데이터셋 상세
미국
USGS High Resolution Orthoimagery
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.
데이터 정보
연관 데이터
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.