U.S. Geological Survey (USGS) scientists conducted field data collection efforts during the weeks of September 9-13 and November 18-22, 2019, using a combination of technologies to map and validate topography, vegetation, and features in two areas of interest (AOI's) in north central Colorado. The western AOI included land managed by the Bureau of Land Management and the U.S. Forest Service. The eastern AOI included agricultural and urban areas. The work was initiated as an effort to test and evaluate the Leica Geosystems CountryMapper* sensor. The CountryMapper is a hybrid sensor that collects imagery and light detection and ranging (lidar) data simultaneously. The CountryMapper has the potential to collect data that satisfies both USGS National Geospatial Program (NGP) 3D Elevation Program (3DEP) and U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) requirements in a single collection. Real Time Kinematic Global Navigational Satellite System (RTK-GNSS), total station, ground based lidar (GBL), Unmanned Aerial System (UAS) lidar, and UAS imagery data were collected to compare to the data collected by the CountryMapper. * Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

U.S. Geological Survey (USGS) scientists conducted field data collection efforts during the weeks of September 9-13 and November 18-22, 2019, using a combination of technologies to map and validate topography, vegetation, and features in two areas of interest (AOI's) in north central Colorado. The western AOI included land managed by the Bureau of Land Management and the U.S. Forest Service. The eastern AOI included agricultural and urban areas. The work was initiated as an effort to test and evaluate the Leica Geosystems CountryMapper* sensor. The CountryMapper is a hybrid sensor that collects imagery and light detection and ranging (lidar) data simultaneously. The CountryMapper has the potential to collect data that satisfies both USGS National Geospatial Program (NGP) 3D Elevation Program (3DEP) and U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) requirements in a single collection. Real Time Kinematic Global Navigational Satellite System (RTK-GNSS), total station, ground based lidar (GBL), Unmanned Aerial System (UAS) lidar, and UAS imagery data were collected to compare to the data collected by the CountryMapper. * Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

U.S. Geological Survey (USGS) scientists conducted field data collection efforts between August 17th and 28th, 2020 over a large stretch of the Niobrara River in Nebraska using high accuracy surveying technologies. The work was initiated as an effort to validate commercially acquired topobathymetric light detection and ranging (lidar) data. The goal was to compare and validate the airborne lidar data to topographic, bathymetric, structural, and infrastructural data collected through more traditional means (e.g. Global Navigational Satellite System (GNSS) surveying). The airborne topobathymetric lidar data will be used for characterization of endangered species aquatic habitat, improving the understanding of fluvial geomorphic features, sediment transport modeling, and 2D/3D hydrologic and hydraulic modeling. The impacts of the spring 2019 flood and resulting Spencer Dam failure will be further assessed and monitored using the lidar data along with testing inland topobathymetric lidar mapping capabilities for inclusion in the USGS National Geospatial Program (NGP) 3D Elevation Program (3DEP).

U.S. Geological Survey (USGS) scientists conducted field data collection efforts between August 17th and 28th, 2020 over a large stretch of the Niobrara River in Nebraska using high accuracy surveying technologies. The work was initiated as an effort to validate commercially acquired topobathymetric light detection and ranging (lidar) data. The goal was to compare and validate the airborne lidar data to topographic, bathymetric, structural, and infrastructural data collected through more traditional means (e.g. Global Navigational Satellite System (GNSS) surveying). The airborne topobathymetric lidar data will be used for characterization of endangered species aquatic habitat, improving the understanding of fluvial geomorphic features, sediment transport modeling, and 2D/3D hydrologic and hydraulic modeling. The impacts of the spring 2019 flood and resulting Spencer Dam failure will be further assessed and monitored using the lidar data along with testing inland topobathymetric lidar mapping capabilities for inclusion in the USGS National Geospatial Program (NGP) 3D Elevation Program (3DEP).

U.S. Geological Survey (USGS) scientists conducted field data collection efforts during the time periods of April 25 - 26, 2017, October 24 - 28, 2017, and July 25 - 26, 2018, using a combination of surveying technologies to map and validate topography, structures, and other features at five sites in central South Dakota. The five sites included the Chamberlain Explorers Athletic Complex and the Chamberlain High School in Chamberlain, SD, Hanson Lake State Public Shooting Area near Corsica, SD, the State Capital Grounds in Pierre, SD, and Platte Creek State Recreation Area near Platte, SD. The work was initiated as an effort to evaluate airborne Geiger-Mode and Single Photon light detection and ranging (lidar) data that were collected over parts of central South Dakota. Both Single Photon and Geiger-Mode lidar offer the promise of being able to map areas at high altitudes, thus requiring less time than traditional airborne lidar collections, while acquiring higher point densities. Real Time Kinematic Global Navigational Satellite System (RTK-GNSS), total station, and ground-based lidar (GBL) data were collected to evaluate data collected by the Geiger-Mode and Single Photon systems.

U.S. Geological Survey (USGS) scientists conducted field data collection efforts during the time periods of April 25 - 26, 2017, October 24 - 28, 2017, and July 25 - 26, 2018, using a combination of surveying technologies to map and validate topography, structures, and other features at five sites in central South Dakota. The five sites included the Chamberlain Explorers Athletic Complex and the Chamberlain High School in Chamberlain, SD, Hanson Lake State Public Shooting Area near Corsica, SD, the State Capital Grounds in Pierre, SD, and Platte Creek State Recreation Area near Platte, SD. The work was initiated as an effort to evaluate airborne Geiger-Mode and Single Photon light detection and ranging (lidar) data that were collected over parts of central South Dakota. Both Single Photon and Geiger-Mode lidar offer the promise of being able to map areas at high altitudes, thus requiring less time than traditional airborne lidar collections, while acquiring higher point densities. Real Time Kinematic Global Navigational Satellite System (RTK-GNSS), total station, and ground-based lidar (GBL) data were collected to evaluate data collected by the Geiger-Mode and Single Photon systems.

U.S. Geological Survey (USGS) scientists completed a multidisciplinary data collection effort during the week of October 21-25, 2019, using new technologies to map and validate bathymetry over a large stretch of the non-tidal Potomac River. The work was initiated as an effort to validate commercially-acquired topobathymetric light detection and ranging (lidar) data funded through a partnership between the USGS and the Interstate Commission on the Potomac River Basin (ICPRB). The goal was to compare airborne lidar data to bathymetric data collected through more traditional means (boat-based sonar, wading Real Time Kinematic Global Navigational Satellite System (RTK-GNSS) surveys) and through unmanned aerial systems (UAS). In addition to accurately measuring river bottom elevations with GNSS and sonar, remote sensing imagery was collected with optical, multispectral, thermal, and ground-based lidar (GBL) sensors to test new technologies. The bathymetric lidar data, once delivered, will be used for hydrodynamic and water supply risk modeling, aquatic habitat assessments, and to test inland bathymetry mapping capabilities for inclusion in the USGS National Geospatial Program (NGP) 3D Elevation Program (3DEP). The data contained within this particular release are comprised of conventional survey (i.e. total station and GNSS) and GBL data.

U.S. Geological Survey (USGS) scientists completed a multidisciplinary data collection effort during the week of October 21-25, 2019, using new technologies to map and validate bathymetry over a large stretch of the non-tidal Potomac River. The work was initiated as an effort to validate commercially-acquired topobathymetric light detection and ranging (lidar) data funded through a partnership between the USGS and the Interstate Commission on the Potomac River Basin (ICPRB). The goal was to compare airborne lidar data to bathymetric data collected through more traditional means (boat-based sonar, wading Real Time Kinematic Global Navigational Satellite System (RTK-GNSS) surveys) and through unmanned aerial systems (UAS). In addition to accurately measuring river bottom elevations with GNSS and sonar, remote sensing imagery was collected with optical, multispectral, thermal, and ground-based lidar (GBL) sensors to test new technologies. The bathymetric lidar data, once delivered, will be used for hydrodynamic and water supply risk modeling, aquatic habitat assessments, and to test inland bathymetry mapping capabilities for inclusion in the USGS National Geospatial Program (NGP) 3D Elevation Program (3DEP). The data contained within this particular release are comprised of conventional survey (i.e. total station and GNSS) and GBL data.

This dataset provides the complete catalog of point cloud data collected during LiDAR surveys over selected forest research sites across the Amazon rainforest in Brazil between 2008 and 2018 for the Sustainable Landscapes Brazil Project. Flight lines were selected to overfly key field research sites in the Brazilian states of Acre, Amazonas, Bahia, Goias, Mato Grosso, Para, Rondonia, Santa Catarina, and Sao Paulo. The point clouds have been georeferenced, noise-filtered, and corrected for misalignment of overlapping flight lines. They are provided in 1 km2 tiles. The data were collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time.

These are terrestrial laser scanner datasets collected in forested areas west of Flagstaff, Arizona in 2015 and 2016. For each of the two scanners, six treatment areas were scanned, with four of them overlapping one another (Figure 1). These data are composed of individual scans referenced to one another using reflective targets, and geolocated using differentially corrected GPS and RTK locations of scan locations (Figure 3). There were overall large differences in point density among the two scanners (Figure 2).