期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII - Part 2
页码：519-524
出版社：Copernicus Publications
摘要：Temperature-Vegetation Dryness Index (TVDI) is one of the agriculture drought indexes. This paper presents a data composite method which improves the calculation of TVDI through taking the time of pixel into consideration, and the adaptability of TVDI in drought assessment has also enhanced significantly. First, the Normalized Difference Vegetation Index (NDVI) data series are composed by using maximum value composite (MVC) method, and the Land Surface Temperature (LST) data series are composed to construct NDVI-Ts feature space. Then, the wet and dry sides of NDVI-Ts feature space are fixed by a number of ways to build new TVDI, and we note it as T-TVDI, for assessing the drought condition. To verify our proposed method, TVDI in time scale of ten-days is established for Chongqing region in China, and the results coincide with the actual situation. Finally, the T-TVDI and TVDI of Chongqing region in 2008 are calculated and compared. The correlations of them and Soil Moisture are analyzed as well as Precipitation. It shows that T-TVDI has the advantages of stability and high accuracy in the short term. It is feasible to use T-TVDI to evaluate drought in proper region and reasonable crop growth period
