Temperature Vegetation Precipitation Dryness Index (TVPDI)-based dryness-wetness monitoring in China

Abstract Soil Moisture (SM) is a direct indicator of dryness of the land surface, and the amount of precipitation (P), vegetation status, and Land Surface Temperature (LST) are directly related to SM; thus, these factors indirectly characterize the dryness of the land surface. However, there are limitations and shortcomings of using a single factor to assess dryness because of the interactions among factors. A method that can combine the advantages of the three factors is needed to better monitor dryness. In this study, a new Remote Sensing (RS) dryness index, called the Temperature Vegetation Precipitation Dryness Index (TVPDI), was defined and developed using the Euclidean distance method and three-dimensional (3D) P-Normalized Difference Vegetation Index (NDVI)-LST.The reasonableness of this index was tested and verified using SM data, three variables (P, NDVI, and LST), other recognized dryness indices, crop yield per unit area and Net Primary Productivity (NPP). In addition, the reliability of the TVPDI results was analyzed at different spatial scales and using different data sources. The results demonstrated that the TVPDI was highly correlated with SM (R > 0.64, p