This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Salt Point map area, California. The vector data file is included in "Habitat_OffshoreSaltPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSaltPoint/data_catalog_OffshoreSaltPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., ...

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of San Francisco map area, California. The vector data file is included in "Habitat_SanFrancisco.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanFrancisco/data_catalog_OffshoreSanFrancisco.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Endris, C.A., Manson, M.W., Sliter, R.W., Kvitek, R.G. ...

This part of SIM 3306 presents data for the habitat map of the Offshore of San Gregorio map area, California. The vector data file is included in "Habitat_OffshoreSanGregorio.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSanGregorio/data_catalog_OffshoreSanGregorio.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Watt, J.T., Golden, N.E., Endris, C.A., Phillips, E.L., Hartwell, S.R., Johnson, S.Y., Kvitek, R.G., Erdey, M.D., Bretz, C ...

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

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Santa Cruz map area, California. The vector data file is included in "Habitat_OffshoreSantaCruz.zip," which is accessible from https://doi.org/10.5066/F7TM785G. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Erdey, M.D., Golden, N.E., Greene, H.G., Dieter, B.E., Hartwell, S.R., Ritchie, A.C., Finlayson, D.P., Endris, C.A., Watt, J.T., Davenport, C.W., Sliter, R.W., Maier ...

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Bodega Head map area, California. The vector data file is included in "Habitat_OffshoreBodegaHead.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E. ...

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Point Reyes map area, California. The vector data file is included in "Habitat_PointReyes.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, ...

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Tomales Point map area, California. The polygon shapefile is included in "Habitat_OffshoreTomalesPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreTomalesPoint/data_catalog_OffshoreTomalesPoint.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Greene, H.G., Erdey, M.D., Cochrane, G.R., Watt, J.T., Kvitek, R.G., Manson, M.W., ...

This part of DS 781 presents habitat data in the Offshore of Carpinteria map area, California. The vector data file is included in "Habitat_OffshoreCarpinteria.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCarpinteria/data_catalog_OffshoreCarpinteria.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., Endris, C.A., Seitz, G.G., Sliter, R.W., Erdey, M.D., Wong, F.L ...

This part of DS 781 presents the habitat map of the Offshore of Coal Oil Point map area, California. The vector data file is included in "Habitat_OffshoreCoalOilPoint.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreCoalOilPoint/data_catalog_OffshoreCoalOilPoint.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., Dieter, B.E., Conrad, J.E., Lorenson, T.D., Krigsman, L.M., Greene, ...

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Fort Ross map area, California. The polygon shapefile is included in "Habitat_OffshoreFortRoss.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreFortRoss/data_catalog_OffshoreFortRoss.html. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, ...

This part of DS 781 presents the habitat map of the Offshore of Refugio Beach map area, California. The vector data file is included in "Habitat_RefugioBeach.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreRefugioBeach/data_catalog_OffshoreRefugioBeach.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., Krigsman, L.M., Dieter, B.E., Conrad, J.E., Greene, H.G., Seitz, G.G., Endris, C.A., Sliter ...

This part of DS 781 presents data for the habitat map of the Offshore of Santa Barbara map area, California. The vector data file is included in "Habitat_OffshoreSantaBarbara.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreSantaBarbara/data_catalog_OffshoreSantaBarbara.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., Greene, H.G., Krigsman, L.M., Kvitek, R.G., Dieter, B.E., Endris, C.A., ...

This part of DS 781 presents habitat data in the Offshore of Ventura map area, California. The vector data file is included in "Habitat_OffshoreVentura.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreVentura/data_catalog_OffshoreVentura.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., Seitz, G.G., Gutierrez, C.I., Sliter, R.W., Erdey ...

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Pacifica map area, California. The vector data file is included in "Habitat_OffshorePacifica.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshorePacifica/data_catalog_OffshorePacifica.html. These data accompany the pamphlet and map sheets of Edwards, B.D., Phillips, E.L., Dartnell, P., Greene, H.G., Bretz, C.K., Kvitek, R.G., Hartwell, S.R., Johnson, S.Y., Cochrane, G.R., Dieter, B.E., Sliter, R.W., Ross ...

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Bolinas map area, California. The vector data file is included in "Habitat_OffshoreBolinas.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., ...

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Half Moon Bay map area, California. The polygon shapefile is included in "Habitat_OffshoreHalfMoonBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/OffshoreHalfMoonBay/data_catalog_OffshoreHalfMoonBay.html. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Greene, H.G., Johnson, S.Y., Golden, N.E., Hartwell, S.R., Dieter, B.E., Manson, M.W., Sliter, R.W., Ross, S.L., Watt, J ...

This part of DS 781 presents data for the habitat map of the seafloor of the Drakes Bay and Vicinity map area, California. The vector data file is included in "Habitat_DrakesBay.zip," which is accessible from https://pubs.usgs.gov/ds/781/DrakesBay/data_catalog_DrakesBay.html. These data accompany the pamphlet and map sheets of Watt, J.T., Dartnell, P., Golden, N.E., Greene, H.G., Erdey, M.D., Cochrane, G.R., Johnson, S.Y., Hartwell, S.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Sliter, R.W., ...

This part of DS 781 presents data for the habitat map of the seafloor of the Hueneme Canyon and Vicinity map area, California. The vector data file is included in "Habitat_HuenemeCanyon.zip," which is accessible from http://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 ...

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Monterey map area, California. The vector data file is included in "Habitat_OffshoreMonterey.zip," which is accessible from https://doi.org/10.5066/F70Z71C8. These data accompany the pamphlet and map sheets of Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds. ...

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

This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Scott Creek map area, California. The vector data file is included in "Habitat_OffshoreScottCreek.zip," which is accessible from https://doi.org/10.5066/F7CJ8BJW. These data accompany the pamphlet and map sheets of Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Watt, J.T., Krigsman, L.M., Ritchie, A.C., ...

A benthic habitat polygon coverage has been created of the coral reef ecosystem within and adjacent to Kaloko-Honokohau (KAHO) National Historical Park on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate ...

Underwater video was collected in March 2014 in the nearshore waters of Faga`alu Bay on the island of Tutuila, American Samoa, as part of the U.S. Geological Survey Coastal and Marine Geology Program's Pacific Coral Reefs Project. This dataset includes 2,119 still images extracted from the video footage every 10 seconds and an Environmental Systems Research Institute (ESRI) shapefile of individual still-image locations with benthic habitat interpretations for each image.

A benthic habitat polygon coverage has been created of the coral reef ecosystem off the coast of Pu'uhonua O Honaunau (PUHO) National Historical Park on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, ...

This shapefile contains habitat polygons identifying the dominant and major geomorphological structure, biological type and percent cover, and geologic zone for 11 square kilometers of Olowalu reef off west-central Maui at a minimum mapping unit of 100 square meters. Habitats were mapped with heads-up digitization using the NOAA Habitat Digitizer Extension in ArcMap (Esri, v.10.8.2). Seafloor characteristics were based on visual interpretation of 3-band (red, green, blue) 0.5m satellite orthoimagery, 1-m ...

A benthic habitat polygon coverage has been created of the coral reef ecosystem on the south shore of Moloka'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major Biological Cover, Percent of Major Biological Cover, Reef Zone ...

A benthic habitat polygon coverage has been created of the coral reef ecosystem within the U.S. Coral Reef Task Force Watershed Partnership Initiative Kaanapali priority study area and the State of Hawaii Kahekili Herbivore Fisheries Management Area, West-Central Maui, Hawaii. Polygons were hand-digitized from visual interpretation of QuickBird-2 satellite imagery (2005), and SHOALS bathymetry data. We also utilized in situ knowledge from underwater photography and videography (2002-2011), side-scan sonar ...

A benthic habitat polygon coverage has been created of the coral reef ecosystem off the coast of Pu'ukohola Heiau (PUHE) National Historic Site on the Kona Coast of Hawai'i. Polygons were hand-digitized from visual interpretation of aerial photography and SHOALS bathymetry data. We also utilized in situ knowledge from towed instruments, underwater photography and videography, and diver and snorkeler observations. The polygons have attributes for Main Structure/Substrate, Dominant Structure/Substrate, Major ...

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, ...

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 ...

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, ...

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, ...

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 ...

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, ...

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, ...

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, ...

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 ...

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 ...

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 ...

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 ...

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, ...

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, ...

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 ...

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, ...

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, ...

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, ...

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 ...

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, ...

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, ...

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, ...

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 ...

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, ...

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, ...

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 ...

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, ...

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, ...

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, ...

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 ...

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, ...

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, ...

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, ...

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 ...

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, ...

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, ...

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 ...

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 ...

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, ...

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 ...

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, ...

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, ...

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, ...

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 ...

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, ...

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 ...

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, ...

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 ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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 ...

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 ...

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, ...

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, ...

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 ...

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 ...

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, ...

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, ...

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 ...

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, ...

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 ...

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, ...

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, ...

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 ...

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, ...

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, ...

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 ...

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, ...

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, ...

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, ...

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, ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Sediment grain-size distributions and total organic carbon contents were measured at four intertidal sites and three subtidal sites along the urban waterfront (east shore) of Bellingham Bay, Washington, July 3-11, 2019 and June 6-August 31, 2020. Intertidal substrate was sampled in eelgrass beds, and subtidal substrate was sampled inside and outside of the deep edge of eelgrass beds.

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) project collects aerial imagery along coastal swaths 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 vulnerability and response to ...

The U.S. Geological Survey (USGS) Remote Sensing Coastal Change (RSCC) and Processes Impacting Seafloor Change and Ecosystem Services (PISCES) projects collect underwater imagery of coral reefs and other scientifically interesting, submerged environments using the novel SfM (Structure-from-Motion) Quantitative Underwater Imaging Device with 5 cameras (SQUID-5) system. This sensor collects imagery with optimized endlap/sidelap and precise position information to create high-resolution orthomosaics, three ...

This is a set of 1962 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, ...

This is a set of 4599 vertical aerial photogrammetric images and their derivatives, collected from Lonoak vicinity with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files 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 ...

This is a set of 2135 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 ...

Results of a survey of samples collected from 1930 to 2024 along the west coast of the United States from Alaska to San Diego, California as well as Honolulu, Hawaii for the presence of the Asian nonindigenous benthic foraminifera Trochammina hadai.

This data release provides census counts of the non-indigenous benthic foraminifera Trochammina hadai Uchio in surface sediment samples obtained in San San Francisco Bay, California from 1983-2024.

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 642 primarily near-nadir aerial photogrammetric images and their derivatives, collected from the Elwha River, WA, with an intervalometer-triggered digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes, primarily during and after dam removal on the Elwha River, at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {YYYYMMDDHHMMSS}_{SN ...

This is a set of 2361 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, ...

This is a set of 3012 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, ...

This is a set of 5136 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, ...

These metadata describe Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) attributed polygons derived from multibeam echosounder acoustic bathymetry and backscatter intensity data, and from underwater video collected offshore of Morro Bay, California from 2016 to 2020. The polygons have CMECS substrate, geoform and biotic component attributes. Most of the data were collected in support of the U.S. Geological Survey (USGS)/Bureau of Ocean Energy Management ...

This is a set of 2872 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, ...

This is a set of 4937 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, ...

This is a set of 1151 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, ...

This is a 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 "Elwha PlaneCam" system which consists of one or two cameras mounted in the wing inspection plate(s) of a Cessna 172 flown by Rite Bros. Aviation on flights coordinated through the Department of the Interior's (DOI) Office of Aviation Services (OAS), Olympic National Park, and/or USGS Pacific Coastal and Marine ...

This is a set of 8444 oblique aerial photogrammetric images and their derivatives, collected from Pelican State Beach to Point Bonita with a fixed-lens digital camera from a crewed light aircraft, for processing using structure-from-motion photogrammetry and machine learning to study coastal geomorphic processes at high temporal and spatial resolution. JPG files in each folder follow the following naming convention: {CAM###}_{YYYYMMDDHHMMSS_ss}.jpg, where {CAM###} is the last 3 digits of the camera serial ...

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.

Underwater video imagery was collected in March 2014 in the nearshore waters of Faga'alu Bay on the Island of Tutuila, American Samoa, as part of the U.S. Geological Survey Coastal and Marine Geology Program's Pacific Coral Reefs Project. Included here are 40 video files in .mpg format and an Environmental Systems Research Institute (ESRI) shapefile with location (navigation) points every two seconds.

Conductivity-Temperature-Depth (CTD) profile data were collected along transects across study areas of west and east Hawaii Island between 2010 and 2014. Measurements were made over a range of tide and weather conditions and help characterize the spatial extent and variability in estuarine conditions across the reef when grouped by 1 to 2-hour survey period or by season. Sites of cold and warm groundwater discharge along east Hawaii were characterized for comparison.

Spatial measurements of water temperature, specific conductance, salinity, pH, dissolved oxygen, and turbidity between 0.25 and 0.50 m water depth were collected every 10-seconds along and across shore at 12 principal study areas along west and east Hawaii Island. Measurements were made between 2010 and 2013 during different seasons and tide states over the course of 1.0 to 2.5 hours to evaluate the spatial and temporal extent of water properties that influence coral reef health and coral reef habitat ...

Time-series data of water level, water temperature, and salinity were collected at 10 locations along west Hawaii Island between 2010 and 2011 in nearshore coral reef settings. Conductivity-temperature-depth sensors were attached to fossil limestone, rock, or dead coral within otherwise healthy coral reef settings spanning water depths of 8 to 23 ft. Continuous measurements were made every 10 or 20 minutes.

Time-series data of water temperature were collected at 33 locations along the west coast of the Island of Hawaii, including within Kaloko-Honokohau National Historical Park (KAHO), and Puu o Honaunau National Historical Park (PUHO) between 2010 and 2013 in nearshore coral reef and anchialine pool settings. Temperature sensors were attached to fossil limestone, rock or dead coral within otherwise healthy coral reef settings spanning water depths of 0.1 to 8.84 m (0.3 to 29.0 ft). Continuous measurements ...

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between the Hulahula River and the Colville River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was used as ...

This dataset consists of short-term (~31 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2010. A reference baseline was used as ...

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the sheltered north coast of Alaska coastal region between the Hulahula River and the Colville River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was used as ...

This dataset consists of short-term (~31 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2010. A reference baseline was used as ...

This dataset includes shorelines from 63 years ranging from 1947 to 2010 for the north coast of Alaska between the Hulahula River and the Colville River. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), Conoco-Philips (CP), British Petroleum Alaska (BPXA)), satellite imagery (State of Alaska), and lidar elevation data (USGS). ...

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between the U.S. Canadian Border to the Hulahula River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was ...

This dataset consists of short-term (~32 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1978 and 2010. A reference baseline was ...

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the sheltered north coast of Alaska coastal region between the U.S. Canadian Border to the Hulahula River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was ...

This dataset consists of short-term (~32 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1978 and 2010. A reference baseline was ...

This dataset includes shorelines from 63 years ranging from 1947 to 2010 for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), satellite imagery (U.S. Fish and Wildlife Service (USFWS), State of Alaska), and lidar elevation data (USGS). ...

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between Point Barrow and Icy Cape for the time period 1947 to 2012. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the originating ...

This dataset consists of short-term (~32 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end point rate-of-change method based on available shoreline data between 1979 and 2011. A reference baseline was used as the originating point ...

This substrate, geomorphic, and geologic attributed polygon shapefile in the Offshore of Arcata, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). The map area is one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification ...

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the sheltered north coast of Alaska coastal between Point Barrow and Icy Cape for the time period 1947 to 2012. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the originating ...

This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end point rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the originating point ...

This dataset includes shorelines from 65 years ranging from 1947 to 2012 for the north coast of Alaska between Point Barrow and Icy Cape. Shorelines were compiled from topographic survey sheets and Nautical Charts (T-sheet, Nautical Chart; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), satellite imagery (State of Alaska), and lidar elevation data (USGS). Historical shoreline positions ...

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between the Colville River and Point Barrow for the time period 1947 to 2012. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the ...

This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the ...

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the sheltered north coast of Alaska coastal region between the Colville River and Point Barrow for the time period 1947 to 2012. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

This dataset consists of long-term (~65 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2012. A reference baseline was used as the ...

This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the ...

This dataset includes shorelines from 65 years ranging from 1947 to 2012 for the north coast of Alaska between the Colville River and Point Barrow. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), and lidar elevation data(USGS). Historical shoreline positions serve as easily understood features that can be used to describe ...

Observations of bleached coral were documented by scuba divers along pre-determined transects and are presented here in comma-separated format. Included in the table are coral species observed, colony size, size of bleached area on colony, and seawater temperature.

Observations of coral disease and health indicators were documented by scuba divers along pre-determined transects and are presented here in comma-separated format. Included in the table are coral species observed, colony size, types and number of indicators observed, and a size range of indicators observed.

Observations of coral species and size were documented by scuba divers along pre-determined transects and are presented here in comma-separated format.

Coral Point Count with Excel extensions (CPCe; Kohler and Gill, 2006) was used to help calculate percent of coral cover or other benthic substrates from a randomly selected subset of seafloor photographs collected on the west Hawaii Island coast.

Seafloor photographs were collected by SCUBA divers along pre-determined transects using an underwater digital camera following benthic survey protocols developed by the National Park Service (NPS) at Kaloko-Honokohau National Historical Park (Marrack and others, 2014; Weijerman and others, 2014) and modeled after the U.S. Geological Survey (USGS) and NPS coral reef survey protocols (Rogers and others, 2001; Brown and others, 2011). This dataset includes seafloor photographs in jpg format, the locations of ...

Isotopic analyses of authigenic carbonates and methanotrophic deep-sea mussels, Bathymodiolus sp., was performed on samples collected from seep fields in the Baltimore and Norfolk Canyons on the north Atlantic margin. Samples were collected using remotely operated underwater vehicles (ROVs) during three different research cruises in 2012, 2013, and 2015. Analyses were performed by several different laboratories, and the results are presented in spreadsheet format.

Acoustic-backscatter data were collected during a 2018 swath survey in the Cache Slough Complex and the Sacramento River Deep Water Ship Channel, California. Data were collected by the U.S. Geological Survey (USGS) during USGS field activity 2018-684-FA, using interferometric bathymetric sidescan sonar systems mounded to the USGS R/V San Lorenzo and the R/V Kelpfly. The backscatter data are provided as GeoTIFF images.

Geophysical properties (P-wave velocity, gamma ray density, and magnetic susceptibility), geochronologic (radiocarbon, excess Lead-210, and Cesium-137), and geochemical data (organic carbon content and 60 element contents) are reported for select vibracores collected aboard the S/V Retriever October 17-20, 2016, in San Pablo Bay, California. Geophysical properties were measured with a Geotek Multi-Sensor Core Logger (MSCL). Radiocarbon was measured by accelerator mass spectrometry (AMS). Excess Lead-210 and ...

This data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). There are 12 associated flood mask shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the degradation scenarios (Mean Elevation and Mean Erosion).

Geochemical analysis (including age-corrected radiocarbon stable isotopes, and elemental composition) and growth parameters (including calcification rate, density, and extension information) were measured from a coral core collected from a reef off the southern side of Tutuila, American Samoa. The core was collected near Matautuloa Point on 8 April 2012 in collaboration with the Ecosystem Sciences Division, Pacific Islands Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), ...

This part of the data release presents projected flooding extent polygon shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). There are eight associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the pre-storm scenario (base) and the post-storm scenarios.

This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for Commonwealth of Puerto Rico. There are eight associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the pre-storm scenario (base) and the post-storm scenarios.

This data release indicates faunal presence or absence of shelly artifacts (invertebrate remains) from the Dominican University of California archaeological site MRN-CA-254, Marin County, California.

This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for American Samoa (the islands of Tutuila, Ofu-Olosega, and Tau). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding depth point data ...

This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for Commonwealth of the Northern Mariana Islands (the islands of Saipan and Tinian). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs.

This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding depth point data ...

This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the Territory of Guam. There are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding depth point data are also presented as a comma-separated value (.csv) ...

This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the State of Hawaii (the islands of Hawaii, Kahoolawe, Kauai, Lanai, Maui, Molokai, Niihau, and Oahu). For each island there are 8 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of ...

This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the Territory of Puerto Rico (the islands of Culebra, Puerto Rico, and Vieques). For each island there are 8 associated flood mask and flood depth shapefiles: one for each four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of coral reefs. Flooding ...

This data release provides flooding extent polygons (flood masks) and depth values (flood points) based on wave-driven total water levels for 22 locations within the States of Hawaii and Florida, the Territories of Guam, American Samoa, Puerto Rico, and the U.S. Virgin Islands, and the Commonwealth of the Northern Mariana Islands. For each of the 22 locations there are eight associated flood mask polygons and flood depth point files: one for each four nearshore wave energy return periods (rp; 10-, 50-, 100- ...

This part of the data release presents projected flooding extent polygon (flood masks) and flooding depth points (flood points) shapefiles based on wave-driven total water levels for the Territory of the U.S. Virgin Islands (the islands of Saint Croix, Saint John, and Saint Thomas). For each island there are 8 associated flood mask and flood depth shapefiles: one for each four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years) and both with (wrf) and without (worf) the presence of ...

Results of radiocarbon dating of deep-sea (500 m to 700 m) black corals are presented. These corals were collected off the southeastern United States as part of the Southeastern United States Deep-Sea Corals (SEADESC) Initiative.

Geochemical analysis (including stable boron, boron:calcium ratio, and carbon and oxygen isotopes) were measured from coral cores collected in July 2013 from the shallow reef at Kahekili in Kaanapali, west Maui, Hawaii from scleractinian Porites lobata.

This data release provides census counts of benthic foraminifera (in percent for the total fauna and as raw counts for just the living specimens) as well as environmental parameters (temperature, salinity, and oxygen concentration) at the sampling sites, and radiocarbon measurements from selected push core samples obtained under and near a whale-fall off western Vancouver Island, British Columbia, Canada.

This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the State Florida (the Florida Peninsula and the Florida Keys). There are 16 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the restoration scenarios (structural_25, structural_05, and ecological_25).

This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the Commonwealth of Puerto Rico. There are 16 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the restoration scenarios (structural_25, structural_05, and ecological_25).

This part of the data release presents projected flooding extent polygon (flood masks) shapefiles based on wave-driven total water levels for the Territory of the U.S. Virgin Islands. There are 16 associated flood mask and flood depth shapefiles: one for each of four nearshore wave energy return periods (rp; 10-, 50-, 100-, and 500-years), the current scenario (base) and each of the restoration scenarios (structural_25, structural_05, and ecological_25).

This dataset consists of short-term (~31 years) shoreline change rates for the north coast of Alaska between the Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2010. A reference baseline was used as the ...

Geochemical analysis of carbonate rock samples collected from seep fields on the RB1903 and AT41 research expeditions in the U.S. Mid- and South Atlantic. Samples were collected as a fingerprint to past hydrocarbon seep activity, fluid source, and depositional environment.

Geochemical and mineralogic analysis of selected carbonate rock samples collected from seep fields on the RB1903 and AT41 research expeditions in the U.S. Mid- and South Atlantic.Samples were collected as a fingerprint to past hydrocarbon seep activity, fluid source, and depositional environment. Analyses include: Wavelength-dispersive X-ray Fluorescence (WDXRF) major element, Inductively Coupled Optical Emission Spectroscopy/Mass Spectroscopy (ICPOES-MS) major and minor element, and x-ray diffractrometry ...

Results are presented from Accelerator Mass Spectrometry (AMS) carbon-14 radiocarbon dating of carbonate rock samples collected from seep fields offshore the U.S. Mid- and South Atlantic in 2018 and 2019. Samples were collected as a fingerprint to past hydrocarbon seep activity, fluid source, and depositional environment.

This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Burien, Washington, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these ...

This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Seattle, California, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these ...

Results of radiocarbon age dating of planktic foraminifera, benthic foraminifera, and pelecypod shell fragments collected from piston cores, trigger weight cores, and IKU grab samples obtained in 2015 and 2017 offshore British Columbia, Canada and southeastern Alaska, U.S. along the Queen Charlotte-Fairweather fault zone.

This part of USGS Data Series 935 (Cochrane, 2014) presents substrate, geomorphic, and biotope data in the Offshore of Tacoma, Washington, map area, a part of the Southern Salish Sea Habitat Map Series. Given the variable bathymetric resolution, the complex geologic history of the region, and the lack of acoustic backscatter data, automated and semi-automated classification schemes of classifying seafloor substrate and geoform were deemed to have very low accuracy. Instead, classification of these ...

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, ...

Eelgrass (Zostera marina) characteristics, sediment grain size distributions, sediment total organic carbon contents (TOC), carbon isotope ratios of sediment organic matter, and total carbon to total nitrogen ratios were measured at four lower intertidal sites in Bellingham Bay, Washington, July 2-5, 2019.

This data release provides census counts of diatoms in sediments of a core obtained off San Francisquito Creek in South San Francisco Bay.

This data release provides census counts of benthic foraminifera in sediments of a core obtained off San Francisquito Creek in South San Francisco Bay.

This data release provides the measurement of anthropogenic metals and other elements in sediments of a core obtained off San Francisquito Creek in South San Francisco Bay.

This data release provides census counts of palynomorphs in sediments of a core obtained off San Francisquito Creek in South San Francisco Bay.

Results of radiocarbon age dating of planktic and benthic foraminifera collected from cores obtained in 1999, 2006, and 2019 offshore central California in the vicinity of Morro Bay.

This part of USGS Data Series 781 presents substrate, geomorphic, and geologic attributed polygons in the Offshore of the Eel River, California, map area, one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data ...

This shapefile has substrate, geomorphic, and geologic attributed polygons in the Offshore of Cape Mendocino, California, map area, one of 83 map areas of the California State Waters Map Series, USGS Data Series 781 (Golden, 2019). The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal ...

This substrate, geomorphic, and geologic attributed polygon shapefile in the Offshore of Eureka, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). The map area is one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification ...

This part of USGS Data Series 781 presents substrate, geomorphic, and geologic attributed polygons in the Offshore of Morro Bay, California, map area, one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data ...

This shapefile has substrate, geomorphic, and geologic attributed polygons in the Offshore of Point Buchon, California, map area, one of 83 map areas of the California State Waters Map Series, USGS Data Series 781 (Golden and Cochrane, 2019). The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification Standard (CMECS; ...

This substrate, geomorphic, and geologic attributed polygon shapefile in the Offshore of Eureka, California, map area is part of USGS Data Series 781 (Golden and Cochrane, 2019). The map area is one of 83 map areas of the California State Waters Map Series. The polygons are derived from multibeam echosounder (MBES) data and derivatives of that data using video-supervised and unsupervised classification. Attributes and attribute values are named following the Coastal and Marine Ecological Classification ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...

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, ...