Remote sensing strategies to characterization of drought, vegetation dynamics in relation to climate change from 1983 to 2016 in Tibet and Xinjiang Province, China.

Abstract

Due to various land cover changes, vegetation dynamics, and climate, drought is the most complex climate-related disaster problem in Tibet and Xinjiang, China. The purpose of the present study is to analyze the performance of the AVHRR Normalized Vegetation Index (NDVI) and the temporal and spatial differences of seasonal vegetation dynamics by correlating the results with rainfall and temperature data of NASA's MERRA to examine the vegetation dynamics and droughts in Tibet and the Xinjiang Province of China. Our method is based on the use of AVHRR NDVI data and NASA MERRA temperature and precipitation during 1983-2016. Due to the dryness and low vegetation, NDVI is more useful to describe the drought conditions in Tibet and Xinjiang of China. The NDVI, TCI, VHI, NVSWI, VCI, TVDI, and NAP from April to October increased rapidly. While the NDVI, TCI, VHI, NVSWI, NAP, TVDI, and VCI are stable every month in September, again improve in October, and then confirm downward trend in December. The NDVI, TCI, VHI, NVSWI, NAP, VCI, and TVDI monthly values indicate that Tibet and Xinjiang province of China suffered from severe drought in 2006, 2008, and 2012 which were the most drought years. For monitoring drought in Tibet and Xinjiang province of China, the NDVI, TVDI, NAP, VCI, and NVSWI values were selected as a tool for reporting drought events during different growing seasons. Seasonal values of TVDI, NDVI, NAP, NVSWI, and VCI confirmed that Tibet and Xinjiang province of China suffered from severe drought in 2006, 2008, and 2012 and led the durations of severe drought. The correlation between NDVI, TCI, VHI, NAP, TVDI, and VCI showed a significantly positive correlation, while the significantly negative correlation between NVSWI and NDVI showed a good indication for the assessment of drought, especially for the agricultural regions of Tibet and Xinjiang province of China. This shows that the positive sign to support NAP, NVSWI, and TVDI is good monitoring of the drought indexes in Tibet and the Xinjiang province of China.