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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Dataset Open Access |
| Language: | en |
| Published: |
PANGAEA
2024
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| Subjects: | |
| Online Access: | https://doi.org/10.1594/PANGAEA.962014 |
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| _version_ | 1867169157158535168 |
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| author | Rettelbach, Tabea Nitze, Ingmar Grünberg, Inge Hammar, Jennika Schäffler, Simon Hein, Daniel Gessner, Matthias Bucher, Tilman Brauchle, Jörg Hartmann, Jörg Sachs, Torsten Boike, Julia Grosse, Guido |
| author_facet | Rettelbach, Tabea Nitze, Ingmar Grünberg, Inge Hammar, Jennika Schäffler, Simon Hein, Daniel Gessner, Matthias Bucher, Tilman Brauchle, Jörg Hartmann, Jörg Sachs, Torsten Boike, Julia Grosse, Guido |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | 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 10.28 px/m³ and 3.86 px/m³ respectively. This dataset covers approximately 15.03 km² of the Inuvik-Tuktoyaktuk-Highway in 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. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_962014 |
| institution | PANGAEA |
| language | en |
| publishDate | 2024 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Inuvik-Tuktoyaktuk-Highway, Canada Rettelbach, Tabea Nitze, Ingmar Grünberg, Inge Hammar, Jennika Schäffler, Simon Hein, Daniel Gessner, Matthias Bucher, Tilman Brauchle, Jörg Hartmann, Jörg Sachs, Torsten Boike, Julia Grosse, Guido AC; Airborne Data; Aircraft; AIRMETH, SMART, AIRCOAST, PermaSAR; Arctic Landscape Dynamics; Binary Object; Binary Object (File Size); Canada; Digital Surface Model; File content; MACS; Modular Observation Solutions for Earth Systems; MOSES; Northwest Territories, Canada; Orthoimagery; P5_212_AIRMETH_2018_1808221501; P5-212_AIRMETH_2018; Permafrost; point clouds; POLAR 5; Project; Structure-from-Motion 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 10.28 px/m³ and 3.86 px/m³ respectively. This dataset covers approximately 15.03 km² of the Inuvik-Tuktoyaktuk-Highway in 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. |
| title | Super-high-resolution aerial imagery, digital surface model and 3D point cloud of Inuvik-Tuktoyaktuk-Highway, Canada |
| topic | AC; Airborne Data; Aircraft; AIRMETH, SMART, AIRCOAST, PermaSAR; Arctic Landscape Dynamics; Binary Object; Binary Object (File Size); Canada; Digital Surface Model; File content; MACS; Modular Observation Solutions for Earth Systems; MOSES; Northwest Territories, Canada; Orthoimagery; P5_212_AIRMETH_2018_1808221501; P5-212_AIRMETH_2018; Permafrost; point clouds; POLAR 5; Project; Structure-from-Motion |
| url | https://doi.org/10.1594/PANGAEA.962014 |