The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial products of the South Cow Mountain Recreational Area, Lake County, California, using historic aerial imagery and structure-from-motion (SfM) photogrammetry methods. Products were generated from stereo historical aerial imagery acquired by the BLM in May of 1977. The aerial imagery were downloaded from the USGS Earth Resources Observation and Science (EROS) Data Center's USGS Single Aerial Frame Photo archive and a was created using USGS guidelines. Data were processed using SfM photogrammetry to generate a three-dimensional point cloud (.laz) that identifies pixels of an object from multiple images taken from various angles and calculates the x, y, and z coordinates of that object/pixel. The point cloud was processed to create a DSM (.tif) representing the continuous surface of the uppermost reflective surface (57.3 cm resolution). Finally, source images were stitched together based on shared pixels and orthogonally adjusted to the DSM to create a high resolution (approximately 18.3 cm) orthoimage (.tif) for the study area. This dataset includes a point cloud, digital surface model (DSM), and orthoimagery, as well as synthetic ground-control points (GCPs) and point clusters used to georeference the datasets. Separate metadata for each product are provided on the ScienceBase page for each child item.

The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial products using historic aerial imagery and Structure from Motion (SfM) photogrammetry methods. A point cloud dataset (.laz) of the South Cow Mountain Recreational Area was generated from stereo historical aerial imagery acquired in by the BLM in 1977. The aerial imagery was downloaded from the USGS Earth Resources Observation and Science (EROS) Data Center's USGS Single Aerial Frame Photo archive and the point cloud was created using USGS guidelines. Photo alignment, error reduction, and dense point cloud generation followed guidelines documented in Over, J.R., Ritchie, A.C., Kranenburg, C.J., Brown, J.A., Buscombe, D., Noble, T., Sherwood, C.R., Warrick, J.A., and Wernette, P.A., 2021, Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6— Structure from motion workflow documentation: U.S. Geological Survey Open-File Report 2021–1039, 46 p., https://doi.org/10.3133/ofr20211039. Photo-identifiable points, selected as synthetic ground-control points, followed guidelines documented in Sherwood, C.R.; Warrick, J.A.; Hill, A.D.; Ritchie, A.C.; Andrews, B.D., and Plant, N.G., 2018. Rapid, remote assessment of Hurricane Matthew impacts using four-dimensional structure-from-motion photogrammetry https://doi.org/10.2112/JCOASTRES-D-18-00016.1 Additional post-processing of the 1977 dense point cloud, using Iterative Closest Point (ICP) analysis, was used to improve the alignment with the 2015 LiDAR point cloud. The ICP analysis is explained in Low, K.L., 2004. Linear least-squares optimization for point-to-plane ICP surface registration. Chapel Hill, University of North Carolina, 4(10), pp.1-3. http://www.comp.nus.edu.sg/~lowkl/publications/lowk_point-to-plane_icp_techrep.pdf Data were processed using photogrammetry to generate a three-dimensional point cloud that identifies pixels of an object from multiple images taken from various angles and calculates the x, y, and z coordinates of that object/pixel. The point cloud was processed to create a digital surface model of the study area (57.3 cm resolution). Finally, source images were stitched together based on shared pixels and orthogonally adjusted to the digital surface model to create a high resolution (approximately 18.3 cm) orthoimage for the study area.

The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial products using historic aerial imagery and Structure from Motion (SfM) photogrammetry methods. A high-resolution orthomosaic of the South Cow Mountain Recreational Area was generated from stereo historical aerial imagery acquired in by the BLM in May of1977. The aerial imagery were downloaded from the USGS Earth Resources Observation and Science (EROS) Data Center's USGS Single Aerial Frame Photo archive and an orthomosaic was created using USGS guidelines. Photo alignment, error reduction, and dense point cloud generation followed guidelines documented in Over, J.R., Ritchie, A.C., Kranenburg, C.J., Brown, J.A., Buscombe, D., Noble, T., Sherwood, C.R., Warrick, J.A., and Wernette, P.A., 2021, Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6— Structure from motion workflow documentation: U.S. Geological Survey Open-File Report 2021–1039, 46 p., https://doi.org/10.3133/ofr20211039. Photo-identifiable points, selected as synthetic ground-control points, followed guidelines documented in Sherwood, C.R.; Warrick, J.A.; Hill, A.D.; Ritchie, A.C.; Andrews, B.D., and Plant, N.G., 2018. Rapid, remote assessment of Hurricane Matthew impacts using four-dimensional structure-from-motion photogrammetry https://doi.org/10.2112/JCOASTRES-D-18-00016.1 Additional post-processing of the 1977 dense point cloud, using Iterative Closest Point (ICP) analysis, was used to improve the alignment with the 2015 LiDAR point cloud. The ICP analysis is explained in Low, K.L., 2004. Linear least-squares optimization for point-to-plane ICP surface registration. Chapel Hill, University of North Carolina, 4(10), pp.1-3. http://www.comp.nus.edu.sg/~lowkl/publications/lowk_point-to-plane_icp_techrep.pdf Data were processed using photogrammetry to generate a three-dimensional point cloud that identifies pixels of an object from multiple images taken from various angles and calculates the x, y, and z coordinates of that object/pixel. The point cloud was processed to create a digital surface model of the study area (57.3 cm resolution). Finally, source images were stitched together based on shared pixels and orthogonally adjusted to the digital surface model to create a high resolution (approximately 18.3 cm) orthoimage for the study area.

The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial products using historic aerial imagery and Structure from Motion (SfM) photogrammetry methods. A high-resolution orthomosaic of the South Cow Mountain Recreational Area was generated from stereo historical aerial imagery acquired in by the BLM in May of 1977. The aerial imagery were downloaded from the USGS Earth Resources Observation and Science (EROS) Data Center's USGS Single Aerial Frame Photo archive and an orthomosaic was created using USGS guidelines. Photo alignment, error reduction, and dense point cloud generation followed guidelines documented in Over, J.R., Ritchie, A.C., Kranenburg, C.J., Brown, J.A., Buscombe, D., Noble, T., Sherwood, C.R., Warrick, J.A., and Wernette, P.A., 2021, Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6— Structure from motion workflow documentation: U.S. Geological Survey Open-File Report 2021–1039, 46 p., https://doi.org/10.3133/ofr20211039. Photo-identifiable points, selected as synthetic ground-control points, followed guidelines documented in Sherwood, C.R.; Warrick, J.A.; Hill, A.D.; Ritchie, A.C.; Andrews, B.D., and Plant, N.G., 2018. Rapid, remote assessment of Hurricane Matthew impacts using four-dimensional structure-from-motion photogrammetry https://doi.org/10.2112/JCOASTRES-D-18-00016.1 Additional post-processing of the 1977 dense point cloud, using Iterative Closest Point (ICP) analysis, was used to improve the alignment with the 2015 LiDAR point cloud. The ICP analysis is explained in Low, K.L., 2004. Linear least-squares optimization for point-to-plane ICP surface registration. Chapel Hill, University of North Carolina, 4(10), pp.1-3. http://www.comp.nus.edu.sg/~lowkl/publications/lowk_point-to-plane_icp_techrep.pdf Data were processed using photogrammetry to generate a three-dimensional point cloud that identifies pixels of an object from multiple images taken from various angles and calculates the x, y, and z coordinates of that object/pixel. The point cloud was processed to create a digital surface model of the study area (57.3 cm resolution). Finally, source images were stitched together based on shared pixels and orthogonally adjusted to the digital surface model to create a high resolution (approximately 18.3 cm) orthoimage for the study area.

In cooperation with the U.S. Army Corps of Engineers (USACE), the U.S. Geological Survey (USGS) surveyed ground control points and coordinated aerial photograph acquisition of Hills Creek Lake, a multi-purpose reservoir in western Oregon impounded by the 92-meter ([m]; 302-foot [ft]) tall Hills Creek Dam. Aerial photographs were acquired by the Civil Air Patrol (CAP) on December 20, 2023 and December 28, 2023 when water levels were at 443 and 441 m (1453 ft and 1448 ft; National Geodetic Vertical Datum of 1929 [NGVD 29]) elevation, respectively, about 10 m above typical annual “low pool” or minimum pool for flood risk management operations. Photographs were acquired at about the same altitude with a WaldoAir XCAM Ultra 50 camera mounted on a Cessna aircraft and captured the entire reservoir area as defined by full pool (or maximum conservation pool elevation), including major tributaries entering the reservoir such as the Middle Fork Willamette River and Hills Creek, upstream of Hills Creek Dam. Dam operations at the 1,107-hectare (2735-acre) Hills Creek Lake, located about 19 kilometers upstream of the confluence of the Middle Fork Willamette River and the head of Lookout Point Lake, along with other hydrogeomorphic conditions, result in a diverse array of geomorphic processes and landforms within the reservoir. To document reservoir floor geomorphology, the USGS applied structure-from-motion (SfM) techniques to these aerial photographs, following the workflow outlined in Over and others (2021), and generated three-dimensional xyz point clouds, digital surface models (DSMs), and orthomosaics of Hills Creek Lake. This data release includes ground control points, dataset footprints, original aerial photographs, point clouds, DSMs, and orthomosaics of Hills Creek Lake with varying aerial extents and resolutions that were developed from imagery acquired December of 2023: (1) the December 20 model (HillsCreekLake_20231220) covered the entire reservoir area with an average point density of 27.6 points per square meter, DSM resolution of 19 centimeters per pixel, and orthomosaic ground resolution of 9.52 centimeters per pixel; (2) the December 28 model (HillsCreekLake_20231228) covered the entire reservoir area, excluding a portion of the Larison Creek arm, with an average point density of 29.8 points per square meter, DSM resolution of 18.3 centimeters per pixel, and orthomosaic ground resolution of 9.15 centimeters per pixel. All DSMs and orthomosaics are formatted as Cloud Optimized GeoTIFFs (COGs) for enhanced web visualization (GDAL, 2024). This documentation describes a high-resolution point cloud (LAZ file) of Hills Creek Lake, Oregon, generated from SfM techniques using aerial photographs acquired on December 28, 2023. References: Agisoft, 2025, Agisoft Metashape User Manual - Professional Edition Version 2.2: Agisoft LLC, 115 p., accessed August 11, 2025, at https://www.agisoft.com/pdf/metashape_2_2_en.pdf. American Society for Photogrammetry and Remote Sensing [ASPRS], 2008, LAS Specification Version 1.2: ASPRS, approved September 2, 2008, 13 p., accessed August 11, 2025, at https://www.asprs.org/wp-content/uploads/2010/12/asprs_las_format_v12.pdf. Geospatial Data Abstraction Library [GDAL], 2024, COG -- Cloud Optimized GeoTIFF generator: GDAL, webpage, accessed August 11, 2025, at https://gdal.org/drivers/raster/cog.html#raster-cog. Over, J.R., Ritchie, A.C., Kranenburg, C.J., Brown, J.A., Buscombe, D., Noble, T., Sherwood, C.R., Warrick, J.A., and Wernette, P.A., 2021, Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6—Structure from motion workflow documentation: U.S. Geological Survey Open-File Report 2021–1039, 46 p., https://doi.org/10.3133/ofr20211039. Schwid, M.F., Keith, M.K., and Overstreet, B.T., 2025, High-resolution orthoimagery and digital surface models of Fern Ridge Lake, Oregon, during annual low pool, January and February, 2023: U.S. Geological Survey data release,

In cooperation with the U.S. Army Corps of Engineers (USACE), the U.S. Geological Survey (USGS) surveyed ground control points and coordinated aerial photograph acquisition of Hills Creek Lake, a multi-purpose reservoir in western Oregon impounded by the 92-meter ([m]; 302-foot [ft]) tall Hills Creek Dam. Aerial photographs were acquired by the Civil Air Patrol (CAP) on December 20, 2023 and December 28, 2023 when water levels were at 443 and 441 m (1453 ft and 1448 ft; National Geodetic Vertical Datum of 1929 [NGVD 29]) elevation, respectively, about 10 m above typical annual “low pool” or minimum pool for flood risk management operations. Photographs were acquired at about the same altitude with a WaldoAir XCAM Ultra 50 camera mounted on a Cessna aircraft and captured the entire reservoir area as defined by full pool (or maximum conservation pool elevation), including major tributaries entering the reservoir such as the Middle Fork Willamette River and Hills Creek, upstream of Hills Creek Dam. Dam operations at the 1,107-hectare (2735-acre) Hills Creek Lake, located about 19 kilometers upstream of the confluence of the Middle Fork Willamette River and the head of Lookout Point Lake, along with other hydrogeomorphic conditions, result in a diverse array of geomorphic processes and landforms within the reservoir. To document reservoir floor geomorphology, the USGS applied structure-from-motion (SfM) techniques to these aerial photographs, following the workflow outlined in Over and others (2021), and generated three-dimensional xyz point clouds, digital surface models (DSMs), and orthomosaics of Hills Creek Lake. This data release includes ground control points, dataset footprints, original aerial photographs, point clouds, DSMs, and orthomosaics of Hills Creek Lake with varying aerial extents and resolutions that were developed from imagery acquired December of 2023: (1) the December 20 model (HillsCreekLake_20231220) covered the entire reservoir area with an average point density of 27.6 points per square meter, DSM resolution of 19 centimeters per pixel, and orthomosaic ground resolution of 9.52 centimeters per pixel; (2) the December 28 model (HillsCreekLake_20231228) covered the entire reservoir area, excluding a portion of the Larison Creek arm, with an average point density of 29.8 points per square meter, DSM resolution of 18.3 centimeters per pixel, and orthomosaic ground resolution of 9.15 centimeters per pixel. All DSMs and orthomosaics are formatted as Cloud Optimized GeoTIFFs (COGs) for enhanced web visualization (GDAL, 2024). This documentation describes a high-resolution point cloud (LAZ file) of Hills Creek Lake, Oregon, generated from SfM techniques using aerial photographs acquired on December 20, 2023. References: Agisoft, 2025, Agisoft Metashape User Manual - Professional Edition Version 2.2: Agisoft LLC, 115 p., accessed August 11, 2025, at https://www.agisoft.com/pdf/metashape_2_2_en.pdf. American Society for Photogrammetry and Remote Sensing [ASPRS], 2008, LAS Specification Version 1.2: ASPRS, approved September 2, 2008, 13 p., accessed August 11, 2025, at https://www.asprs.org/wp-content/uploads/2010/12/asprs_las_format_v12.pdf. Geospatial Data Abstraction Library [GDAL], 2024, COG -- Cloud Optimized GeoTIFF generator: GDAL, webpage, accessed August 11, 2025, at https://gdal.org/drivers/raster/cog.html#raster-cog. Over, J.R., Ritchie, A.C., Kranenburg, C.J., Brown, J.A., Buscombe, D., Noble, T., Sherwood, C.R., Warrick, J.A., and Wernette, P.A., 2021, Processing coastal imagery with Agisoft Metashape Professional Edition, version 1.6—Structure from motion workflow documentation: U.S. Geological Survey Open-File Report 2021–1039, 46 p., https://doi.org/10.3133/ofr20211039. Schwid, M.F., Keith, M.K., and Overstreet, B.T., 2025, High-resolution orthoimagery and digital surface models of Fern Ridge Lake, Oregon, during annual low pool, January and February, 2023: U.S. Geological Survey data release,

This portion of the data release presents a topographic point cloud of the exposed Los Padres Reservoir delta where the Carmel River enters the reservoir. The point cloud was derived from structure-from-motion (SfM) processing of aerial imagery collected with an unoccupied aerial system (UAS) on 2017-11-01. The point cloud has 115,819,907 points with an average point density of 611 points per-square meter. Each point in the point cloud contains an explicit horizontal and vertical coordinate, color, intensity, and classification. Classification was performed on the point cloud to identify ground and low-noise points within the point cloud. Additional portions of the point cloud within the horizontal extent of the reservoir water surface were classified as water points (class 9) using a polygon digitized from the orthomosaic imagery also derived from this survey. Water areas on the exposed delta surface including ponded water and areas covered by the Carmel River were not classified as water. The raw imagery used to create these point clouds was acquired using a UAS fitted with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed autonomous flight lines spaced to provide approximately 70 percent overlap between images from adjacent lines. The camera was triggered at 1 Hz using a built-in intervalometer. The UAS was flown at an approximate altitude of 100 meters above ground level (AGL), resulting in a nominal ground-sample-distance (GSD) of 2.6 centimeters per pixel. The raw imagery was geotagged using positions from the UAS onboard single-frequency autonomous GPS. Twenty temporary ground control points (GCPs) consisting of small square tarps with black-and-white cross patterns were distributed throughout the area to establish survey control. The GCP positions were measured using real-time kinematic (RTK) GPS, using corrections from a GPS base station located on a benchmark designated SFML, located approximately 1 kilometer from the study area. The point cloud is formatted in LAZ format (LAS 1.2 specification).

This portion of the data release presents a digital surface model (DSM) and digital elevation model (DEM) of the exposed Los Padres Reservoir delta where the Carmel River enters the reservoir. The DSM and DEM have a resolution of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected with an unoccupied aerial system (UAS) on 2017-11-01. The DSM represents the elevation of the highest object within the bounds of a cell, including vegetation, woody debris and other objects. The DEM represent the elevation of the ground surface where it was visible to the acquisiton system. Due to the nature of SfM processing, the DEM may not represent a true bare-earth surface in areas of thick vegetation cover; in these areas some DEM elevations may instead represent thick vegetation canopy. The raw imagery used to create these elevation models was acquired with a UAS fitted with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed autonomous flight lines spaced to provide approximately 70 percent overlap between images from adjacent lines. The camera was triggered at 1 Hz using a built-in intervalometer. The UAS was flown at an approximate altitude of 100 meters above ground level (AGL), resulting in a nominal ground-sample-distance (GSD) of 2.6 centimeters per pixel. The raw imagery was geotagged using positions from the UAS onboard single-frequency autonomous GPS. Twenty temporary ground control points (GCPs) consisting of small square tarps with black-and-white cross patterns were distributed throughout the area to establish survey control. The GCP positions were measured using real-time kinematic (RTK) GPS, using corrections from a GPS base station located on a benchmark designated SFML, located approximately 1 kilometer from the study area. The DSM and DEM have been formatted as cloud optimized GeoTIFFs with internal overviews and masks to facilitate cloud-based queries and display.

This portion of the data release presents a topographic point cloud of the debris flow at South Fork Campground in Sequoia National Park. The point cloud was derived from structure-from-motion (SfM) photogrammetry using aerial imagery acquired during an uncrewed aerial systems (UAS) survey on 30 April 2024, conducted under authorization from the National Park Service. The raw imagery was acquired with a Ricoh GR II digital camera featuring a global shutter. The UAS was flown on pre-programmed autonomous flight lines spaced to provide approximately 70 percent overlap between images from adjacent lines, from an approximate altitude of 110 meters above ground level (AGL), resulting in a nominal ground-sample-distance (GSD) of 2.9 centimeters per pixel. The imagery was geotagged using positions from the UAS onboard single-frequency autonomous GPS. Survey control was established using temporary ground control points (GCPs) consisting of a combination of small square tarps with black-and-white cross patterns and temporary chalk marks placed on the ground. The GCP positions were measured using dual-frequency real-time kinematic (RTK) GPS with corrections referenced to a static base station operating nearby. The images and GCP positions were used for structure-from-motion (SfM) photogrammetric processing to create a topographic point cloud, a high-resolution orthomosaic image, and a DSM. The point cloud contains 284,906,970 points with an average point-spacing of one point every three centimeters. The point cloud has not been classified, however points with confidence less than three (a measure of the number of depth maps used to generate a point) have been assigned a classification value of 7, which represents low noise. The point cloud is provided in a cloud optimized LAZ format to facilitate cloud-based queries and display.

The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial products of the Scotts Creek Watershed in Lake County, California, using National Agriculture Imagery Program (NAIP) imagery from 2022 and Open Street Map (OSM) from 2019. The imagery was downloaded from United States Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS) Geospatial Data Gateway (https://datagateway.nrcs.usda.gov/) and Geofabrik GmbH - Open Street Map (https://www.geofabrik.de/geofabrik/openstreetmap.html), respectively. An updated trail map for the Upper Scotts Creek Watershed, including the BLM Recreational Area, was created to estimate trail densities in the watershed. A preview image of the roads and trail maps is attached to this data release (see UpperScottsCreek_Roads_and_Trails_Map_2022_USGS2022_CC0.png).