Backpack LiDAR-based digital elevation models from the Perma-X expedition in West Alaska (2022)

• Main Authors: Runge, Alexandra, Kremer, Luis, Barth, Sophia, Inauen, Cornelia, Rettelbach, Tabea, Grosse, Guido
• Format: Dataset
• Language: English
• Published: PANGAEA 2024
• Subjects: AK-Land_2022_NWAlaska; AK-Land_2022_NWAlaska_BAP22A_01; AK-Land_2022_NWAlaska_BAP22A_02; AK-Land_2022_NWAlaska_BAP22B_01; AK-Land_2022_NWAlaska_BAP22B_03; AK-Land_2022_NWAlaska_BAP22B_04; AK-Land_2022_NWAlaska_BAP22C_01; AK-Land_2022_NWAlaska_BAP22C_02; AK-Land_2022_NWAlaska_BAP22D_01; AK-Land_2022_NWAlaska_BAP22D_02; AK-Land_2022_NWAlaska_BAP22H_01; AK-Land_2022_NWAlaska_BAP22H_02; AK-Land_2022_NWAlaska_CSP22F_01; AK-Land_2022_NWAlaska_CSP22F_02; AK-Land_2022_NWAlaska_CSP22F_03; AK-Land_2022_NWAlaska_CSP22F_04; AWI Arctic Land Expedition; BAP22A; BAP22B; BAP22C; BAP22D; BAP22H; Coordinate reference system; CSP22F; Data type; DATE/TIME; DEM; Event label; Feature; Gear; Ice-wedge Polygons; Identification; LATITUDE; northbound; southbound; LONGITUDE; eastbound; westbound; permafrost thaw features; Perma-X; Perma-X Scan Alaska 2022; point clouds; Raster graphic; GeoTIFF format; GeoTIFF format (File Size); Arctic; Ice; permafrost; Seward Peninsula; wedge*; Alaska
• Online Access: https://doi.pangaea.de/10.1594/PANGAEA.963283; https://doi.org/10.1594/PANGAEA.963283

During the Arctic Land Expedition Perma-X in West Alaska (2022-07-28 -- 2022-08-21), several LiDAR scans were acquired using a backpack laser scanning system (GreenValley LiBackpack DGC50). The surveys were carried out on the Baldwin Peninsula and on the Seward Peninsula. The goal of the campaign was to quantify permafrost landscape change by mapping various permafrost thaw features such as thaw slumps, gullies, and degraded ice wedge polygons. These features are predominantly less than 1 km2 in size. The 3D point cloud data from the LiDAR backpack were used to generate Digital Elevation Models (DEMs) of the thaw features. The point cloud processing workflow for these DEMs included point cloud georeferencing, filtering, and ground classification. In total, 15 DEMs were derived at different locations during this campaign. In addition to change detection, the accurate field data are suitable for model parameterization and validation from Earth observation data.