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Quantitative assessment model of ecological vulnerability of the Silk Road Economic Belt, China, utilizing remote sensing based on the partition-integration concept
Guo, Bing1,2,3,4; Fan, Yewen3; Yang, Fei5; Jiang, Lin1; Yang, Wenna1; Chen, Shuting1; Gong, Rui1; Liang, Tian1
2019
Source PublicationGEOMATICS NATURAL HAZARDS & RISK
ISSN1947-5705
Volume10Issue:1Pages:1346-1366
Corresponding AuthorFan, Yewen(1391701562@qq.com)
AbstractThe various patterns of spatial heterogeneity in the eco-environment of the Silk Road Economic Belt of China differ greatly. In this study, a partition-integration concept was introduced to assess the ecological vulnerability of the Silk Road Economic Belt in China. To confirm the comparability of ecological vulnerability among different sub-regions, the net primary productivity (NPP) was utilized to determine the ecological vulnerability thresholds for different sub-regions. The results indicated that: (1) the new assessment model of ecological vulnerability based on the partition-integration concept was strongly operational and practical for the study region; (2) NPP was conducive to the continuous expression of ecological vulnerability, which can ensure better comparison and analysis of ecological vulnerability among the three sub-regions; (3) the spatial patterns of zones at different vulnerability levels differed greatly. The mild vulnerability zone was the most widely distributed, whereas the zone of slight vulnerability covered the smallest area. (4) Specific environmental protection and treatment measures should be conducted in the three sub-regions with different dominant ecological problems. These results can provide decision-making support in realizing the great strategy of the "one belt and one road" idea.
KeywordEcological vulnerability remote sensing quantitative assessment partition-integration Silk Road Economic Belt
DOI10.1080/19475705.2019.1568313
WOS KeywordWATER ; REGION ; AREAS ; GIS ; CONSUMPTION ; MANAGEMENT ; ALGORITHM ; CAPACITY ; XINJIANG ; PLATEAU
Indexed BySCI
Language英语
Funding ProjectNatural Science Foundation of Shandong Province[ZR2018BD001] ; Open Fund of the Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University[KLGIS2017A02] ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University[17I04] ; Project of Shandong Province Higher Educational Science and Technology Program[J18KA181] ; Project of Hubei Key Laboratory of Regional Development and Environmental Response (Hubei University)[2017(B)003] ; National Key R&D Program of China[2017YFA0604804] ; Initial Scientific Research Fund of doctor in Shandong University of Technology[4041/416027]
Funding OrganizationNatural Science Foundation of Shandong Province ; Open Fund of the Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University ; Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University ; Project of Shandong Province Higher Educational Science and Technology Program ; Project of Hubei Key Laboratory of Regional Development and Environmental Response (Hubei University) ; National Key R&D Program of China ; Initial Scientific Research Fund of doctor in Shandong University of Technology
WOS Research AreaGeology ; Meteorology & Atmospheric Sciences ; Water Resources
WOS SubjectGeosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences ; Water Resources
WOS IDWOS:000468744700001
PublisherTAYLOR & FRANCIS LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/59637
Collection中国科学院地理科学与资源研究所
Corresponding AuthorFan, Yewen
Affiliation1.Shandong Univ Technol, Sch Civil Architectural Engn, Zibo, Shandong, Peoples R China
2.East China Normal Univ, Minist Educ, Key Lab Geog Informat Sci, Shanghai, Peoples R China
3.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Hubei, Peoples R China
4.Hubei Univ, Hubei Key Lab Reg Dev & Environm Response, Wuhan, Hubei, Peoples R China
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Guo, Bing,Fan, Yewen,Yang, Fei,et al. Quantitative assessment model of ecological vulnerability of the Silk Road Economic Belt, China, utilizing remote sensing based on the partition-integration concept[J]. GEOMATICS NATURAL HAZARDS & RISK,2019,10(1):1346-1366.
APA Guo, Bing.,Fan, Yewen.,Yang, Fei.,Jiang, Lin.,Yang, Wenna.,...&Liang, Tian.(2019).Quantitative assessment model of ecological vulnerability of the Silk Road Economic Belt, China, utilizing remote sensing based on the partition-integration concept.GEOMATICS NATURAL HAZARDS & RISK,10(1),1346-1366.
MLA Guo, Bing,et al."Quantitative assessment model of ecological vulnerability of the Silk Road Economic Belt, China, utilizing remote sensing based on the partition-integration concept".GEOMATICS NATURAL HAZARDS & RISK 10.1(2019):1346-1366.
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