An Updated Inventory of Retrogressive Thaw Slumps Along the Vulnerable Qinghai-Tibet Engineering Corridor
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 DeepLabv3+, a kind of deep learning model. The file in the format of Geopackage/GPKG contains the boundary of eac...
| Main Authors: | , , |
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| Format: | Dataset |
| Language: | English |
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Zenodo
2021
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5281/zenodo.6397028 https://zenodo.org/record/6397028 |
| Summary: | 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 DeepLabv3+, a kind of deep learning model. The file in the format of Geopackage/GPKG 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 ), Deep Learning model. The corresponding names for the table fields are ‘Probability’, ‘Year-month’, ‘Source Image’, ‘Near roads’, ‘Initial year’, ‘Longitude’, ‘Latitude’, ‘Area’, ‘Deep Learning model’. The ‘Probability’, having values of ‘High’, ‘Medium’ and ‘Low’, measures how much we are sure about the mapped RTSs. |
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