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Orthoimage derived from historical aerial imagery of the South Cow Mountain Recreational Area, Lake County, California, May 27, 1977
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.
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Orthoimage derived from historical aerial imagery of the South Cow Mountain Recreational Area, Lake County, California, May 27, 1977
공공데이터포털
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.
Point cloud, digital surface model (DSM), and orthoimagery derived from historical aerial imagery of the South Cow Mountain Recreational Area, Lake County, California, May 27, 1977
공공데이터포털
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.
Data release of historical aerial photograph orthomosaics of Lassen Volcanic National Park, California (1941, 1952, 1966, 1973, 1998 and 2004)
공공데이터포털
This data release publishes datasets of historical aerial photograph orthomosaics covering areas within and surrounding Lassen Volcanic National Park, California. The historical imagery provides a high-resolution, spatially contiguous record of the park’s landscape across six dates ranging from 1941-2004. A total of 990 hard-copy aerial photographs taken in 1941, 1952, 1966, 1973, 1998, and 2004 were scanned at 800 dpi with an Epson Expression 12000XL. The 1941-1966 images are in black and white and scanned in 16-bit greyscale, and 1973, 1998 and 2004 are in color and scanned as 24-bit RGB. Like many historical aerial photograph collections, most of the flight and camera parameters were missing; Structure-from-Motion (SfM) software offers an efficient solution for orthorectifying images that lack these parameters. We used a SfM software called Agisoft Metashape Professional (v.1.6) to generate the orthomosaics for each image year, which were aligned with sets of reference Ground Control Points (GCPs). Average Root Mean Square Error (RMSE) ranged from 4.07-140 cm, and average reprojection errors ranged from 0.56-0.78 meters. Each orthomosaic metadata file contains specific information on image processing, number of GCPs used and estimated error.
Orthomosaic map produced for the Upper Colorado Integrated Water Science basin, Colorado River at Windy Gap study site, June 13, 2022
공공데이터포털
A Bell 407 helicopter with a gyro-stabilized gimbal was used to collect aerial videos of Upper Colorado River Water Science Basin (IWS) riverine study sites in 2022. Videos were collected using both natural color and thermal infrared cameras. These videos were used to determine the feasibility of estimating river surface velocity using aerial imagery. Photogrammetry techniques were used with the natural color video images to produce an orthomosaic map of the study reach.
Orthomosaic images from UAS surveys of the upper reservoir delta at Jenkinson Lake, El Dorado County, California
공공데이터포털
This portion of the data release presents high-resolution orthomosaic images of the Jenkinson Lake upper reservoir delta in El Dorado County, California. The orthomosaics have resolutions of 2.5 centimeters per pixel and were derived from structure-from-motion (SfM) processing of aerial imagery collected during surveys with unoccupied aerial systems (UAS). The surveys were on 2021-10-13, 2021-11-04, 2022-10-25, and 2023-11-13, and were generally timed to coincide with low water level in the reservoir to 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 orthomosaic images are provided in a three-band RGB format, with 8-bit unsigned integer values compressed using high-quality JPEG compression, and are formatted as cloud optimized GeoTIFFs with internal overviews and masks to facilitate cloud-based queries and display.
ORTHOIMAGERY, CITY OF SHISHMAREF, ALASKA, USA
공공데이터포털
Digital orthographic imagery datasets contain georeferenced images of the Earth's surface, collected by a sensor in which object displacement has been removed for sensor distortions and orientation, and terrain relief. Digital orthoimages have the geometric characteristics of a map, and image qualities of a photograph.
USGS High Resolution Orthoimagery
공공데이터포털
High resolution orthorectified images combine the image characteristics of an aerial photograph with the geometric qualities of a map. An orthoimage is a uniform-scale image where corrections have been made for feature displacement such as building tilt and for scale variations caused by terrain relief, sensor geometry, and camera tilt. A mathematical equation based on ground control points, sensor calibration information, and a digital elevation model is applied to each pixel to rectify the image to obtain the geometric qualities of a map. A digital orthoimage may be created from several photographs mosaicked to form the final image. The source imagery may be black-and-white, natural color, or color infrared with a pixel resolution of 1-meter or finer. With orthoimagery, the resolution refers to the distance on the ground represented by each pixel.
Orthomosaic imagery from the UAS survey of the debris flow at South Fork Campground, Sequoia National Park, CA
공공데이터포털
This portion of the data release presents a high-resolution orthomosaic image of the debris flow at South Fork Campground in Sequoia National Park. The orthomosaic has a resolution of 3 centimeters per pixel and 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 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) photogrammetric processing to create a topographic point cloud, a high-resolution orthomosaic image, and a Digital Surface Model (DSM). The orthomosaic image is provided in a cloud optimized GeoTIFF format with internal overviews and masks to facilitate cloud-based queries and display.