A dataset of monthly temperature vegetation dryness index along the China–Pakistan Economic Corridor from 2000 – 2017

Drought disasters happen frequently along the China–Pakistan Economic Corridor (CPEC), which restrict the development and safety of the alongside countries. Therefore, we need to conduct the research of drought monitoring along the CPEC. Soil water content (SWC) is a fundamental indicator to predict drought. Temperature vegetation dryness index (TVDI) could predict drought by inverting surface soil water content. This dataset is based on normalized differential vegetation index (NDVI) and land surface temperature (LST) from MODIS, combined with SRTM DEM data and applied NDVI-LST spatial characteristics to get the monthly TVDI by extracting the spatial edge of dryness and wetness along CPEC from 2000-2017. 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 format is GeoTiff with the spatial resolution of 1 km. According to the precipitation and soil water content from the meteorological stations, the correlation analysis showed that TVDI had a significantly negative correlation with SPI and SWC (p<0.001). Our result could support drought monitoring and prediction along CPEC