Quantitative assessment model of ecological vulnerability of the Silk Road Economic Belt, China, utilizing remote sensing based on the partition-integration concept
文献类型:期刊论文
作者 | Guo, Bing1,2,3,4; Fan, Yewen3; Yang, Fei5; Jiang, Lin1; Yang, Wenna1; Chen, Shuting1; Gong, Rui1; Liang, Tian1 |
刊名 | GEOMATICS NATURAL HAZARDS & RISK |
出版日期 | 2019 |
卷号 | 10期号:1页码:1346-1366 |
ISSN号 | 1947-5705 |
关键词 | Ecological vulnerability remote sensing quantitative assessment partition-integration Silk Road Economic Belt |
DOI | 10.1080/19475705.2019.1568313 |
通讯作者 | Fan, Yewen(1391701562@qq.com) |
英文摘要 | The 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. |
WOS关键词 | WATER ; REGION ; AREAS ; GIS ; CONSUMPTION ; MANAGEMENT ; ALGORITHM ; CAPACITY ; XINJIANG ; PLATEAU |
资助项目 | Natural 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] |
WOS研究方向 | Geology ; Meteorology & Atmospheric Sciences ; Water Resources |
语种 | 英语 |
出版者 | TAYLOR & FRANCIS LTD |
WOS记录号 | WOS:000468744700001 |
资助机构 | Natural 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 |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/59636] |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Fan, Yewen |
作者单位 | 1.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 |
推荐引用方式 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. |
入库方式: OAI收割
来源:地理科学与资源研究所
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