干旱区生态环境知识资源中心(Arid): Probabilistic assessment of remote sensing-based terrestrial vegetation vulnerability to drought stress of the Loess Plateau in China

Arid

DOI	10.1016/j.rse.2019.111290
	Probabilistic assessment of remote sensing-based terrestrial vegetation vulnerability to drought stress of the Loess Plateau in China
	Fang, Wei 1; Huang, Shengzhi 1; Huang, Qiang 1; Huang, Guohe 2; Wang, Hao 3; Leng, Guoyong 4,5; Wang, Lu 1; Guo, Yi 1
通讯作者	Huang, Shengzhi
来源期刊	REMOTE SENSING OF ENVIRONMENT
ISSN	0034-4257
EISSN	1879-0704
出版年	2019
卷号	232
英文摘要	Quantitative understanding of vegetation vulnerability under drought stress is essential to initiating drought preparedness and mitigation. In this study, a bivariate probabilistic framework is developed for assessing vegetation vulnerability and mapping drought-prone ecosystems more informatively, which is different from previous studies conducted in a deterministic way. The Normalized Difference Vegetation Index (NDVI) is initially correlated to the Standardized Precipitation Index (SPI) at contrasting timescales to evaluate the degree of vegetation dependence on water availability and screen out the vegetation response time. Afterward, the monthly NDVI series is connected with the most correlated SPI to derive joint distributions using a copula method. On such basis, conditional probabilities of vegetation losses are estimated under multiple drought scenarios and used for revealing tempo-spatial patterns of vegetation vulnerability. Particular focus is directed to the Loess Plateau (LP), China, which is a world-famous environmentally fragile area. Results indicate that the proposed framework is valid for vegetation vulnerability assessment as the pair-wise SPI-NDVI observations fall within high-density areas of the estimated NDVI distributions. From a probabilistic perspective, roughly 95% of the LP exhibits greater probability of vegetation losses when suffering from water deficits rather than water surplus. Vegetation loss probabilities reaching their peak (39.7%) in summer indicate the highest vegetation vulnerability to drought stress in summer months sequentially followed by autumn (32.9%) and spring (31.0%), which is linked to marked variations in water requirement at different stages of vegetation growth. Spatially, drought-vulnerable regions are identified in the western edge with vegetation loss probability 20.6% higher than the LP mean value, suggesting higher vulnerability in more arid areas. Irrigation practices and large-scale vegetation restoration, as two important sources of anthropogenic disturbance in the LP, benefit the decreased vegetation vulnerability over the majority of affected areas. Results may increase our knowledge about climatic controls on vegetation health and support the ecosystem restoration planning in the LP.
英文关键词	Vegetation health Drought stress Copula method Conditional probability Vulnerability analysis
类型	Article
语种	英语
国家	Peoples R China ; Canada ; England
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000486355300026
WOS关键词	STANDARDIZED PRECIPITATION INDEX ; CLIMATE-CHANGE ; SOIL-MOISTURE ; ECOLOGICAL RESTORATION ; METEOROLOGICAL DROUGHT ; AGRICULTURAL DROUGHT ; RIPARIAN VEGETATION ; ECO-ENVIRONMENT ; CARBON BALANCE ; WATER DEMAND
WOS类目	Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	中国科学院地理科学与资源研究所 ; University of Oxford
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/218430
作者单位	1.Xian Univ Technol, Sch Water Resources & Hydropower, State Key Lab Ecohydraul Northwest Arid Reg China, Xian 710048, Shaanxi, Peoples R China; 2.Univ Regina, Inst Energy Environm & Sustainable Communities, Regina, SK S4S 0A2, Canada; 3.China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China; 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China; 5.Univ Oxford, Environm Change Inst, Oxford OX1 3QY, England
推荐引用方式 GB/T 7714	Fang, Wei,Huang, Shengzhi,Huang, Qiang,et al. Probabilistic assessment of remote sensing-based terrestrial vegetation vulnerability to drought stress of the Loess Plateau in China[J]. 中国科学院地理科学与资源研究所, University of Oxford,2019,232.
APA	Fang, Wei.,Huang, Shengzhi.,Huang, Qiang.,Huang, Guohe.,Wang, Hao.,...&Guo, Yi.(2019).Probabilistic assessment of remote sensing-based terrestrial vegetation vulnerability to drought stress of the Loess Plateau in China.REMOTE SENSING OF ENVIRONMENT,232.
MLA	Fang, Wei,et al."Probabilistic assessment of remote sensing-based terrestrial vegetation vulnerability to drought stress of the Loess Plateau in China".REMOTE SENSING OF ENVIRONMENT 232(2019).