/NASA ATM2 Lidar-derived dune crest, toe and shoreline

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

Info
2014 Post-Hurricane Sandy SC to NY NOAA NGS Lidar-Derived Dune Crest, Toe and Shoreline

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

Info
Continuous terrain model for water circulation studies, Barnegat Bay, New Jersey (10 meter resolution, 32-bit GeoTIFF, UTM 18, WGS 84)

Water quality in the Barnegat Bay estuary along the New Jersey coast is the focus of a multidisciplinary research project begun in 2011 by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection. This narrow estuary is the drainage for the Barnegat Bay watershed and flushed by just three inlets connecting it to the Atlantic Ocean, is experiencing degraded water quality, algal blooms, loss of seagrass, and increases in oxygen-depletion events. The scale of ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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
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
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 ...

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
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
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
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
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 ...

Info
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 ...

Info
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 ...

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
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
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
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
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
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
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
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
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
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
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
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
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
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
DS888_PRSF_tile_extents: EAARL-B Coastal Topography—Fire Island, New York, pre-Hurricane Sandy, 2012: Seamless (Bare Earth and Submerged)

This shapefile was produced from 53 2-kilometer by 2-kilometer tile extents of remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface ...

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

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

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

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

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

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

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

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

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

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

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

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

Info
San Francisco Bay-Delta bathymetric/topographic digital elevation model(DEM)

A high-resolution (10-meter per pixel) digital elevation model (DEM) was created for the Sacramento-San Joaquin Delta using both bathymetry and topography data. This DEM is the result of collaborative efforts of the U.S. Geological Survey (USGS) and the California Department of Water Resources (DWR). The base of the DEM is from a 10-m DEM released in 2004 and updated in 2005 (Foxgrover and others, 2005) that used Environmental Systems Research Institute(ESRI), ArcGIS Topo to Raster module to interpolate ...

Info
Digital elevation models (DEMs) of the lower Elwha River, Washington, water year 2013 to 2016

Digital elevation models (DEMs) of the lower Elwha River, Washington, were created by synthesizing lidar and PlaneCam Structure-from-Motion (SfM) data. Lidar and still digital photographs were collected by airplane during surveys from 2012 to 2016. The digital photographs were used to create a SfM digital surface model. Each DEM represents the ending conditions for that water year (for example, the 2013 DEM represents conditions at approximately September 30, 2013). The final DEMs, presented here, were ...

Info
Digital elevation model (DEM) of the Cache Slough Complex, Sacramento-San Joaquin Delta, California

This metadata describes a digital elevation model (DEM) created from bathymetric and topographic data collected between 2004 and 2019 in the Cache Slough Complex (CSC), northern Sacramento-San Joaquin Delta, California. We merged the newly collected bathymetric and topographic data presented in this data release (DOI:10.5066/P9AQSRVH) with 2019 surveys by the California Department of Water Resources (DWR), 2017 USGS Sacramento Delta Lidar, and 2004 bathymetry data from the Army Corp of Engineers. Small gaps ...

Info
Digital elevation model (DEM) of the Sacramento River Deep Water Ship Channel (DWSC), Sacramento-San Joaquin Delta, California

This metadata describes a digital elevation model (DEM) created from bathymetric and topographic data collected between 2017 and 2019 in the Sacramento River Deep Water Ship Channel (DWSC), northern Sacramento-San Joaquin Delta, California. We merged the newly collected bathymetric and topographic data presented in this data release (DOI:10.5066/P9AQSRVH) with 2019 surveys by the California Department of Water Resources (DWR) and 2017 USGS Sacramento Delta Lidar, to produce a seamless digital elevation ...

Info
Seamless topo-bathy digital elevation model (DEM) of Arey Lagoon, Alaska

A seamless topographic-bathymetric digital elevation model for an area around Arey Lagoon, Alaska created from a combination of lidar elevation data collected in 2009, single-beam bathymetric data collected in 2011, and NOS sounding data collected in 1948.

Info
Bathymetry Hillshade--Hueneme Canyon and Vicinity, California

This part of DS 781 present the shaded-relief bathymetry map of the Hueneme Canyon and Vicinity map area, California. The raster data file for the shaded-relief map is included in "BathymetryHS_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A ...

Info
Bathymetry--Hueneme Canyon and Vicinity, California

This part of DS 781 presents data for the bathymetry map of the Hueneme Canyon and Vicinity map area, California. The raster data file for the bathymetry map is included in "Bathymetry_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan ...

Info
Contours--Hueneme Canyon and Vicinity, California

This part of DS 781 presents data for the bathymetric contours of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Contours_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W ...

Info
Curvature--Hueneme Canyon and Vicinity, California

This part of DS 781 presents data for the curvature map of the Hueneme Canyon and vicinity map area, California. The raster data file is included in "Curvature_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., ...

Info
Slope—Hueneme Canyon and Vicinity, California

This part of DS 781 presents data for the curvature map of the Hueneme Canyon and vicinity map area, California. The raster data file is included in "Curvature_HuenemeCanyon.zip," which is accessible from https://pubs.usgs.gov/ds/781/HuenemeCanyon/data_catalog_HuenemeCanyon.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N.E., Phillips, E.L., Ritchie, A.C., Kvitek, R.G., Greene, H.G., Krigsman, L.M., Endris, C.A., Clahan, K.B., Sliter, R.W., ...

Info
CENCAL_BASELINE - Offshore Baseline for Central California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
CENCAL_BIASVALUES - Central California Shoreline Bias Values

The USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. These shorelines were used to calculate long-term and short-term change rates in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS ...

Info
CENCAL_INTERSECTS_LT - Long-Term Transect-Shoreline Intersection Points for Central California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
CENCAL_INTERSECTS_ST - Short-Term Transect-Shoreline Intersection Points for Central California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
CENCAL_TRANSECTS_LT - Long-Term Shoreline Change Rates for Central California Generated at a 50 m Transect Spacing, 1853-2002

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
CENCAL_TRANSECTS_ST - Short-Term Shoreline Change Rates for Central California Generated at a 50m Transect Spacing, 1971-1998

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
NORCAL_BASELINES - Offshore Baseline for Northern California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
NORCAL_BIASVALUES - Northern California Shoreline Bias Values

The USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. These shorelines were used to calculate long-term and short-term change rates in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS ...

Info
NORCAL_INTERSECTS_LT - Long-Term Transect-Shoreline Intersection Points for Northern California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
NORCAL_INTERSECTS_ST - Short-Term Transect-Shoreline Intersection Points for Northern California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
NORCAL_TRANSECTS_LT - Long-Term Shoreline Change Rates for Northern California Generated at a 50 m Transect Spacing, 1854-2002

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
NORCAL_TRANSECTS_ST - Short-Term Shoreline Change Rates for Northern California Generated at a 50m Transect Spacing, 1952-2002

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
SOCAL_BASELINE - Offshore Baseline for Southern California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
SOCAL_BIASVALUES - Southern California Shoreline Bias Values

The USGS has produced a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. Shorelines are compiled by state and generally correspond to one of four time periods: 1800s, 1920s-1930s, 1970s, and 1998-2002. These shorelines were used to calculate long-term and short-term change rates in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS ...

Info
SOCAL_INTERSECTS_LT - Long-Term Transect-Shoreline Intersection Points for Southern California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
SOCAL_INTERSECTS_ST - Short-Term Transect-Shoreline Intersection Points for Southern California Generated to Calculate Shoreline Change Rates

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
SOCAL_TRANSECTS_LT - Long-Term Shoreline Change Rates for Southern California Generated at a 50m Transect Spacing, 1852-1998

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
SOCAL_TRANSECTS_ST - Short-Term Shoreline Change Rates for Southern California Generated at a 50m Transect Spacing, 1971-1998

Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 3.0; An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2005-1304, Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Miller, T.M. The extension is designed to efficiently lead a user through the major steps of shoreline change analysis. This extension to ArcGIS contains three main components that define a baseline, generate ...

Info
EAARL Coastal Topography-Louisiana, Mississippi and Alabama, March 2006: First Return

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

Info
EAARL Coastal Topography-Louisiana, Mississippi and Alabama, March 2006: Last Return

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

Info
EAARL Coastal Topography--Louisiana, Mississippi and Alabama September 2006: First Return

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

Info
EAARL Coastal Topography--Louisiana, Mississippi and Alabama September 2006: Last Return

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-100 Years From 2001 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-100 Years From 2001 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-100 Years From 2011 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-100 Years From 2011 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—100 Years From 2014 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—100 Years From 2014 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ...

Info
Seafloor elevation change from the 1930s to 2016 along the Florida Reef Tract, USA

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes along the Florida Reef Tract (FRT) from Miami to Key West within a 982.4 square-kilometer area. USGS staff calculated changes in seafloor elevation from the 1930’s to 2016 using digitized historical hydrographic surveys (H-sheets) acquired by the U.S. Coast and Geodetic Survey (USC&GS) in the 1930’s and light detection and ranging (lidar)-derived digital elevation models ...

Info
Seafloor elevation change from 2002 to 2016 in the Upper Florida Keys

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes in the Upper Florida Keys (UFK) from Triumph Reef to Pickles Reef within a 242.4 square-kilometer area. USGS staff calculated changes in seafloor elevation from 2002 to 2016 using light detection and ranging (lidar)-derived data acquired by the USGS in 2001 and 2002 and lidar-derived data acquired by the National Oceanic and Atmospheric Administration (NOAA) in 2016 and 2017. ...

Info
Beach Topography—Fire Island, New York, Post-Hurricane Sandy, April 2014: Ground Based Lidar (1-Meter Digital Elevation Model)

The U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) and the U.S. Army Corps of Engineers Field Research Facility (USACE-FRF) of Duck, NC collaborated to gather alongshore ground-based lidar beach topography at Fire Island, NY. This high-resolution elevation dataset was collected on April 1, 2014, and is part of the USGS's ongoing beach monitoring effort under Hurricane Sandy Supplemental Project GS2-2B. This USGS Data Release includes the resulting processed elevation ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-25 Years From 2001 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-25 Years From 2001 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-25 Years From 2011 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-25 Years From 2011 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida-25 Years From 2014 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—25 Years From 2014 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-50 Years From 2001 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-50 Years From 2001 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-50 Years From 2011 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-50 Years From 2011 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—50 Years From 2014 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—50 Years From 2014 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-75 Years From 2001 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Port St. Lucie to Marquesas Key, Florida-75 Years From 2001 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation along the Florida Reef Tract, Florida (FL). USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) Office of Coast Survey, see Yates and others, 2017) and light ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-75 Years From 2011 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Big Pine Key to Marquesas Key, Florida-75 Years From 2011 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along Key West, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric Administration (NOAA) ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—75 Years From 2014 Based on Historical Rates of Mean Elevation Change

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ...

Info
Projected Seafloor Elevation Along the Florida Reef Tract From Deerfield Beach to Homestead, Florida—75 Years From 2014 Based on Historical Rates of Mean Erosion

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify the combined effect of all constructive and destructive processes on modern coral reef ecosystems by projecting future regional-scale changes in seafloor elevation for several sites along the Florida Reef Tract, Florida (FL) including the shallow seafloor along the coast of Miami, FL. USGS staff used historical bathymetric point data from the 1930's (National Oceanic and Atmospheric ...

Info
EAARL Coastal Topography--Assateague Island National Seashore, Maryland and Virginia, 2002: Bare Earth

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

Info
EAARL Coastal Topography--Assateague Island National Seashore, Maryland and Virginia, 2002: First Surface

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

Info
EAARL Coastal Topography--Dauphin Island, Alabama, 2010: Bare Earth

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over Dauphin Island, post-Tropical Storm Bonnie (July 2010 tropical storm), using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. ...

Info
EAARL Coastal Topography--Dauphin Island, Alabama, 2010: First Surface

ASCII XYZ point cloud data were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over Dauphin Island, post-Tropical Storm Bonnie (July 2010 tropical storm), using the National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. ...

Info
EAARL Coastal Topography—Chandeleur Islands, Louisiana, 4-5 September 2010: Seamless (Bare Earth and Submerged)

ASCII XYZ point-cloud data for the Chandeleur Islands in Louisiana were produced from remotely sensed, geographically referenced elevation measurements collected on September 4 and 5, 2010 by the U.S. Geological Survey. Elevation measurements were collected over the area using the first-generation Experimental Advanced Airborne Research Lidar (EAARL-A), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high ...

Info
EAARL Coastal Topography—Chandeleur Islands, Louisiana, 12-13 February 2011: Seamless (Bare Earth and Submerged)

ASCII XYZ point-cloud data for the Chandeleur Islands in Louisiana were produced from remotely sensed, geographically referenced elevation measurements collected on February 12 and 13, 2011 by the U.S. Geological Survey. Elevation measurements were collected over the area using the first-generation Experimental Advanced Airborne Research Lidar (EAARL-A), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high ...

Info
Seafloor Elevation Change From 2016 to 2017 at Crocker Reef, Florida Keys-Impacts From Hurricane Irma

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes at Crocker Reef near Islamorada, Florida (FL), within a 33.6 square-kilometer area following the landfall of Hurricane Irma in September 2017. USGS staff used light detection and ranging (lidar)-derived data acquired by the National Oceanic and Atmospheric Administration (NOAA) between July 21 and November 21, 2016 and USGS multibeam data collected between October 10 and ...

Info
EAARL Coastal Topography-Northern Gulf of Mexico

ASCII xyz point cloud data were produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with the U.S. Geological Survey (USGS) and National Air and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams ...

Info
EAARL Topography-Vicksburg National Millitary Park 2007: First Surface

A first surface elevation map (also known as a Digital Elevation Model, or DEM) of the Vicksburg National Military Park in Mississippi was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), National Park Service (NPS), and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ranging system ...

Info
EAARL Topography-Jean Lafitte National Historical Park and Preserve 2006

A first surface/bare earth elevation map (also known as a Digital Elevation Model, or DEM) of the Jean Lafitte National Historical Park and Preserve in Louisiana was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL ...

Info
EAARL Topography-Vicksburg National Millitary Park 2008: Bare Earth

A bare earth elevation map (also known as a Digital Elevation Model, or DEM) of the Vicksburg National Military Park in Mississippi was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), National Park Service (NPS), and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ranging system ...

Info
EAARL Coastal Topography-Fire Island National Seashore 2007

A bare earth/first surface elevation map (also known as a Digital Elevation Model, or DEM) of the Fire Island National Seashore in New York was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ...

Info
EAARL Topography-Natchez Trace Parkway 2007: First Surface

A first surface elevation map (also known as a Digital Elevation Model, or DSM) of a portion of the Natchez Trace Parkway in Mississippi was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), National Park Service (NPS), and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ranging system ...

Info
EAARL Coastal Topography-Sandy Hook 2007

A first surface/bare earth elevation map (also known as a Digital Elevation Model, or DEM) of the Gateway National Recreation Area's Sandy Hook Unit in New Jersey was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar ...

Info
EAARL Submerged Topography-U.S. Virgin Islands 2003

A submerged topography elevation map (also known as a Digital Elevation Model, or DEM) of a portion of the U.S. Virgin Islands was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), and National Park Service (NPS). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ranging system mounted ...

Info
EAARL Coastal Topography--Northeast Barrier Islands 2007: First Surface

A first surface elevation map (also known as a Digital Elevation Model, or DEM) of the northeast coastal barrier islands in New York and New Jersey was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ranging system mounted onboard ...

Info
EAARL Coastal Topography--Northeast Barrier Islands 2007: Bare Earth

A bare earth elevation map (also known as a Digital Elevation Model, or DEM) of the northeast coastal barrier islands in New York and New Jersey was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ranging system mounted onboard an ...

Info
EAARL Coastal Topography - Northern Gulf of Mexico, 2007: First surface

A first surface elevation map (also known as a Digital Elevation Model, or DEM) of the northern Gulf of Mexico barrier islands and Naval Live Oaks was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed ...

Info
EAARL Coastal Topography - Northern Gulf of Mexico, 2007: Bare earth

A bare earth elevation map (also known as a Digital Elevation Model, or DEM) of the northern Gulf of Mexico barrier islands and Naval Live Oaks was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ...

Info
EAARL Topography--George Washington Birthplace National Monument 2008

A first surface/bare earth elevation map (also known as a Digital Elevation Model, or DEM) of the George Washington Birthplace National Monument in Virginia was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a ...

Info
EAARL Coastal Topography-St. John, U.S. Virgin Islands 2003: First Surface

A first surface elevation map (also known as a Digital Elevation Model, or DEM) of a portion of St. John, U.S. Virgin Islands was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), and National Park Service (NPS). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ranging system mounted ...

Info
EAARL Coastal Topography--Pearl River Delta 2008: Bare Earth

A bare earth elevation map (also known as a Digital Elevation Model, or DEM) of the Pearl River Delta in Louisiana and Mississippi was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the University of New Orleans (UNO), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ranging ...

Info
EAARL Coastal Topography--Pearl River Delta 2008: First Surface

A first surface elevation map (also known as a Digital Elevation Model, or DEM) of the Pearl River Delta in Louisiana and Mississippi was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the University of New Orleans (UNO), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed-laser ...

Info
ATM Coastal Topography--Alabama 2001

A first surface elevation map was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning Lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a twin-otter or P3 aircraft and incorporates a green-wavelength laser ...

Info
ATM Coastal Topography--Florida 2001: Western Panhandle

A first surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning Lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft and incorporates a green-wavelength ...

Info
ATM Coastal Topography--Florida 2001: Eastern Panhandle

A first surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning Lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft and incorporates a green-wavelength ...

Info
EAARL Coastal Topography--Assateague Island National Seashore, 2008: First Surface

A first-surface elevation map (also known as a Digital Elevation Model, or DEM) of the Assateague Island National Seashore in Virginia and Maryland was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed ...

Info
EAARL Coastal Topography--Assateague Island National Seashore, 2008: Bare Earth

A bare-earth elevation map (also known as a Digital Elevation Model, or DEM) of the Assateague Island National Seashore in Virginia and Maryland was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ...

Info
ATM Coastal Topography--Texas, 2001: UTM Zone 14

A first-surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft and incorporates a green-wavelength ...

Info
ATM Coastal Topography--Texas, 2001: UTM Zone 15

A first-surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft and incorporates a green-wavelength ...

Info
ATM Coastal Topography--Mississippi, 2001

A first-surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft and incorporates a green-wavelength ...

Info
ATM Coastal Topography--Louisiana, 2001: UTM Zone 15 (Part 1 of 2)

A first-surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft and incorporates a green-wavelength ...

Info
ATM Coastal Topography--Louisiana, 2001: UTM Zone 16 (Part 2 of 2)

A first-surface elevation map was produced cooperatively from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS) and National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Airborne Topographic Mapper (ATM), a scanning lidar system that measures high-resolution topography of the land surface. The ATM system is deployed on a Twin Otter or P-3 Orion aircraft and incorporates a green-wavelength ...

Info
EAARL Coastal Topography--Western Florida, Post-Hurricane Charley, 2004: First Surface

A first-surface elevation map (also known as a Digital Elevation Model, or DEM) of a portion of western Florida, post-Hurricane Charley, was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an ...

Info
EAARL Coastal Topography and Imagery--Naval Live Oaks Area, Gulf Islands National Seashore, Florida, 2007

A digital elevation map (also known as a Digital Elevation Model, or DEM) of the Naval Live Oaks Area in Florida's Gulf Islands National Seashore was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed ...

Info
EAARL Coastal Topography--Western Florida, Post-Hurricane Charley, 2004: Seamless (Bare Earth and Submerged)

A seamless (bare-earth and submerged) elevation map (also known as a Digital Elevation Model, or DEM) of a portion of western Florida, post-Hurricane Charley, was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system ...

Info
EAARL Coastal Topography--Chandeleur Islands, Louisiana, 2010: Bare Earth

A bare-earth digital elevation map (also known as a Digital Elevation Model, or DEM) of a portion of the Chandeleur Islands, Louisiana, was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft ...

Info
EAARL Coastal Topography--Gateway National Recreation Area, New Jersey and New York, 2009

A digital elevation map (also known as a Digital Elevation Model, or DEM) of a portion of the Gateway National Recreation Area in New Jersey and New York was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a ...

Info
EAARL Coastal Topography--Eastern Florida, Post-Hurricane Frances, 2004: First Surface

A digital elevation map (also known as a Digital Elevation Model, or DEM) of a portion of the eastern Florida coastline was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ...

Info
EAARL Coastal Topography--Eastern Florida, Post-Hurricane Frances, 2004: Bare Earth

A bare-earth digital elevation map (also known as a Digital Elevation Model, or DEM) of a portion of the eastern Florida coastline was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to ...

Info
EAARL Coastal Topography--Mississippi and Alabama Barrier Islands, Post-Hurricane Gustav, 2008

A digital elevation model (DEM) of a portion of the Mississippi and Alabama barrier islands, post-Hurricane Gustav (September 2008 hurricane), was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ...

Info
EAARL Coastal Topography--Sandy Hook Unit, Gateway National Recreation Area, New Jersey, Post-Nor'Ida, 2009

A digital elevation model (DEM) of a portion of the Sandy Hook Unit of the Gateway National Recreation Area in New Jersey, post-Nor'Ida (November 2009 nor'easter) was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to ...

Info
EAARL Coastal Topography--Fire Island National Seashore, New York, Post-Nor'Ida, 2009

A digital elevation model (DEM) of a portion of the Fire Island National Seashore in New York, post-Nor'Ida (November 2009 nor'easter), was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, ...

Info
EAARL Coastal Topography and Imagery--Assateague Island National Seashore, Maryland and Virginia, Post-Nor'Ida, 2009

A digital elevation model (DEM) of a portion of the Assateague Island National Seashore in Maryland and Virginia, post-Nor'Ida (November 2009 nor'easter), was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ...

Info
EAARL Coastal Topography--Eastern Louisiana Barrier Islands, Post-Hurricane Gustav, 2008: First Surface

A digital elevation model (DEM) of a portion of the eastern Louisiana barrier islands, post-Hurricane Gustav (September 2008 hurricane), was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to ...

Info
EAARL Coastal Topography--Eastern Florida, Post-Hurricane Jeanne, 2004: First Surface

A digital elevation model (DEM) of a portion of the eastern Florida coastline, post-Hurricane Jeanne (September 2004 hurricane), was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ...

Info
EAARL Coastal Topography--Maryland and Delaware, post-Nor'Ida, 2009

A digital elevation model (DEM) of a portion of the eastern Maryland and Delaware coastline, post-Nor'Ida (November 2009 nor'easter), was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The ...

Info
EAARL Coastal Topography--Cape Hatteras National Seashore, North Carolina, Post-Nor'Ida, 2009: First Surface

A digital elevation model (DEM) of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, post-Nor'Ida (November 2009 nor'easter), was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system ...

Info
EAARL Coastal Topography and Imagery--Fire Island National Seashore, New York, 2009

A digital elevation model (DEM) of a portion of the Fire Island National Seashore in New York was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS), the National Park Service (NPS), and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to ...

Info
EAARL Coastal Topography--Cape Hatteras National Seashore, North Carolina, Post-Nor'Ida, 2009: Bare Earth

A digital elevation model (DEM) of a portion of the Cape Hatteras National Seashore in North Carolina, post-Nor'Ida (November 2009 nor'easter), was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground ...

Info
EAARL Coastal Topography-Cape Canaveral, Florida, 2009: First Surface

A digital elevation model (DEM) of a portion of the eastern Florida coastline was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), Kennedy Space Center, FL. Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, ...

Info
EAARL Coastal Topography--Northern Outer Banks, North Carolina, Post-Nor'Ida, 2009

A digital elevation model (DEM) of a portion of the northern North Carolina coastline beachface, post-Nor'Ida (November 2009 nor'easter), was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The ...

Info
EAARL Topography--Potato Creek Watershed, Georgia, 2010

A digital elevation model (DEM) of a portion of the Potato Creek watershed in Georgia was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area on February 27, 2010, using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency ...

Info
EAARL Topography--Three Mile Creek and Mobile-Tensaw Delta, Alabama, 2010

A digital elevation model (DEM) of a portion of the Mobile-Tensaw Delta region and Three Mile Creek in Alabama was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area (bathymetry was irresolvable) using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. ...

Info
EAARL Coastal Topography--Eastern Florida, Post-Hurricane Jeanne, 2004: Bare Earth

A digital elevation model (DEM) of a portion of the eastern Florida coastline, post-Hurricane Jeanne (September 2004 hurricane), was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ...

Info
EAARL Coastal Topography--Assateague Island National Seashore, Maryland and Virginia, 2010

A digital elevation model (DEM) of a portion of the Assateague Island National Seashore in Maryland and Virginia was produced from remotely sensed, geographically referenced elevation measurements collected cooperatively by the U.S. Geological Survey (USGS) and the National Park Service (NPS). Elevation measurements were collected over the area on March 19 and 24, 2010, using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ...

Info
EAARL Coastal Topography--Virginia, Post-Nor'Ida, 2009

A digital elevation model (DEM) of a portion of the Virginia coastline beachface, post-Nor'Ida (November 2009 nor'easter), was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The EAARL sensor ...

Info
EAARL Coastal Topography--Alligator Point, Louisiana, 2010

A digital elevation model (DEM) of a portion of Alligator Point, Louisiana, was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's ...

Info
EAARL Coastal Topography--Central Wetlands, Louisiana, 2010

A digital elevation model (DEM) of a portion of the Central Wetlands, Louisiana was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area on March 4 and 5, 2010, using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser ...

Info
EAARL Coastal Topography--North Shore, Lake Pontchartrain, Louisiana, 2010

A digital elevation model (DEM) of a portion of the north shore of Lake Pontchartrain, Louisiana, was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area on February 28, March 1, and March 5, 2010, using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. ...

Info
EAARL Coastal Topography and Imagery--Western Louisiana, Post-Hurricane Rita, 2005: First Surface

ASCII xyz and binary point-cloud data, as well as a digital elevation model (DEM) of a portion of the Louisiana coastline, post-Hurricane Rita (September 2005 hurricane), was produced from remotely sensed, geographically referenced elevation measurements cooperatively by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Elevation measurements were collected over the area using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging ...

Info
Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012: Digital elevation model (DEM)

A DEM was produced for a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines, post-Hurricane Sandy (Sandy was an October 2012 hurricane that made landfall as an extratropical cyclone on the 29th), from remotely sensed, geographically referenced elevation measurements collected by Photo Science, Inc. (Delaware, Maryland, Virgina, and North Carolina) and Woolpert, Inc. (Fire Island, New York) using airborne lidar sensors.

Info
Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012: Lidar-extracted dune features

Dune crest and toe positions along a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines, post-Hurricane Sandy (Sandy was an October 2012 hurricane that made landfall as an extratropical cyclone on the 29th), were produced by the U.S. Geological Survey (USGS) from remotely sensed, geographically referenced elevation measurements collected by Photo Science, Inc. (Delaware, Maryland, Virginia, and North Carolina) and Woolpert, Inc. (Fire Island, New York)using using airborne ...

Info
Coastal Topography--Northeast Atlantic Coast, Post-Hurricane Sandy, 2012: Mean-high-water shoreline

Mean-high-water (MHW) shoreline for a portion of the New York, Delaware, Maryland, Virginia, and North Carolina coastlines were derived from lidar data collected following Hurricane Sandy (Sandy was an October 2012 hurricane that made landfall as an extratropical cyclone on the 29th). Data were produced by the U.S. Geological Survey (USGS) from remotely sensed, geographically-referenced elevation measurements collected by Photo Science, Inc. (Delaware, Maryland, Virginia, and North Carolina) and Woolpert, ...

Info
EAARL-B Coastal Topography--Eastern New Jersey, Hurricane Sandy, 2012: First Surface

ASCII xyz and binary point-cloud data, as well as a digital elevation model (DEM) of a portion of the New Jersey coastline, pre- and post-Hurricane Sandy (October 2012 hurricane), were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ...

Info
EAARL-B Submerged Topography—Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012

American Standard Code for Information Interchange XYZ and binary point-cloud data, as well as a digital elevation model for part of Barnegat Bay, New Jersey, pre-Hurricane Sandy (October 2012 hurricane), were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ranging system mounted onboard an aircraft to ...

Info
EAARL-B Submerged Topography—Barnegat Bay, New Jersey, post-Hurricane Sandy, 2012–2013

American Standard Code Information Interchange XYZ and binary point-cloud data, as well as a digital elevation model for part of Barnegat Bay, New Jersey, post-Hurricane Sandy (October 2012 hurricane), were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ranging system mounted onboard an aircraft to ...

Info
EAARL-B Coastal Topography--Chandeleur Islands, Louisiana, 2012: Seamless (Bare Earth and Submerged) (.shp file)

This shapefile was produced from 52 2-kilometer by 2-kilometer tile extents of remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the ...

Info
Beach Topography— Terrestrial-Based Lidar Beach Topography of Fire Island, New York, June 2014

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collaborated to gather alongshore terrestrial-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on June 11, 2014, to characterize beach topography and document ongoing beach evolution and recovery, and is part of the ongoing beach monitoring within the ...

Info
Terrestrial-Based Lidar Beach Topography of Fire Island, New York, June 2014

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collaborated to gather alongshore terrestrial-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on June 11, 2014, to characterize beach topography and document ongoing beach evolution and recovery, and is part of the ongoing beach monitoring within the ...

Info
Beach Topography—Fire Island, New York, Post-Hurricane Sandy, April 2013: Ground Based Lidar (1-Meter Digital Elevation Model)

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center in Florida and the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina, collaborated to gather alongshore ground-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on April 10, 2013, to characterize beach topography following substantial erosion that occurred during Hurricane Sandy, which made landfall on October 29, 2012, and multiple, ...

Info
Lidar-Derived Classified Bare-Earth Point-Cloud for Coastal Topography—Fire Island, New York, 07 May 2012

Binary point-cloud data were produced for Fire Island, New York, from remotely sensed, geographically referenced elevation measurements collected by Photo Science, Inc. using an Optech Gemini lidar sensor flown on a Cessna 206 aircraft.

Info
Lidar-Derived Bare-Earth Digital Elevation Model (DEM) Mosaic for Coastal Topography—Fire Island, New York, 07 May 2012

A digital elevation model (DEM) mosaic was produced for Fire Island, New York, from remotely sensed, geographically referenced elevation measurements collected by Photo Science, Inc. using an Optech Gemini lidar sensor flown on a Cessna 206 aircraft

Info
Projected Seafloor Elevation Change and Relative Sea Level Rise Along the Florida Reef Tract from Miami to Boca Chica Key 25, 50, 75, and 100 Years from 2016

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes along the Florida Reef Tract (FRT) from Miami to Boca Chica Key, Florida. Changes in seafloor elevation were calculated from the 1930s to 2016 using digitized hydrographic sheet sounding data and light detection and ranging (lidar)-derived digital elevation models (DEMs) acquired by the National Oceanic and Atmospheric Administration (NOAA) in 2016 and 2017. Most of the ...

Info
EAARL Coastal Topography--Dauphin Island, Alabama, Post-Hurricane Katrina, 2005: Bare Earth

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

Info
EAARL Coastal Topography--Dauphin Island, Alabama, Post-Hurricane Katrina, 2005: First Surface

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

Info
Seafloor Elevation Change From 2004 to 2016 at Looe Key, Florida Keys

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes at Looe Key near Big Pine Key, Florida (FL), within a 16.4 square-kilometer area between 2004 and 2016. USGS staff used light detection and ranging (lidar)-derived data acquired by the U.S. Army Corps of Engineers (USACE) Joint Airborne Lidar Bathymetry Technical Center of eXpertise (JALBTCX) between December 1 and 31, 2004 (USACE-JALBTCX) and the National Oceanic and ...

Info
Seafloor Elevation Change From 2016 to 2017 at Looe Key, Florida Keys-Impacts From Hurricane Irma (version 2.0)

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes at Looe Key near Big Pine Key, Florida (FL), within a 19.7 square-kilometer area following Hurricane Irma's landfall in September 2017. USGS staff used light detection and ranging (lidar)-derived data acquired by the National Oceanic and Atmospheric Administration (NOAA) between July 21 and November 21, 2016 and USGS multibeam data collected December 12-17, 2017 (Fredericks ...

Info
Projected Seafloor Elevation Change and Relative Sea Level Rise Surrounding Maui, Hawaii 25, 50, 75, and 100 Years from 1999

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes surrounding Maui, Hawaii. Changes in seafloor elevation were calculated using historical bathymetric point data from the 1960s (see Yates and others, 2017a) and light detection and ranging (lidar)-derived data acquired in 1999 (NOAA, 2013) using methods outlined in Yate and others (2017b). An elevation change analysis between the 1960s and 1999 data was performed to quantify ...

Info
Topographic Lidar Survey of Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana, July 12-14, 2013 -- Bare Earth Digital Elevation Models (DEMs)

A topographic lidar survey was conducted on July 12-14, 2013 over Dauphin Island, Alabama and Chandeleur, Stake, Grand Gosier and Breton Islands, Louisiana. The data were collected at a nominal pulse space of 1 meter (m) and processed to identify bare earth elevations. Bare earth Digital Elevation Models (DEMs) were generated based on these data. Photo Science, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process the lidar data. The bare earth DEMs are 32-bit floating point ERDAS ...

Info
Topographic Lidar Survey of the Alabama, Mississippi, and Southeast Louisiana Barrier Islands, from September 5 to October 11, 2012 -- Bare Earth Digital Elevation Models

A topographic lidar survey was conducted from September 5 to October 11, 2012, for the barrier islands of Alabama, Mississippi and southeast Louisiana, including the coast near Port Fourchon. Most of the data were collected September 5-10, 2012, with a reflight conducted on October 11, 2012, to increase point density in some areas. The data were collected at a nominal pulse space of 1-meter (m) and processed to identify bare earth elevations. Bare earth Digital Elevation Models(DEMs) were generated based ...

Info
Topographic Lidar Survey of the Chandeleur Islands, Louisiana, February 6, 2012 -- Bare Earth DEMs

A topographic Lidar survey was conducted on February 6, 2012, over the Chandeleur Islands, Louisiana. The data were collected at a nominal pulse space of 0.5-meter (m) and processed to identify bare earth elevations. Bare earth digital elevation models (DEMs) were generated based on these data. Digital Aerial Solutions, LLC, was contracted by the U.S. Geological Survey (USGS) to collect and process the lidar data. The bare earth DEMs are 32-bit floating point ERDAS Imagine (IMG) files with a horizontal ...

Info
Biscayne National Park LIDAR GeoTIFF

Lidar is a remote sensing technique that uses laser light to detect, range, or identify remote objects based on light reflected by the object or emitted through it subsequent fluorescence. Airborne ranging lidar is now being applied in coastal environments to produce accurate, cost-efficient elevation datasets with high data density. The USGS in cooperation with NASA and NPS is using airborne lidar to measure the submerged topography of the north Florida reef tract; secondarily, the data will be assessed ...

Info
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 ...

Info
EAARL Bare Earth Topography-Fire Island National Seashore

A bare earth elevation map (also known as a Digital Elevation Model or DEM) of Fire Island National Seashore was produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with the U.S. Geological Survey (USGS), National Air and Space Administration (NASA), and the National Park Service (NPS). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft ...

Info
EAARL Topography-Fire Island National Seaashore

A first return elevation map (also known as a Digital Elevation Model or DEM) of Fire Island National Seashore was produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with the U.S. Geological Survey (USGS), National Air and Space Administration (NASA), and the National Park Service (NPS). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft ...

Info
EAARL Topography-Assateague Island National Seashore-Lidar GeoTIFF

LiDAR is a remote sensing technique that uses laser light to detect, range, or identify remote objects based on light reflected by the object or emitted through it subsequent fluorescence. Airborne ranging LiDAR is now being applied in coastal environments to produce accurate, cost-efficient elevation datasets with high data density. The USGS in cooperation with NASA and NPS is using airborne LiDAR to measure the topography of Assateague Island National Seashore land features. Elevation measurements were ...

Info
EAARL Topography-Thomas Stone National Historic Site

A first surface elevation map (also known as a Digital Elevation Model or DEM) of Thomas Stone National Historic Site was produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with the U.S. Geological Survey (USGS), National Air and Space Administration (NASA), and the National Park Service (NPS). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an ...

Info
EAARL Topography - Gateway National Recreation Area

A bare earth elevation map (also known as a Digital Elevation Model or DEM) of Gateway National Recreation Area was produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with the U.S. Geological Survey (USGS), National Air and Space Administration (NASA), and the National Park Service (NPS). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an ...

Info
EAARL Topography George Washington Birthplace National Monument

A bare earth elevation map (also known as a Digital Elevation Model or DEM) of George Washington Birthplace National Monument was produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with the U.S. Geological Survey (USGS), the National Air and Space Administration (NASA), and the National Park Service (NPS). Elevation measurements were collected over the area using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted ...

Info
EAARL Topography-Cape Cod National Seashore

Elevation maps (also known as Digital Elevation Models or DEMs) of Cape Cod National Seashore were produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with NASA and NPS. Point data in ascii text files were interpolated in a GIS to create a grid or digital elevation model (DEM) of each beach surface. Elevation measurements were collected in Massachusetts, over Cape Cod National Seashore using the NASA Experimental Advanced Airborne Research LiDAR (EAARL), a pulsed ...

Info
EAARL Topography-Gulf Islands National Seashore-Mississippi

Abstract: Elevation maps (also known as Digital Elevation Models or DEMs) of Gulf Islands National Seashore were produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with NASA and NPS. Point data in ascii text files were interpolated in a GIS to create a grid or digital elevation model (DEM) of each beach surface. Elevation measurements were collected in Florida, Mississippi and Texas, over Gulf Islands National Seashore, using the NASA Experimental Advanced ...

Info
EAARL Topography-Sagamore Hill National Historic Site

Elevation maps (also known as Digital Elevation Models or DEMs) of the Sagamore Hill National Historic Site were produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with NASA and NPS. Point data in ascii text files were interpolated in a GIS to create a grid or digital elevation model (DEM) of each beach surface. Elevation measurements were collected in New York, over the Sagamore Hill National Historic Site using the NASA Experimental Advanced Airborne Research ...

Info
EAARL Submarine Topography-Florida Keys National Marine Sanctuary

Lidar is a remote sensing technique that uses laser light to detect, range, or identify remote objects based on light reflected by the object or emitted through its subsequent fluorescence. Airborne ranging Lidar is now being applied in coastal environments to produce accurate, cost-efficient elevation datasets with high spatial density. The USGS in cooperation with NASA, NOAA, and NPS is using airborne Lidar to measure the submerged topography of the northern Florida reef tract; secondarily, the data will ...

Info
EAARL Topography-Gulf Islands National Seashore-Florida

Elevation maps (also known as Digital Elevation Models or DEMs) of Gulf Islands National Seashore were produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with NASA and NPS. Point data in ascii text files were interpolated in a GIS to create a grid or digital elevation model (DEM) of each beach surface. Elevation measurements were collected in Florida, Mississippi and Texas, over Gulf Islands National Seashore, using the NASA Experimental Advanced Airborne Research ...

Info
EAARL Topography-Padre Island National Seashore

Elevation maps (also known as Digital Elevation Models or DEMs) of Padre Island National Seashore were produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with NASA and NPS. Point data in ascii text files were interpolated in a GIS to create a grid or digital elevation model (DEM) of each beach surface. Elevation measurements were collected in Texas, over Padre Island National Seashore, using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a pulsed ...

Info
EAARL Submarine Topography-Northern Florida Keys Reef Tract

Lidar is a remote sensing technique that uses laser light to detect, range, or identify remote objects based on light reflected by the object or emitted through its subsequent fluorescence. Airborne ranging lidar is now being applied in coastal environments to produce accurate, cost-efficient elevation datasets with high spatial density. The USGS, in cooperation with NASA and NPS, is using airborne lidar to measure the submerged topography of the Northern Florida Keys Reef Tract (NFKRT); secondarily, the ...

Info
EAARL Bare Earth Topography-Colonial National Historical Park

Elevation maps (also known as Digital Elevation Models or DEMs) of Colonial National Historical Park were produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with NASA and NPS. Point data in ASCII text files were interpolated in a GIS to create a grid or digital elevation model (DEM) of each surface. Elevation measurements were collected in Virginia, over Colonial National Historical Park, using the NASA Experimental Advanced Airborne Research Lidar (EAARL), a ...

Info
Seafloor Elevation and Volume Change Analyses from 2016 to 2019 Along the Florida Reef Tract, USA

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes along the Florida Reef Tract (FRT) from Miami to Marquesas Keys within a 939.4 square-kilometer area between 2016 and 2019. USGS staff used light detection and ranging (lidar)-derived data acquired by the National Oceanic and Atmospheric Administration (NOAA) during two separate lidar surveys. The first is dataset is referenced as "2016 lidar" data and was collected between ...

Info
EAARL-B Topography—Suncook River, New Hampshire, 5-6 November 2013: Seamless (Bare Earth and Submerged)

Binary point-cloud data for part of the Suncook River in New Hampshire were produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey, in cooperation with the New Hampshire Geological Survey. Elevation measurements were collected over the area on November 5 and 6, 2013 using the second-generation Experimental Advanced Airborne Research Lidar, a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and ...

Info
Projected Seafloor Elevation Change and Relative Sea Level Rise Near St. Croix, U.S. Virgin Islands 25, 50, 75, and 100 Years from 2014

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes near Buck Island and St. Croix, U.S. Virgin Islands. Changes in seafloor elevation were calculated using historical bathymetric point data from the 1980s (see Yates and others, 2017a) and light detection and ranging (lidar)-derived data acquired in 2014 (NOAA, 2015) using methods outlined in Yates and others (2017b). An elevation change analysis between the 1980s and 2014 ...

Info
Lidar-Derived Point Cloud for EAARL-B Submerged Topography–—Saint Thomas, U.S. Virgin Islands, 2014

ASCII XYZ point cloud data for a portion of the submerged environs of Saint Thomas, U.S. Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected on March 7, 8, 11, 12, 13, 14, 17, 18, and 24, 2014 by the U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration (NOAA) Coral Reef Conservation Program. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne ...

Info
Lidar-Derived Digital Elevation Model (DEM) Mosaic for EAARL-B Submerged Topography-Saint Thomas, U.S. Virgin Islands, 2014

A submerged topography Digital Elevation Model (DEM) mosaic for a portion of the submerged environs of Saint Thomas, U.S. Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected on March 7, 8, 11, 12, 13, 14, 17, 18, and 24, 2014 by the U.S. Geological Survey, in collaboration with the National Oceanic and Atmospheric Administration (NOAA) Coral Reef Conservation Program. Elevation measurements were collected over the area using the second-generation ...

Info
Projected Seafloor Elevation Change and Relative Sea Level Rise Near St. Thomas, U.S. Virgin Islands 25, 50, 75, and 100 Years from 2014

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes near St. Thomas, U.S. Virgin Islands. Changes in seafloor elevation were calculated using historical bathymetric point data from the 1960s and 1970s (see Yates and others, 2017a) and light detection and ranging (lidar)-derived elevation data acquired in 2014 (NOAA, 2015) using methods outlined in Yates and others (2017b). An elevation change analysis between the historical ...

Info
Transects_BackBarrier.shp - Digital Shoreline Analysis System version 4.3 Transects with Linear Regression Rate Calculations for the Back-Barrier (North-Facing) coast of Dauphin Island, Alabama.

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

Info
Aerial photomosaic of John Day Reservoir, 1966

A two-week field operation was conducted in the John Day Reservoir on the Columbia River to image the floor of the pool, to measure the distribution and thickness of post-impoundment sediment, and to verify these geophysical data with video photography and bottom sediment samples. The field program was a cooperative effort between the USGS Coastal and Marine Geology Team of the Geologic Division and the USGS Columbia River Research Laboratory of the Biological Resources Division. The data collection was ...

Info
Coastal Marine Geology Program Video and Photograph Portal

Access to the U.S. Geological Survey (USGS) Coastal and Marine Geology Program’s (CMGP) vast collection of unique and valuable seafloor and coastal imagery is made available in the CMGP Video and Photograph Portal. The portal provides a single location for data discovery and viewing. The CMGP and our research partners invest immense resources collecting, processing, and archiving seafloor and oblique coastal video and photographs. Until the publication of the CMGP Video and Photograph Portal in 2015, only ...

Info
Orthophotomosaic image (natural color) of the north coast of Barter Island, Alaska acquired on September 07 2014 (GeoTIFF image; 11-cm resolution)

Aerial photographs were collected from a small, fixed-wing aircraft over the coast of Barter Island, Alaska on September 07 2014. Precise aircraft position information and structure-from-motion photogrammetric methods were combined to derive a high-resolution orthophotomosaic. This orthophotomosaic contain 3-band, 8-bit, unsigned raster data (red/green/blue; file format-GeoTIFF) with a ground sample distance (GSD) resolution of 11 cm. The file employs Lempel-Ziv-Welch (LZW) compression. This ...

Info
Orthophotomosaic image (natural color) of the north coast of Barter Island, Alaska acquired on July 01 2014 (GeoTIFF image, 19-cm resolution)

Aerial photographs were collected from a small, fixed-wing aircraft over the coast of Barter Island, Alaska on July 01 2014, September 07 2014. Precise aircraft position information and structure-from-motion photogrammetric methods were combined to derive a high-resolution orthophotomosaic. This orthophotomosaic contain 3-band, 8-bit, unsigned raster data (red/green/blue; file format-GeoTIFF) with a ground sample distance (GSD) resolution of 19 cm. The file employs Lempel-Ziv-Welch (LZW) compression. This ...

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Info
Geometrically corrected image mosaic of 1936 aerial photographs of Rincon, Puerto Rico (mosaic_1936.tif)

The 8 km of shoreline from Punta Higuero to Punta Cadena in Rincón, Puerto Rico is experiencing long-term coastal erosion. This study documents historical shoreline changes at Rincón for the period 1936-2005. Twelve historical shoreline positions were compiled from existing data, new orthophotography, and GPS field surveys.

Info
Geometrically corrected image mosaic of 1983 aerial photographs of Rincon, Puerto Rico (mosaic_1983.tif)

The 8 km of shoreline from Punta Higuero to Punta Cadena in Rincón, Puerto Rico is experiencing long-term coastal erosion. This study documents historical shoreline changes at Rincón for the period 1936-2005. Twelve historical shoreline positions were compiled from existing data, new orthophotography, and GPS field surveys.

Info
Geometrically corrected image mosaic of 1987 aerial photograps of Rincon, Puerto Rico (mosiac_1987.tif)

The 8 km of shoreline from Punta Higuero to Punta Cadena in Rincón, Puerto Rico is experiencing long-term coastal erosion. This study documents historical shoreline changes at Rincón for the period 1936-2005. Twelve historical shoreline positions were compiled from existing data, new orthophotography, and GPS field surveys.

Info
24-bit True Color NE Quadrant of RINCON NE, Orthophoto Production for Puerto Rico and US Virgin Islands (rincon1_2004.tif)

This dataset is a single orthoimage from a collection of GeoTIFF format natural color orthoimages covering the islands of Puerto Rico, Mona, Desecheo, Culebra, Vieques, and the US Virgin Islands. An orthophoto is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Each orthophoto provides imagery for ...

Info
24-bit True Color NW Quadrant of RINCON NE, Orthophoto Production for Puerto Rico and US Virgin Islands (rincon2_2004.tif)

This dataset is a single orthoimage from a collection of GeoTIFF format natural color orthoimages covering the islands of Puerto Rico, Mona, Desecheo, Culebra, Vieques, and the US Virgin Islands. An orthophoto is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Each orthophoto provides imagery for ...

Info
24-bit True Color SE Quadrant of RINCON NE, Orthophoto Production for Puerto Rico and US Virgin Islands (rincon3_2004.tif)

This dataset is a single orthoimage from a collection of GeoTIFF format natural color orthoimages covering the islands of Puerto Rico, Mona, Desecheo, Culebra, Vieques, and the US Virgin Islands. An orthophoto is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Each orthophoto provides imagery for ...

Info
24-bit True Color SW Quadrant of RINCON NE, Orthophoto Production for Puerto Rico and US Virgin Island (rincon4_2004.tif)

This dataset is a single orthoimage from a collection of GeoTIFF format natural color orthoimages covering the islands of Puerto Rico, Mona, Desecheo, Culebra, Vieques, and the US Virgin Islands. An orthophoto is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Each orthophoto provides imagery for ...

Info
24-bit True Color NE Quadrant of RINCON W NE, Orthophoto Production for Puerto Rico and US Virgin Islands (rincon5_2004.tif)

This dataset is a single orthoimage from a collection of GeoTIFF format natural color orthoimages covering the islands of Puerto Rico, Mona, Desecheo, Culebra, Vieques, and the US Virgin Islands. An orthophoto is remotely sensed image data in which displacement of features in the image caused by terrain relief and sensor orientation have been mathematically removed. Orthophotography combines the image characteristics of a photograph with the geometric qualities of a map. Each orthophoto provides imagery for ...

Info
Positions of temporary targets used as ground control points associated with UAS flights over Black Beach, Falmouth, Massachusetts on 18 March 2016 (text file)

Imagery acquired with unmanned aerial systems (UAS) and coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Survey worked in collaboration with members of the Marine Biological Laboratory and Woods Hole Analytics at Black ...

Info
High-resolution orthomosaic image (natural color) of Black Beach, Falmouth, Massachusetts on 18 March 2016 (32-bit GeoTIFF)

Imagery acquired with unmanned aerial systems (UAS) and coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Survey worked in collaboration with members of the Marine Biological Laboratory and Woods Hole Analytics at Black ...

Info
Elevations surveyed at Black Beach, Falmouth, Massachusetts on 18 March 2016 (text file)

Imagery acquired with unmanned aerial systems (UAS) and coupled with structure from motion (SfM) photogrammetry can produce high-resolution topographic and visual reflectance datasets that rival or exceed lidar and orthoimagery. These new techniques are particularly useful for data collection of coastal systems, which requires high temporal and spatial resolution datasets. The U.S. Geological Survey worked in collaboration with members of the Marine Biological Laboratory and Woods Hole Analytics at Black ...

Info
EAARL Topography-Dry Tortugas National Park

Lidar is a remote sensing technique that uses laser light to detect, range, or identify remote objects based on light reflected by the object or emitted through it subsequent fluorescence. Airborne ranging lidar is now being applied in coastal environments to produce accurate, cost-efficient elevation datasets with high data density. The USGS in cooperation with NASA and NPS is using airborne lidar to measure the submerged topography of the Dry Tortugas reef tract and Subaerail topography of land features ...

Info
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 ...

Info
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.

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

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

Info
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 ...

Info
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 ...

Info
Low-altitude aerial imagery collected from a Helikite at 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 ...

Info
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 ...

Info
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 ...

Info
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.

Info
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 ...

Info
Low-altitude georeferenced aerial imagery collected from a Helikite at Marconi Beach, Wellfleet on March 11, 2022

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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
Aerial imagery from the UAS survey of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01

This portion of the data release presents the raw aerial imagery collected during the unoccupied aerial system (UAS) survey of the Los Padres Reservoir delta, Carmel River valley, CA, 2017-11-01. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. A total of six flights were conducted for the ...

Info
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. ...

Info
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, ...

Info
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 ...

Info
Location of sea floor video tracklines along with videos collected in 2014 by the U.S. Geological Survey offshore of Fire Island, NY (MP4 videos files and Esri polyline shapefile, Geographic, WGS 84)

The U.S. Geological Survey (USGS) conducted a geophysical and sampling survey in October 2014 that focused on a series of shoreface-attached ridges offshore of western Fire Island, NY. Seismic-reflection data, surficial grab samples and bottom photographs and video were collected along the lower shoreface and inner continental shelf. The purpose of this survey was to assess the impact of Hurricane Sandy on this coastal region. These data were compared to seismic-reflection and surficial sediment data ...

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

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

Info
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 ...

Info
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. ...

Info
Brittle Stars--Santa Barbara Channel, California

This part of DS 781 presents data for the map showing the predicted distribution of brittle stars in the Santa Barbara Channel, California, region. The raster data file is included in "BrittleStars_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas ...

Info
Cup Corals--Santa Barbara Channel, California

This part of DS 781 presents data for the map showing the predicted distribution of cup corals in the Santa Barbara Channel, California, region. The raster data file is included in "CupCorals_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas along the ...

Info
Hydroids--Santa Barbara Channel, California

This part of DS 781 presents data for the map showing the predicted distribution of hydroids in the Santa Barbara Channel, California, region. The raster data file is included in "Hydroids_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas along the ...

Info
Short Sea Pens--Santa Barbara Channel, California

This part of DS 781 presents data for the map showing the predicted distribution of short sea pens in the Santa Barbara Channel, California, region. The raster data file is included in "ShortSeaPens_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas ...

Info
Tall Sea Pens--Santa Barbara Channel, California

This part of DS 781 presents data for the map showing the predicted distribution of tall sea pens in the Santa Barbara Channel, California, region. The raster data file is included in "TallSeaPens_SantaBarbaraChannel.zip," which is accessible from https://pubs.usgs.gov/ds/781/SantaBarbaraChannel/data_catalog_SantaBarbaraChannel.html. Presence-absence data of benthic macro-invertebrates and associated habitat (that is, sediment type and depth) were collected using a towed camera sled in selected areas along ...

Info
3D bathymetric surfaces of low- and high-relief sites from the coral reef flat off Waiakane, Molokai

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

Info
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.

Info
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" ...

Info
Digital Surface Models (DSM) from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017

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

Info
Ground control point locations for UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017

This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during the August 2017 unoccupied aerial system (UAS) surveys of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. Eighteen temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of ...

Info
Aerial imagery from UAS surveys of beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017

This portion of the data release presents the raw aerial imagery collected during the uncrewed aerial system (UAS) survey conducted on the ocean beaches adjacent to the Columbia River Mouth at the Oregon-Washington border in August 2017. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. The ...

Info
Topographic point clouds from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, August 2017

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

Info
Ground control point locations for UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, July 2021

This portion of the data release presents the locations of the temporary ground control points (GCPs) used for the structure-from-motion (SfM) processing of the imagery collected during the July 2021 unoccupied aerial system (UAS) surveys of the ocean beach at Fort Stevens State Park, OR, and Benson Beach at Cape Disappointment State Park, WA. Eighteen temporary ground control points (GCPs) were distributed throughout the survey area to establish survey control. The GCPs consisted of a combination of small ...

Info
Aerial imagery from UAS surveys of beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, July 2021

This portion of the data release presents the raw aerial imagery collected during the uncrewed aerial system (UAS) survey conducted on the ocean beaches adjacent to the Columbia River Mouth at the Oregon-Washington border in July 2021. The imagery was acquired using a Department of Interior-owned 3DR Solo quadcopter fitted with a Ricoh GR II digital camera featuring a global shutter. The camera was mounted using a fixed mount on the bottom of the UAS and oriented in an approximately nadir orientation. The ...

Info
Topographic point clouds from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, July 2021

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

Info
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 ...

Info
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 ...

Info
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 ...

Info
Low-altitude aerial imagery collected from a Helikite at 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 ...

Info
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 ...

Info
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 ...

Info
Low-altitude aerial imagery collected from a kite at Head of the Meadow Beach, Truro during field activity 2020-015-FA on March 6, 2020

The data in this release map the beach and nearshore environment at Head of the Meadow Beach in Truro, MA and provide environmental context for the camera calibration information for the 2019 CoastCam installation that looks out at the coast shared by beachgoers, shorebirds, seals, and sharks. This is related to the field activity 2020-015-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 the CoastCam, which are ...

Info
Digital surface model representing Head of the Meadow Beach, Truro during field activity 2021-014-FA on February 04, 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 ...

Info
Low-altitude aerial imagery collected from a Helikite at Head of the Meadow Beach, Truro 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 ...

Info
Bathymetric grid during field activity 2021-022-FA offshore Marconi Beach, Wellfleet MA on March 10, 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 ...

Info
Digital surface model representing Marconi Beach, Wellfleet 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 ...

Info
Low-altitude aerial imagery collected from a helium powered balloon-kite at Marconi Beach, Wellfleet 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 ...

Info
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 ...

Info
Digital Surface Models (DSM) from UAS surveys of the beaches at Fort Stevens State Park, OR, and Cape Disappointment State Park, WA, July 2021

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

Info
Topographic digital surface model (DSM) for Whiskeytown Lake and surrounding area, 2019-11-12

This portion of the data release presents a digital surface model (DSM) and hillshade of Whiskeytown Lake and the surrounding area derived from Structure from Motion (SfM) processing of aerial imagery acquired on 2019-11-12. Unlike a digital elevation model (DEM), the DSM represents the elevation of the highest object within the bounds of a cell. Vegetation, buildings and other objects have not been removed from the data. In addition, data artifacts resulting from noise and vegetation in the original ...

Info
Orthomosaic imagery for Whiskeytown Lake and surrounding area, northern California, 2019-11-12

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

Info
Orthomosaic imagery for Whiskeytown Lake and surrounding area, northern California, 2020-11-10

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

Info
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 ...

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

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

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

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

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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.

Info
ROV Tracklines from 1999 in the Pulley Ridge area in the Gulf of Mexico

Pulley Ridge is a series of drowned barrier islands that extends almost 200 km in 60-100 m water depths. This drowned ridge is located on the Florida Platform in the southeastern Gulf of Mexico about 250 km west of Cape Sable, Florida. This barrier island chain formed during the initial stage of the Holocene marine transgression. These islands were then submerged and left abandoned near the outer edge of the Florida Platform. The southern portion of Pulley Ridge hosts zooxanthellate scleractinian corals, ...

Info
ROV Tracklines from 2001 in the Pulley Ridge are in the Gulf of Mexico based on 5-min navigation

Pulley Ridge is a series of drowned barrier islands that extends almost 200 km in 60-100 m water depths. This drowned ridge is located on the Florida Platform in the southeastern Gulf of Mexico about 250 km west of Cape Sable, Florida. This barrier island chain formed during the initial stage of the Holocene marine transgression. These islands were then submerged and left abandoned near the outer edge of the Florida Platform. The southern portion of Pulley Ridge hosts zooxanthellate scleractinian corals, ...

Info
ROV Point Navigation from 2001 in the Pulley Ridge are in the Gulf of Mexico based on 5-min navigation

Pulley Ridge is a series of drowned barrier islands that extends almost 200 km in 60-100 m water depths. This drowned ridge is located on the Florida Platform in the southeastern Gulf of Mexico about 250 km west of Cape Sable, Florida. This barrier island chain formed during the initial stage of the Holocene marine transgression. These islands were then submerged and left abandoned near the outer edge of the Florida Platform. The southern portion of Pulley Ridge hosts zooxanthellate scleractinian corals, ...

Info
MPEG Animation of the Southern Portion of the Pulley Ridge Study Area

Pulley Ridge is a series of drowned barrier islands that extends almost 200 km in 60-100 m water depths. This drowned ridge is located on the Florida Platform in the southeastern Gulf of Mexico about 250 km west of Cape Sable, Florida. This barrier island chain formed during the initial stage of the Holocene marine transgression. These islands were then submerged and left abandoned near the outer edge of the Florida Platform. The southern portion of Pulley Ridge hosts zooxanthellate scleractinian corals, ...

Info
Sustainable Seas Expedition Tracklines: Years 2000 and 2001

Pulley Ridge is a series of drowned barrier islands that extends almost 200 km in 60-100 m water depths. This drowned ridge is located on the Florida Platform in the southeastern Gulf of Mexico about 250 km west of Cape Sable, Florida. This barrier island chain formed during the initial stage of the Holocene marine transgression. These islands were then submerged and left abandoned near the outer edge of the Florida Platform. The southern portion of Pulley Ridge hosts zooxanthellate scleractinian corals, ...

Info
Sustainable Seas Expedition Points along Tracks: Years 2000 and 2001

Pulley Ridge is a series of drowned barrier islands that extends almost 200 km in 60-100 m water depths. This drowned ridge is located on the Florida Platform in the southeastern Gulf of Mexico about 250 km west of Cape Sable, Florida. This barrier island chain formed during the initial stage of the Holocene marine transgression. These islands were then submerged and left abandoned near the outer edge of the Florida Platform. The southern portion of Pulley Ridge hosts zooxanthellate scleractinian corals, ...

Info
Low-altitude aerial imagery collected from a Helikite at 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. ...

Info
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. ...

Info
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 ...

Info
Geotagged low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ...

Info
Braddock East digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017 (32-bit floating point GeoTIFF image).

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ...

Info
Braddock East orthomosaic from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017 (GeoTIFF image).

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ...

Info
Braddock East point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017 (LAZ file).

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ...

Info
Braddock West digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017 (32-bit floating point GeoTIFF image).

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ...

Info
Braddock West orthomosaic from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017 (GeoTIFF image).

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ...

Info
Braddock West point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Braddock Bay, New York in July 2017 (LAZ file).

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinities of Braddock Bay, Sodus Bay, and Chimney Bluffs State Park, New York. This data release includes images tagged ...

Info
Point cloud from low-altitude aerial imagery from unmanned aerial system (UAS) flights over Coast Guard Beach, Nauset Spit, Nauset Inlet, and Nauset Marsh, Cape Cod National Seashore, Eastham, Massachusetts on 1 March 2016 (LAZ file)

This point cloud was derived from low-altitude aerial images collected from an unmanned aerial system (UAS) flown in the Cape Cod National Seashore on 1 March, 2016. The objective of the project was to evaluate the quality and cost of mapping from UAS images. The point cloud contains 434,096,824 unclassifed and unedited geolocated points. The points have horizontal coordinates in NAD83(2011) UTM Zone 19 North meters, vertical coordinates in NAVD88 meters, and colors in the red-green-blue (RGB) schema. The ...

Info
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 ...

Info
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 ...

Info
Multispectral aerial imagery from unmanned aerial systems (UAS) flights and image locations: Plum Island Estuary and Parker River NWR (PIEPR), February 27th, 2018

Low-altitude (80 and 100 meters above ground level) digital images were taken over an area of the Plum Island Estuary and Parker River National Wildlife Refuge (NWR) in Massachusetts using 3DR Solo unmanned aircraft systems (UAS) on February 27, 2018. These images were collected as part of an effort to document marsh stability over time and quantify sediment movement using UAS technology. Each UAS was equipped with either a Ricoh GRII digital camera for natural color photos, used to produce digital ...

Info
True color aerial imagery from unmanned aerial systems (UAS) flights and image locations: Plum Island Estuary and Parker River NWR (PIEPR), February 27th, 2018

Low-altitude (80 and 100 meters above ground level) digital images were taken over an area of the Plum Island Estuary and Parker River National Wildlife Refuge (NWR) in Massachusetts using 3DR Solo unmanned aircraft systems (UAS) on February 27, 2018. These images were collected as part of an effort to document marsh stability over time and quantify sediment movement using UAS technology. Each UAS was equipped with either a Ricoh GRII digital camera for natural color photos, used to produce digital ...

Info
Chimney Bluffs digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Chimney Bluffs, New York in July 2017 (32-bit floating point GeoTIFF image)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Chimney Bluffs State Park, New York. This data release includes images tagged with locations determined from ...

Info
Chimney Bluffs orthomosaic from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Chimney Bluffs, New York in July 2017 (GeoTIFF image)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Chimney Bluffs State Park, New York. This data release includes images tagged with locations determined from ...

Info
Chimney Bluffs point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Chimney Bluffs, New York in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Chimney Bluffs State Park, New York. This data release includes images tagged with locations determined from ...

Info
Geotagged low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Chimney Bluffs, New York in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), in three locations along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Chimney Bluffs State Park, New York. This data release includes images tagged with locations determined from ...

Info
Charles Point digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (32-bit floating point GeoTIFF image)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Charles Point orthomosaic from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (GeoTIFF image)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Charles Point point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (LAZ file)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Greig Street digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (32-bit floating point GeoTIFF image)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Greig Street orthomosaic from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (GeoTIFF image)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Greig Street point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (LAZ file)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Lake Bluffs digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (32-bit floating point GeoTIFF image)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Lake Bluffs orthomosaic from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (GeoTIFF image)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Lake Bluffs point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (LAZ file)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Geotagged low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York, in July 2017

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Sodus North digital elevation model (DEM) from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (32-bit floating point GeoTIFF image)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Sodus North orthomosaic from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (GeoTIFF image)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
Sodus North point cloud from low-altitude aerial imagery from unmanned aerial systems (UAS) flights over of the Lake Ontario shoreline in the vicinity of Sodus Bay, New York in July 2017 (LAZ file)

Low-altitude (80-100 meters above ground level) digital images were obtained from a camera mounted on a 3DR Solo quadcopter, a small unmanned aerial system (UAS), along the Lake Ontario shoreline in New York during July 2017. These data were collected to document and monitor effects of high lake levels, including shoreline erosion, inundation, and property damage in the vicinity of Sodus Bay, New York. This data release includes images tagged with locations determined from the UAS GPS; tables with updated ...

Info
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 ...

Info
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 ...

Info
Digital Surface Models (DSM) from UAS surveys of the upper reservoir delta at Jenkinson Lake, El Dorado County, California

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

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
Low-altitude aerial imagery collected from a UAS at 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 ...

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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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 ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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, ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
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 ...

Info
Structure-from-Motion orthophotos from the Florida Keys, 2019

Georeferenced orthophotos were created from structure-from-motion (SfM) data using seafloor images collected using the new 5-camera system SfM Quantitative Underwater Imaging Device with Five Cameras (SQUID-5). Images were collected in July 2019 by towing the SQUID-5 in 3 to 4 meters of water off of Islamorada in the Florida Keys during 3 days. The five cameras were synchronized together and with a survey-grade Global Positioning System (GPS). Images were collected over diverse benthic settings, including ...

Info