Table 1 Data and Sources Used in This Study
From: Unveiling the factors influencing Sakya monastery distribution via interpretable machine learning
Data name | Time | Format | Data source |
|---|---|---|---|
Tibetan Buddhist monastery | Historical period to present | Shapefile | Historical and Geographical Information Database of Tibetan Buddhist Monasteries |
Administrative divisions | 2024 | Shapefile | National Platform for Common GeoSpatial Information Services (https://www.tianditu.gov.cn/) |
Digital Elevation Model (DEM/30 m) | 2011 | Raster | National Geomatics Center of China (https://www.webmap.cn) |
Historical river and lake | 1820 | Shapefile | China Historical GIS (https://timespace-china.fudan.edu.cn) |
Average annual temperature | 1901 | Raster | Institute of Tibetan Plateau Research, Chinese Academy of Sciences (https://data.tpdc.ac.cn) |
Average annual precipitation | 1901 | Raster | Institute of Tibetan Plateau Research, Chinese Academy of Sciences (https://data.tpdc.ac.cn) |
Historical villages and towns | 1820 | Shapefile | China Historical GIS (https://timespace-china.fudan.edu.cn) |
Tea Horse Ancient Road route | 1820 | Shapefile | The Institute for Quantitative Social Science, Harvard University (https://www.iq.harvard.edu/) |
Historical population distribution | 1820 | ASCII | History Database of the Global Environment 3.3 (https://public.yoda.uu.nl/geo/UU01/67UHB4.html) |
