Using Temperature Vegetation Drought Index for Monitoring Drought Based on Remote Sensing Data

Abstract

Drought is one of the major natural disasters in China, it has extremely affected national food security. In this study, Normalized Difference Vegetation Index (NDVI) and surface temperature (Ts) were calculated by using 8-day composite Moderate-Resolution Imaging Spectroradiometer (MODIS) reflectance product data MOD09A1 and MOD11A2, then NDVI-Ts feature space was obtained and dry edge and wet edge equation was fit. According to coefficients of dry edge and wet edge equation, Temperature Vegetation Drought Index (TVDI) will be calculated and refer it as a drought monitoring indicator. In addition, drought monitoring and classification of Shandong province (China) was completed by TVDI from February to May,2011. Furthermore, the drought classification diagram was made and the drought area in each period was counted. The results showed revealed that: NDVI-Ts feature was roughly a triangular shape in the two-dimensional plane, and drought conditions could be better monitored through TVDI. Finally, the desktop demonstration system of drought monitoring was designed and some general functions were realized based on ArcGis Engine.

Applying TVDI based on remote sensing data to evaluate the drought in Cu Chi District

“…scale, all weather monitoring and multi-band working which are suitable for real-time monitoring on a large-scale. In recent years, with the development of multi-temporal and multi-spectral remote sensing technologies, the large amount of observational data has been achieved, which made it possible for real-time drought monitoring (Huang et al, 2011). Currently, methods of remote sensing for drought monitoring include thermal inertia, microwave remote sensing and the vegetation indices, etc.…”