Taken together, lakes and drained lake basins may cover up to 80% of the lowland landscapes in permafrost regions of the Arctic. Lake formation, growth, and drainage in lowland permafrost regions create a terrestrial and aquatic landscape mosaic of importance to geomorphic and hydrologic processes, tundra vegetation communities, permafrost and ground-ice characteristics, biogeochemical cycling, wildlife habitat, and human land-use activities. Our project focuses on quantifying the role of thermokarst lake expansion, drainage, and drained lake basin evolution in the Arctic System. We did this through a combination of field studies, environmental sensor networks, remote sensing, and modeling.
This dataset consists of an orthomosaic and digital surface model (DSM) derived from drone surveys on 23 July 2022 at Derksen and Schmutz Basins on the Arctic Coastal Plain of northern Alaska. 6,158 digital images were acquired from a DJI Phantom 4 Real-Time Kinematic (DJI P4RTK) quadcopter with a DJI D-RTK 2 Mobile Base Station. The mapped area was around 580 hectares (ha). The drone system was flown at 100 meters (m) above ground level (agl) and flight speeds varied from 7–8 meters/second (m/s). The orientation of the camera was set to 90 degrees (i.e. looking straight down). The along-track overlap and across-track overlap of the mission were set at 80% and 70%, respectively. All images were processed in the software Pix4D Mapper (v. 4.8.4) using the standard 3D Maps workflow and the accurate geolocation and orientation calibration method to produce the orthophoto mosaic and digital surface model at spatial resolutions of 5 and 10 centimeters (cm), respectively. Elevation information derived over waterbodies is noisy and does not represent the surface elevation of the feature. A Leica Viva differential global positioning system (GPS) provided ground control for the mission and the data were post-processed to WGS84 UTM Zone 5 North in Ellipsoid Heights (meters).
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Orthomosaic Image and Digital Surface Model of Novo Basin, Arctic Coastal Plain of northern Alaska, 20 July 2022
Taken together, lakes and drained lake basins may cover up to 80% of the lowland landscapes in permafrost regions of the Arctic. Lake formation, growth, and drainage in lowland permafrost regions create a terrestrial and aquatic landscape mosaic of importance to geomorphic and hydrologic processes, tundra vegetation communities, permafrost and ground-ice characteristics, biogeochemical cycling, wildlife habitat, and human land-use activities. Our project focuses on quantifying the role of thermokarst lake expansion, drainage, and drained lake basin evolution in the Arctic System. We did this through a combination of field studies, environmental sensor networks, remote sensing, and modeling.
This dataset consists of an orthomosaic and digital surface model (DSM) derived from drone surveys on 20 July 2022 at Novo Basin on the Arctic Coastal Plain of northern Alaska. 332 digital images were acquired from a DJI Phantom 4 Real-Time Kinematic (DJI P4RTK) quadcopter with a DJI D-RTK 2 Mobile Base Station. The mapped area was around 43 hectares (ha). The drone system was flown at 100 meters (m) above ground level (agl) and flight speeds varied from 7–8 meters/second (m/s). The orientation of the camera was set to 90 degrees (i.e. looking straight down). The along-track overlap and across-track overlap of the mission were set at 80% and 70%, respectively. All images were processed in the software Pix4D Mapper (v. 4.8.4) using the standard 3D Maps workflow and the accurate geolocation and orientation calibration method to produce the orthophoto mosaic and digital surface model at spatial resolutions of 5 and 10 centimeters (cm), respectively. Elevation information derived over waterbodies is noisy and does not represent the surface elevation of the feature. A Leica Viva differential global positioning system (GPS) provided ground control for the mission and the data were post-processed to WGS84 UTM Zone 5 North in Ellipsoid Heights (meters).
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- Award ID(s):
- 1806213
- NSF-PAR ID:
- 10481655
- Publisher / Repository:
- NSF Arctic Data Center
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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