Publications

Zhu, S; Xiao, ZX; Luo, XG; Zhang, HR; Liu, XW; Wang, R; Zhang, MZ; Huo, ZB (2020). Multidimensional Response Evaluation of Remote-Sensing Vegetation Change to Drought Stress in the Three-River Headwaters, China. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 13, 6249-6259.

Abstract
The impact of drought on ecosystems has become increasingly prominent. This study used the MODIS remote-sensing vegetation index and the standardized precipitation index to quantify vegetation coverage status and meteorological drought level. Using the copula method, the joint distribution of the drought index and related vegetation cover variables were simulated for the first time. The conditional distribution of vegetation biomass was deduced, and the multidimensional response between the vegetation biomass and drought was explored to understand the possible vegetation loss under different drought severity conditions. The three-river headwaters (TRH) region is the source place of the Yangtze River, Yellow River, and Lancang River, where the ecosystem is characterized by the innate vulnerability. Using this region as a case study, the results show that the spatiotemporal evolution of drought and vegetation in the TRH region has apparent regional heterogeneity. The vegetation cover in the eastern region is significantly better than that in the northwestern region, while the vegetation growth trend in the northwestern region is stronger than that in the southeastern region. It is feasible to build a vegetation-drought multidimensional response model based on the copula method. In 92.5% of the TRH region, vegetation cover was significantly affected by the severity of the drought. The impact on the growth of vegetation caused by persistent drought events was higher than that of short-term but high-intensity drought. The vegetation in the TRH area has a certain degree of drought resistance. This study provides outstanding theoretical support and reference for the protection of the TRH basin ecosystem.

DOI:
10.1109/JSTARS.2020.3027347

ISSN:
1939-1404