TPRoGI: a comprehensive rock glacier inventory for the Tibetan Plateau using deep learning

An inventory of 44,273 rock glaciers, covering approximately 6,000 km2, across the Tibetan Plateau, was compiled using remote sensing and DeepLabv3+, a kind of deep learning model. The file in the format of a shapefile contains the boundary of each rock glacier as vectors in the Coordinate Reference System of EPSG:4326-WGS 84. The associated attribute table includes rock glacier ID, source data, date of mapping, mapper’s name, reviewer’s name, additional information, latitude (units: degrees), longitude (units: degrees), subregion of rock glacier, rock glacier area (units: m2), mean elevation of rock glacier (units: m), median elevation of rock glacier (units: m), minimum elevation of rock glacier (units: m), maximum elevation of rock glacier (units: m), mean slope of rock glacier (units: degrees), median slope of rock glacier (units: degrees), minimum slope of rock glacier (units: degrees), maximum slope of rock glacier (units: degrees), aspect of rock glacier (units: degrees), mean annual air temperature (units: °C), mean annual ground temperature (units: °C), annual precipitation (units:  mm), annual potential incoming solar radiation (units:  kWh/m2). The corresponding names for the table fields are ‘ID’, ‘SOUR_DATA’, ‘MAP_DATE’, ‘MAPPER’, ‘REVIEWER’, ‘ADDI_INF’, ‘LAT’, ‘LON’, ‘SUBREGION’, ‘AREA’, ‘ELE_MEAN’, ‘ELE_MEDIAN’, ‘ELE_MIN’, ‘ELE_MAX’, ‘SLO_MEAN’, ‘SLO_MEDIAN’, ‘SLO_MIN’, ‘SLO_MAX’, ‘ASPECT’, ‘MAAT’, ‘MAGT’, ‘AP’, ‘PISR’.