cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.962002
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Trail Valley Creek, Canada (subset 03)

description: As part of the MOSES airborne campaign led by the Alfred Wegener Institute in 2018, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 15.68 px/m³ and 4.35 px/m³ respectively. This dataset covers approximately 21.37 km² of Trail Valley Creek, Canada, with all images collected on 22 August 2018. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962003
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Trail Valley Creek, Canada (subset 04)

description: As part of the MOSES airborne campaign led by the Alfred Wegener Institute in 2018, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 15.63 px/m³ and 4.98 px/m³ respectively. This dataset covers approximately 21.38 km² of Trail Valley Creek, Canada, with all images collected on 22 August 2018. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962004
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Trail Valley Creek, Canada (subset 05)

description: As part of the MOSES airborne campaign led by the Alfred Wegener Institute in 2018, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 10 cm, as well as photogrammetric point clouds in RGB and NIR at 14.48 px/m³ and 4.74 px/m³ respectively. This dataset covers approximately 21.39 km² of Trail Valley Creek, Canada, with all images collected on 22 August 2018. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962118
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Anaktuvuk River Fire Scar (subset 02)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 22.36 pts/m² and 7.52 pts/m², respectively. This dataset covers approximately 7.52 km² of the Anaktuvuk River fire scar in Alaska, with all images collected on 22 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962128
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Anaktuvuk River Fire Scar (subset 03)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 24.91 pts/m² and 8.58 pts/m², respectively. This dataset covers approximately 7.64 km² of the Anaktuvuk River fire scar in Alaska, with all images collected on 22 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962271
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Ketik Fire Scar, Alaska (subset 01)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 34.79 pts/m² and 11.80 pts/m², respectively. This dataset covers approximately 8.17 km² of the Ketik fire scar in Alaska, with all images collected on 27 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962132
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Anaktuvuk River Fire Scar (subset 04)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 24.33 pts/m² and 8.47 pts/m², respectively. This dataset covers approximately 7.76 km² of the Anaktuvuk River fire scar in Alaska, with all images collected on 22 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962134
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Anaktuvuk River Fire Scar (subset 05)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 23.22 pts/m² and 8.44 pts/m², respectively. This dataset covers approximately 6.21 km² of the Anaktuvuk River fire scar in Alaska, with all images collected on 22 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962275
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Ketik Fire Scar, Alaska (subset 02)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 36.63 pts/m² and 12.29 pts/m², respectively. This dataset covers approximately 9.49 km² of the Ketik fire scar in Alaska, with all images collected on 27 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962278
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Ketik Fire Scar, Alaska (subset 03)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 35.84 pts/m² and 12.29 pts/m², respectively. This dataset covers approximately 9.60 km² of the Ketik fire scar in Alaska, with all images collected on 27 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962279
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Ketik Fire Scar, Alaska (subset 04)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 35.13 pts/m² and 11.51 pts/m², respectively. This dataset covers approximately 9.60 km² of the Ketik fire scar in Alaska, with all images collected on 27 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962297
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Ketik Fire Scar, Alaska (subset 05)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 37.02 pts/m² and 11.77 pts/m², respectively. This dataset covers approximately 9.49 km² of the Ketik fire scar in Alaska, with all images collected on 27 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962312
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Ketik Fire Scar, Alaska (subset 06)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 37.36 pts/m² and 12.48 pts/m², respectively. This dataset covers approximately 9.46 km² of the Ketik fire scar in Alaska, with all images collected on 27 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962317
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Ketik Fire Scar, Alaska (subset 07)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 37.42 pts/m² and 12.65 pts/m², respectively. This dataset covers approximately 9.39 km² of the Ketik fire scar in Alaska, with all images collected on 27 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962320
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Ketik Fire Scar, Alaska (subset 08)

description: As part of the ThawTrend-Air airborne campaign led by the Alfred Wegener Institute in 2019, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 36.11 pts/m² and 12.70 pts/m², respectively. This dataset covers approximately 9.49 km² of the Ketik fire scar in Alaska, with all images collected on 27 July 2019. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962635
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Buckland Fire Scar, Alaska (subset 01)

description: As part of the Perma-X airborne campaign led by the Alfred Wegener Institute in 2021, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 32.61 pts/m² and 11.30 pts/m², respectively. This dataset covers approximately 11.58 km² of the Buckland Fire scar in Alaska, with all images collected on 27 June 2021. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962637
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Buckland Fire Scar, Alaska (subset 02)

description: As part of the Perma-X airborne campaign led by the Alfred Wegener Institute in 2021, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 35.36 pts/m² and 13.04 pts/m², respectively. This dataset covers approximately 8.25 km² of the Buckland Fire scar in Alaska, with all images collected on 27 June 2021. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962638
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Buckland Fire Scar, Alaska (subset 03)

description: As part of the Perma-X airborne campaign led by the Alfred Wegener Institute in 2021, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 36.23 pts/m² and 12.77 pts/m², respectively. This dataset covers approximately 7.69 km² of the Buckland Fire scar in Alaska, with all images collected on 27 June 2021. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962725
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of the Northern Noatak Valley, Alaska (subset 04)

description: As part of the Perma-X airborne campaign led by the Alfred Wegener Institute in 2021, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 23.83 pts/m² and 8.42 pts/m², respectively. This dataset covers approximately 13.36 km² of the northern Noatak Valley in Alaska, with all images collected on 2 July 2021. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962640
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Buckland Fire Scar, Alaska (subset 04)

description: As part of the Perma-X airborne campaign led by the Alfred Wegener Institute in 2021, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 39.26 pts/m² and 13.01 pts/m², respectively. This dataset covers approximately 7.00 km² of the Buckland Fire scar in Alaska, with all images collected on 27 June 2021. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.
DOI: 10.1594/pangaea.962642
title: Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Buckland Fire Scar, Alaska (subset 05)

description: As part of the Perma-X airborne campaign led by the Alfred Wegener Institute in 2021, we collected super-high-resolution multispectral imagery of permafrost landscapes with the Modular Aerial Camera System (MACS), developed by the German Aerospace Center. From these images, we photogrammetrically processed four-band orthophotos (blue, green, red, near-infrared) and digital surface models at a spatial resolution of 7 cm, as well as photogrammetric point clouds in RGB and NIR at 38.39 pts/m² and 12.95 pts/m², respectively. This dataset covers approximately 7.77 km² of the Buckland Fire scar in Alaska, with all images collected on 27 June 2021. This super-high-resolution dataset provides opportunities for generating detailed training datasets of permafrost landform inventories, a baseline for change detection for thermokarst and thermo-erosion processes, and upscaling of field measurements to lower-resolution satellite observations.