A novel remote sensing ecological vulnerability index on large scale: A case study of the China-Pakistan Economic Corridor region

doi:10.1016/j.ecolind.2021.107955

	A novel remote sensing ecological vulnerability index on large scale: A case study of the China-Pakistan Economic Corridor region
	Wu, Hongwei 1; Guo, Bing 1,2,3,4,5,6,7,9; Fan, Junfu 1; Yang, Fei 3; Han, Baomin 1; Wei, Cuixia 1; Lu, Yuefeng 1; Zang, Wenqian 8; Zhen, Xiaoyan 7; Meng, Chao 6
刊名	ECOLOGICAL INDICATORS
	2021-10-01
卷号	129 页码:13
关键词	Ecological vulnerability Remote sensing Spatial distribution Geodetector China-Pakistan Economic Corridor region
ISSN号	1470-160X
DOI	10.1016/j.ecolind.2021.107955
通讯作者	Guo, Bing(guobingjl@163.com) ; Fan, Junfu(fanjf@sdut.edu.cn) ; Yang, Fei(yangfei@igsnrr.ac.cn)
英文摘要	There were dramatic changes in the ecological vulnerability (EV) of the China-Pakistan Economic Corridor (CPEC) region due to the effects of climate change and human activity. Obtaining field observation and statistical data for the evaluation of the EV of the CPEC region is difficult due to its transnational status. This study proposes a novel remote sensing ecological vulnerability index (RSEVI) based on the Moderate Resolution Imaging Spectroradiometer (MODIS), STRM3, DMSP-OLS, and NPP-VIIRS products. The RSEVI index was applied to the CPEC region to investigate the spatiotemporal changes in EV and the influencing factors during 2000-2019. The results showed that: (1) the large-scale application of the RSEVI index showed good applicability to the CPEC region, with a precision of 89.75%; (2) the average RSEVI value for the CPEC region was 0.83, thereby falling into a category of "intensive vulnerability"; (3) a stable trend in RSEVI was observed for the entire CPEC region during the study period, except for the Indus Basin where there was a significant change; (4) the increasing rate of the RSEVI in the northeastern parts exceeded that of other parts during 2000-2019; (5) precipitation, temperature, and vegetation coverage showed negative relationships with RSEVI, whereas RSEVI showed a positive relationship with slope. The RSEVI results indicated that ice and bare land were the most vulnerable, whereas cropland was the least vulnerable; (6) there were differences in the dominant factor and dominant interactive factor among different sub-regions. The results of this study could provide important decision support for the protection of the ecological environment and for economic development.
资助项目	Open fund of Key Laboratory of National Geographic Census and Monitoring, MNR[2020NGCM02] ; Open Research Fund of the Key Laboratory of Digital Earth Science, Chinese Academy of Sciences[2019LDE006] ; Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources[KF-2020-05001] ; Open fund of Key Laboratory of Land use, Ministry of Natural Resources[20201511835] ; Open Fund of Key Laboratory for Digital Land and Resources of Jiangxi Province, East China University of Technology[DLLJ202002] ; Open foundation of MOE Key Laboratory of Western China's Environmental Systems, Lanzhou University ; fundamental Research funds for the Central Universities[lzujbky-2020-kb01] ; University-Industry Collaborative Education Program[201902208005] ; Open Fund of Key Laboratory of Meteorology and Ecological Environment of Hebei Province[Z202001H] ; Open Fund of Key Laboratory of Geomatics and Digital Technology of Shandong Province ; Open Fund of Key Laboratory of Geomatics Technology and Application Key Laboratory of Qinghai Province[QHDX-2019-04]
WOS关键词	CLIMATE-CHANGE ; RIVER-BASIN ; MANAGEMENT
WOS研究方向	Biodiversity & Conservation ; Environmental Sciences & Ecology
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000681692700002
资助机构	Open fund of Key Laboratory of National Geographic Census and Monitoring, MNR ; Open Research Fund of the Key Laboratory of Digital Earth Science, Chinese Academy of Sciences ; Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources ; Open fund of Key Laboratory of Land use, Ministry of Natural Resources ; Open Fund of Key Laboratory for Digital Land and Resources of Jiangxi Province, East China University of Technology ; Open foundation of MOE Key Laboratory of Western China's Environmental Systems, Lanzhou University ; fundamental Research funds for the Central Universities ; University-Industry Collaborative Education Program ; Open Fund of Key Laboratory of Meteorology and Ecological Environment of Hebei Province ; Open Fund of Key Laboratory of Geomatics and Digital Technology of Shandong Province ; Open Fund of Key Laboratory of Geomatics Technology and Application Key Laboratory of Qinghai Province
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/164731]
专题	中国科学院地理科学与资源研究所
通讯作者	Guo, Bing; Fan, Junfu; Yang, Fei
作者单位	1.Shandong Univ Technol, Sch Civil Architectural Engn, Zibo 255000, Shandong, Peoples R China 2.Geomat Technol & Applicat Key Lab Qinghai Prov, Xining 810001, Peoples R China 3.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 4.Minist Nat Resources, Key Lab UrbanLand Resources Monitoring & Simulat, Shenzhen 518000, Peoples R China 5.Minist Nat Resources, Key Lab Natl Geog Census & Monitoring, Wuhan 430072, Peoples R China 6.China Land Survey & Planning Inst, Key Lab Land Use, MNR, Beijing 100035, Peoples R China 7.Key Lab Meteorol & Ecol Environm Hebei Prov, Shijiazhuang 050021, Hebei, Peoples R China 8.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100101, Peoples R China 9.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Wu, Hongwei,Guo, Bing,Fan, Junfu,et al. A novel remote sensing ecological vulnerability index on large scale: A case study of the China-Pakistan Economic Corridor region[J]. ECOLOGICAL INDICATORS,2021,129:13.
APA	Wu, Hongwei.,Guo, Bing.,Fan, Junfu.,Yang, Fei.,Han, Baomin.,...&Meng, Chao.(2021).A novel remote sensing ecological vulnerability index on large scale: A case study of the China-Pakistan Economic Corridor region.ECOLOGICAL INDICATORS,129,13.
MLA	Wu, Hongwei,et al."A novel remote sensing ecological vulnerability index on large scale: A case study of the China-Pakistan Economic Corridor region".ECOLOGICAL INDICATORS 129(2021):13.