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 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.

This portion of the data release presents high-resolution Digital Surface Models (DSM) of the Jenkinson Lake upper reservoir delta in El Dorado County, California. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected during surveys with unoccupied aerial systems (UAS). The surveys were on 2021-10-13, 2021-11-04, 2022-10-25, and 2023-11-13, and were generally timed to coincide with low water level in the reservoir to maximize sub-aerial coverage. The raw imagery used to create the orthomosaics was acquired with a UAS quadcopter 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, from 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. 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) processing to create topographic point clouds, high-resolution orthomosaic images, and DSMs. The DSMs are provided in a cloud optimized GeoTIFF format with internal overviews and masks to facilitate cloud-based queries and display.

This portion of the data release presents high-resolution Digital Surface Models (DSM) of the Jenkinson Lake upper reservoir delta in El Dorado County, California. The DSMs have resolutions of 10 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected during surveys with unoccupied aerial systems (UAS). The surveys were on 2021-10-13, 2021-11-04, 2022-10-25, and 2023-11-13, and were generally timed to coincide with low water level in the reservoir to maximize sub-aerial coverage. The raw imagery used to create the orthomosaics was acquired with a UAS quadcopter 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, from 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. 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) processing to create topographic point clouds, high-resolution orthomosaic images, and DSMs. The DSMs are provided in a cloud optimized GeoTIFF format with internal overviews and masks 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 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.

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.

These datasets consist of four, 1-meter spatial resolution digital surface models (DSMs) that were generated to orthorectify airborne multispectral imagery acquired in 2002, 2009, 2013, and 2021 for the Colorado River in Grand Canyon in Arizona, USA. These datasets also consist of a 1-meter spatial resolution digital elevation model (DEM) that was generated from the 2021 DSM. The DSMs and DEM were also produced to support development of additional GIS products. Elevation values are expressed as ellipsoid heights. These datasets also include accuracy assessments that were performed to show the limitations of estimating elevation from the DSMs and DEM pixels locations on the landscape. Data were acquired during periods of low steady Colorado River flow of approximately 8,000 cubic feet per second released from Glen Canyon Dam.

These datasets consist of four, 1-meter spatial resolution digital surface models (DSMs) that were generated to orthorectify airborne multispectral imagery acquired in 2002, 2009, 2013, and 2021 for the Colorado River in Grand Canyon in Arizona, USA. These datasets also consist of a 1-meter spatial resolution digital elevation model (DEM) that was generated from the 2021 DSM. The DSMs and DEM were also produced to support development of additional GIS products. Elevation values are expressed as ellipsoid heights. These datasets also include accuracy assessments that were performed to show the limitations of estimating elevation from the DSMs and DEM pixels locations on the landscape. Data were acquired during periods of low steady Colorado River flow of approximately 8,000 cubic feet per second released from Glen Canyon Dam.

Data included in this release are two digital surface models (DSMs) obtained by using uncrewed aerial system (UAS) surveys conducted on August 14, 2019, and July 8, 2022, at an edge-of-field site north of the Medina River Natural Area near San Antonio, Texas.

Data included in this release are two digital surface models (DSMs) obtained by using uncrewed aerial system (UAS) surveys conducted on August 14, 2019, and July 8, 2022, at an edge-of-field site north of the Medina River Natural Area near San Antonio, Texas.