High-resolution livestock seasonal distribution data on the Qinghai-Tibet Plateau in 2020

We provide a division of cold-season and warm-season pastures on the Qinghai-Tibet Plateau (QTP), and livestock, cattle, and sheep number distribution data on each of the seasonal pastures, in dasymetric representation at a spatial resolution of 500 m.  Seasonal pastures were delineated by identifying the key elements that affect the seasonal distribution of grazing and combining the random forest classification model, and the average AUC (area under the ROC curve) of the model is 0.98. Spatial disaggregation weights were derived using the prediction from a random forest model that linked county-level census livestock numbers to topography, climate, vegetation, and socioeconomic predictors. The random forest model's internal cross-validation coefficients of determination (R²) range from 0.68 to 0.83, and the external cross-scale validations between dasymetric mapping results and township census data range from 0.52 to 0.70. The data could provide important information for further modeling of human-environment interaction under climate change for this region. This study is supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP, grant no. 2019QZKK0906).