This data release includes two dense point clouds produced from uncrewed aerial system (UAS) imagery surveys conducted on August 14, 2019, and July 8, 2022 at an edge-of-field site north of Medina River Natural Area near San Antonio, Texas. The dense point cloud for the August 14, 2019, survey contains 166,261,373 points, and the dense point cloud for the July 8, 2022 survey contains 164,395,847 points. Points within the dense point cloud have not been classified.

This data release includes aerial imagery collected during two uncrewed aerial system (UAS) imagery surveys at an edge-of-field site north of Medina River Natural Area near San Antonio, Texas, on August 14, 2019, and July 8, 2022. A total of 1,153 images were collected during the survey on August 14, 2019, and a total of 1,277 images were collected during the survey on July 8, 2022. In total, 2,430 images provided in the form of geotagged true-color aerial images in JPG format are provided.

This data release includes aerial imagery collected during two uncrewed aerial system (UAS) imagery surveys at an edge-of-field site north of Medina River Natural Area near San Antonio, Texas, on August 14, 2019, and July 8, 2022. A total of 1,153 images were collected during the survey on August 14, 2019, and a total of 1,277 images were collected during the survey on July 8, 2022. In total, 2,430 images provided in the form of geotagged true-color aerial images in JPG format are provided.

Uncrewed aerial system (UAS) flights were conducted by the U.S. Geological Survey at an edge-of-field site located north of Medina River Natural Area near San Antonio, Texas on August 14, 2019, and July 8, 2022, to support efforts aimed at estimating edge-of-field erosion and potential sediment loading into the Medina River near San Antonio. Data provided here include imagery obtained during the flights, and ground control point (GCP) information. Additional products including automatically generated point clouds, digital surface models (DSMs), and orthomosaic imagery produced using structure-from-motion (SfM) techniques are part of this data release.

Uncrewed aerial system (UAS) flights were conducted by the U.S. Geological Survey at an edge-of-field site located north of Medina River Natural Area near San Antonio, Texas on August 14, 2019, and July 8, 2022, to support efforts aimed at estimating edge-of-field erosion and potential sediment loading into the Medina River near San Antonio. Data provided here include imagery obtained during the flights, and ground control point (GCP) information. Additional products including automatically generated point clouds, digital surface models (DSMs), and orthomosaic imagery produced using structure-from-motion (SfM) techniques are part of this data release.

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.

These point clouds were derived from low-altitude (approximately 92-m above ground surface) images collected from unmannned aerial system (UAS) flights over an edge-of-field, paired sampling site that is part of U.S. Geological Survey (USGS) Great Lakes Restoration Initiative (GLRI) monitoring. The objective of this UAS photogrammetry data collection was to provide information on the tile-drain network in each of the two fields with the goal of understanding already observed patterns in runoff amount and water quality from these sites. A 3DR Solo quadcopter served as the flight vehicle, controlled in pre-planned missions using Mission Planner. UAS and the multispectral camera (MicaSense RedEdge) both recorded geospatial information in WGS84; the point clouds are also in WGS84 although final images are in NAD83 UTM Zone 16N. This multispectral camera provides independent images for five wavelength ranges: blue (B; approximately 475-500 nanometers [nm]), green (G; 550-560 nm), red (R: 660-670 nm), red-edge (710-720 nm), and near infrared (NR; 820-860 nm), that are co-located and processed together (MicaSense, 2015); images are provided as R-G-B and as NR-B-G. Thermal-infrared (ThIR) data were collected using a FLIR Vue Pro R 640 thermal camera with an uncooled vanadium oxide microbolometer and a 13-mm lens. Multispectral images were collected at 2-second intervals, with a flight speed of 7 meters per second (m/s) and 75% overlap; these images were georeferenced. Thermal images were collected with a flight speed of 5 m/s and 65% overlap (55% sidelap) and geo-referenced after collection by integrating the flight logs and photo timestamps using GeoSetter (3.4 BETA). Ground control was evaluated using the location of two surface flumes in addition to "ground rulers" that were visible in multispectral images; absolute error ranged from 5.36 to 12.92 m among the four photo-sets, with relative error of -0.06 to 0.06 m for the ground rulers. USGS monitoring sites include Bull Rapids Road near Harlan, IN (USGS Site IDs 411229084541101, 411229084541102, 411228084541701, 411228084541702, and 411228084541703). Citation: MicaSense, Inc. (2015). MicaSense RedEdge. MicaSense, Inc. Seattle, WA, micasense.com.

These point clouds were derived from low-altitude (approximately 92-m above ground surface) images collected from unmannned aerial system (UAS) flights over an edge-of-field, paired sampling site that is part of U.S. Geological Survey (USGS) Great Lakes Restoration Initiative (GLRI) monitoring. The objective of this UAS photogrammetry data collection was to provide information on the tile-drain network in each of the two fields with the goal of understanding already observed patterns in runoff amount and water quality from these sites. A 3DR Solo quadcopter served as the flight vehicle, controlled in pre-planned missions using Mission Planner. UAS and the multispectral camera (MicaSense RedEdge) both recorded geospatial information in WGS84; the point clouds are also in WGS84 although final images are in NAD83 UTM Zone 16N. This multispectral camera provides independent images for five wavelength ranges: blue (B; approximately 475-500 nanometers [nm]), green (G; 550-560 nm), red (R: 660-670 nm), red-edge (710-720 nm), and near infrared (NR; 820-860 nm), that are co-located and processed together (MicaSense, 2015); images are provided as R-G-B and as NR-B-G. Thermal-infrared (ThIR) data were collected using a FLIR Vue Pro R 640 thermal camera with an uncooled vanadium oxide microbolometer and a 13-mm lens. Multispectral images were collected at 2-second intervals, with a flight speed of 7 meters per second (m/s) and 75% overlap; these images were georeferenced. Thermal images were collected with a flight speed of 5 m/s and 65% overlap (55% sidelap) and geo-referenced after collection by integrating the flight logs and photo timestamps using GeoSetter (3.4 BETA). Ground control was evaluated using the location of two surface flumes in addition to "ground rulers" that were visible in multispectral images; absolute error ranged from 5.36 to 12.92 m among the four photo-sets, with relative error of -0.06 to 0.06 m for the ground rulers. USGS monitoring sites include Bull Rapids Road near Harlan, IN (USGS Site IDs 411229084541101, 411229084541102, 411228084541701, 411228084541702, and 411228084541703). Citation: MicaSense, Inc. (2015). MicaSense RedEdge. MicaSense, Inc. Seattle, WA, micasense.com.

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.