Xia, Zhuoxuan; Huang, Lingcao; Liu, Lin (2021): An Inventory of Retrogressive Thaw Slumps Along the Vulnerable Qinghai-Tibet Engineering Corridor [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.933957
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Abstract:
An inventory of 875 retrogressive thaw slumps over a landscape of 54000 km^2, along the Qinghai-Tibet Engineering Corridor underlain by permafrost, was compiled using remote sensing and deep learning. The file in the format of ESRI Shapefile contains the boundary of each retrogressive thaw slump as vectors in the Coordinate Reference System of EPSG:32646 - WGS 84. The associated attribute table includes probability, time of the satellite images, source of the satellite images, the near roads labels, year of initiation, longitude and latitude, area (units: m^2). The corresponding names for the table fields are 'Probabilit', 'Year-month', 'Source Img', 'near roads', 'Initial_Y', 'Longitude', 'Latitude', 'Area'. The files in the GIF format show the temporal changes of each retrogressive thaw slump from 2016 to 2020.
Related to:
Xia, Zhuoxuan; Huang, Lingcao; Fan, Chengyan; Jia, Shichao; Lin, Zhanju; Liu, Lin; Luo, Jin; Niu, Fujun; Zhang, Tingjun (in review): Using a Deep-learning-aided Method to Obtain an Inventory of Retrogressive Thaw Slumps Along the Vulnerable Qinghai-Tibet Engineering Corridor.
Xia, Zhuoxuan; Huang, Lingcao; Liu, Lin (2021): Inventorying Retrogressive Thaw Slumps along the Qinghai-Tibet Engineering Corridor using a deep-learning-aided semi-automatic method. EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-16426, https://doi.org/10.5194/egusphere-egu21-16426
Coverage:
Latitude: 32.000000 * Longitude: 93.000000
Event(s):
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | File content | Content | Xia, Zhuoxuan | |||
| 2 | Binary Object | Binary | Xia, Zhuoxuan |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
4 data points