USGS Lidar Point Cloud IL Pike-ScottCo 2015 20801092 LAS 2017
Dates
Publication Date
2017-10-16
Start Date
2015-11-22
End Date
2015-12-03
File Modification Date
2020-11-28 05:45:04
Citation
U.S. Geological Survey, 20171016, USGS Lidar Point Cloud IL Pike-ScottCo 2015 20801092 LAS 2017: U.S. Geological Survey.
Summary
Lidar (Light detection and ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format. The LAS format is a standardized binary format for storing 3-dimensional point cloud data and point attributes along with header information and variable length records specific to the data. Millions of data points are stored as a 3-dimensional data cloud as a series of x (longitude), y (latitude) and z (elevation) points. A few older projects in this collection are in ASCII format. Please refer to http://www.asprs.org/Committee-General/LASer-LAS-File-Format-Exchange-Activities.html for additional information.
Summary
Lidar (Light detection and ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format. The LAS format is a standardized binary format for storing 3-dimensional point cloud data and point attributes along with header information and variable length records specific to the data. Millions of data points are stored as a 3-dimensional data cloud as a series of x (longitude), y (latitude) and z (elevation) points. A few older projects in this collection are in ASCII format. Please refer to http://www.asprs.org/Committee-General/LASer-LAS-File-Format-Exchange-Activities.html for additional information.
High-resolution digital elevation maps generated by airborne and stationary LiDAR have led to significant advances in geomorphology, the branch of geoscience concerned with the origin and evolution of Earth's surface topography. LiDAR provides unique characteristics relative to other remotely sensed data sources by providing three-dimensional feature information that cannot be derived from traditional imaging sensors.
