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Zone division and extraction of historic area based on big data

文献类型：期刊论文

作者Zhu, He1,2,3
刊名CURRENT ISSUES IN TOURISM
出版日期2020-09-10
页码22
关键词Zone division zone extraction big data tourists and residents historic area China
ISSN号1368-3500
DOI10.1080/13683500.2020.1814223
通讯作者Zhu, He(zhuhe@igsnrr.ac.cn)
英文摘要Although zoning has great potential in coordinating regional development and destination management, it is challenging to derive an optimal zoning method in the historic district. To address this challenge, this paper proposes a zone division method attempting to balance tourists' and residents' spatial demands and realizing urban historic area sustainable development. A 3-zones (Tourist active zone, Local community zone, and Buffer zone) plan is put forward based on a case study of the Qianmen area in Beijing, China. Then zone extraction is conducted with two kinds of big data, Points of Interests (POI) and Mobile Phone Signal (MPS). The Thiessen polygon-based method to divide the tourists' concentrated area and a fishnet-based density method to distinguish the area of residents mainly living are used to help identify borderlines of different zones. A survey map for tourists and residents is used to verify the zone extraction results. Subsequently, zone management strategies are suggested for different zones improvement. This discussion contributes to overcoming the traditional methods' defects in subarea-scale research with scientifically sound and practical.
WOS关键词LAND-USE ; TOURISM ; DESTINATION ; DISTRICT ; INFORMATION ; EXPERIENCES ; NETWORKS ; POINTS ; SCALE ; TOWN
资助项目National Natural Science Foundation of China (NSFC)[41801139] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDA23100302]
WOS研究方向Social Sciences - Other Topics
语种英语
WOS记录号WOS:000569503400001
出版者ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
资助机构National Natural Science Foundation of China (NSFC) ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)
源URL[http://ir.igsnrr.ac.cn/handle/311030/156879]  
专题中国科学院地理科学与资源研究所
通讯作者Zhu, He
作者单位1.Chinese Acad Sci, Key Lab Reg Sustainable Dev Modeling, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
3.Univ Calif Los Angeles, Dept Geog, Los Angeles, CA 90024 USA
推荐引用方式
GB/T 7714		 Zhu, He. Zone division and extraction of historic area based on big data[J]. CURRENT ISSUES IN TOURISM,2020:22.
APA Zhu, He.(2020).Zone division and extraction of historic area based on big data.CURRENT ISSUES IN TOURISM,22.
MLA Zhu, He."Zone division and extraction of historic area based on big data".CURRENT ISSUES IN TOURISM (2020):22.

入库方式： OAI收割

来源：地理科学与资源研究所

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