Utilising data sources including ZY-3 imagery, Landsat-8 OLI/TIRS, Sentinel-2, and ASTER GDEM V3, high-precision glacier boundaries in the Karakoram range were delineated through deep learning algorithms and manual visual inspection. These boundaries were then assigned attributes such as shape and topography. This dataset provides foundational data support for glacier research in the High Asia region.
ZY-3 fusion imaging resolution 2m project acquisition.
Landsat-8 OLI/TIRS resolution 30m address: https://earth.esa.int/eogateway/catalog/landsat-8-9-oli-tirs-worldwide-data-products.
Sentinel-2 resolution 10m address: https://scihub.copernicus.eu/dhus/#/home.
ASTER GDEM V3 resolution 30m address: https://www.earthdata.nasa.gov/topics/land-surface/digital-elevation-terrain-model-dem.
1. Produce ZY-3 DEM using PCI Geomatica and calculate slope characteristics at 4m resolution; derive surface temperature data from Landsat-8 OLI/TIRS using the gee platform at 30m resolution.
2. Employ the constructed deep learning algorithm to extract glacier boundaries, primarily utilising ZY-3 optical imagery supplemented by topography and temperature characteristics.
3. Manually corrected the raw boundaries extracted by deep learning and assigned attributes such as shape characteristics and topography.
Based on the buffer zone method, the uncertainty in the glacier boundary of the Karakoram Mountains is ±1.71%, while that of the terminal moraine boundary is ±3.58%.
| # | number | name | type |
| 1 | 2021YFE0116800 | National key R & D plan | |
| 2 | KC-24248782 | Multi-modal Remote Sensing Fusion for Glacier Identification Considering Spatial Resolution Differences | other |
| 3 | 42361144874 | Research on Glacial Hazard Processes in the Upper Indus Region Coupling Hydrological and Geochemical Dynamics | National Natural Science Foundation of China |
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CSTR:11738.11.NCDC.GLACIER.DB6974.2025
10.12072/ncdc.glacier.db6974.2025
