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.

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.

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.

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.

This metadata record describes the .15 cm pixel resolution digital orthoimagery produced for the Arkansas GIS Office by the Sanborn Map Company. The orthoimagery provided is 4-band (R, G, B, NIR), 8-bit per pixel and delivered in section tiles in uncompressed TIFF/TFW, compressed SID/SDW (40:1) and compressed county wide SID mosaics (40:1) formats. The data was collected on February 25, 26, 2017 and March 1, 2, 3, 8, 2017 at an altitude range between 9505 and 9893 feet using an UltraCam Eagle camera and complies with the NSSDA standards, large scale maps at 1" = 50'. This orthoimagery is published in Universal Transverse Mercator Zone 15N, NAD 83, meters.

This data set contains imagery from the National Agricultural Imagery Program (NAIP). NAIP acquires digital ortho imagery during the agricultural growing seasons in the continental U.S.. A primary goal of the NAIP program is to enable availabilty of ortho imagery within a year of acquisition. NAIP provides two main products: 1 meter ground sample distance (GSD) ortho imagery rectified to a horizontal accuracy of within +/- 3 meters of reference digital ortho quarter quads (DOQQS) from the National Digital Ortho Program (NDOP); and, 2 meter GSD ortho imagery rectified to within +/- 20 meters of reference DOQQs. The tiling format of NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 360 meter buffer on all four sides. NAIP quarter quads are rectified to the UTM coordinate system NAD83. NAIP imagery can obtain as much as 10% cloud cover per tile. This file was generated by compressing mosaicked digital quarter quadrangle image tiles scanned from natural color positive or color infrared positive aerial film into a single mosaic. The mosaic may cover all or portions of an individual county. MrSid software compression, with mosaic option, was used to create the final product. Each individual image tile within the mosaic covers a 3.75 X 3.75 minute quarter quadrangle plus a 360 meter buffer on all four sides. All individual tile images and the resulting mosaic were rectified to the UTM coordinate system, NAD 83 and cast into a single predetermined UTM zone. All digital products and the underlying film images were produced through the National Agriculture Imagery Program (NAIP). The primary purpose of the mosaicked digital ortho quarter quads is to support USDA Field Service Centers located in counties throughout the United States.