Abstract: Drought disasters happen frequently along the China–Pakistan Economic Corridor (CPEC), which harm the development and safety of the countries along it. It is therefore important to conduct drought monitoring along CPEC. While soil water content (SWC) is a fundamental indicator of drought prediction, temperature vegetation dryness index (TVDI) can predict drought by inverting surface soil water content. Based on a combination of MODIS normalized differential vegetation index (NDVI) and land surface temperature (LST) products and SRTM DEM data, the study used NDVI-LST spatial characteristics to extract the spatial edge of dryness and wetness along CPEC from 2000 – 2017, through which to obtain the monthly TVDI. The study area is from 41°25'24.49"N to 23°45'24.49"N and from 60°53'57.97"E to 79°52'27.97"E. The data are in GeoTiff format, with a spatial resolution of 1 km. We then compared the data with the precipitation and soil water content observed by meteorological stations. Results showed that TVDI had a significantly negative correlation with SPI and SWC (p<0.001). The dataset can be used to support drought monitoring and prediction along CPEC.
Keywords: China–Pakistan Economic Corridor ; temperature vegetation dryness index; land surface temperature; normalized differential vegetation index