Extracting knowledge from legacy maps to delineate eco-geographical regions
文献类型:期刊论文
作者 | Yang, Lin3,4![]() ![]() ![]() ![]() |
刊名 | INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
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出版日期 | 2020-09-18 |
页码 | 23 |
关键词 | Knowledge extraction ecological regionalization legacy map buffer zone fuzzy membership function |
ISSN号 | 1365-8816 |
DOI | 10.1080/13658816.2020.1806284 |
通讯作者 | Wu, Shaohong(wush@igsnrr.ac.cn) |
英文摘要 | Legacy ecoregion maps contain knowledge on relationships between eco-region units and their environmental factors. This study proposes a method to extract knowledge from legacy area-class maps to formulate a set of fuzzy membership functions useful for regionalization. We develop a buffer zone approach to reduce the uncertainty of boundaries between eco-region units on area-class maps. We generate buffer zones with a Euclidean distance perpendicular to the boundaries, then the original eco-region units without buffer zones serve as the basic units to generate the probability density functions (PDF) of environmental variables. Then, we transform the PDFs to fuzzy membership functions for class-zones on the map. We demonstrate the proposed method with a climatic zone map of China. The results showed that the buffer zone approach effectively reduced the uncertainties of boundaries. A buffer distance of 10-15 km was recommended in this study. The climatic zone map generated based on the extracted fuzzy membership functions showed a higher spatial stratification heterogeneity (compared to the original map). Based on the fuzzy membership functions with climate data of 1961-2015, we also prepared an updated climatic zone map. This study demonstrates the prospects of using fuzzy membership functions to delineate area classes for regionalization purpose. |
WOS关键词 | CLIMATE-CHANGE ; FUZZY-LOGIC ; ECOREGIONS ; SIMILARITY ; MANAGEMENT ; FRAMEWORK ; MODEL |
资助项目 | National Natural Science Foundation of China[41530749] ; National Natural Science Foundation of China[41971054] ; Key Laboratory of Land Surface Pattern and Simulation, CAS[LBKF201506] |
WOS研究方向 | Computer Science ; Geography ; Physical Geography ; Information Science & Library Science |
语种 | 英语 |
WOS记录号 | WOS:000571094500001 |
出版者 | TAYLOR & FRANCIS LTD |
资助机构 | National Natural Science Foundation of China ; Key Laboratory of Land Surface Pattern and Simulation, CAS |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/156941] ![]() |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Wu, Shaohong |
作者单位 | 1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 2.China Acad Urban Planning & Design, Urban Planning Acad Infromat Ctr, Beijing, Peoples R China 3.Nanjing Univ, Sch Geog & Ocean Sci, Nanjing, Peoples R China 4.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China 5.Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Yang, Lin,Li, Xinming,Yang, Qinye,et al. Extracting knowledge from legacy maps to delineate eco-geographical regions[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2020:23. |
APA | Yang, Lin.,Li, Xinming.,Yang, Qinye.,Zhang, Lei.,Zhang, Shujie.,...&Zhou, Chenghu.(2020).Extracting knowledge from legacy maps to delineate eco-geographical regions.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,23. |
MLA | Yang, Lin,et al."Extracting knowledge from legacy maps to delineate eco-geographical regions".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE (2020):23. |
入库方式: OAI收割
来源:地理科学与资源研究所
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