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Modelling spatial distribution of fine-scale populations based on residential properties
Han, Dongrui1,2; Yang, Xiaohuan1,2; Cai, Hongyan1; Xu, Xinliang1; Qiao, Zhi3; Cheng, Chuanzhou1,2; Dong, Nan4; Huang, Dong1,2; Liu, Andi5
2019-07-18
Source PublicationINTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN0143-1161
Volume40Issue:14Pages:5287-5300
Corresponding AuthorYang, Xiaohuan(yangxh@lreis.ac.cn)
AbstractFine-scale population gridded datasets are of great significance in emergency response, resource allocation, and traffic planning. Many studies have developed fine-scale population spatialization models based on building patch area (BPA) and building floor (BF). However, little attention has been given to house occupancy rate (HOR). Based on BPA, BF and HOR, this study proposed a novel fine-scale population spatialization method, taking the six districts of Beijing as the study area. The results showed that the HOR in central Beijing was higher than that of the surrounding area. The model with consideration of HOR was more accurate than that without it. In addition, the fine-scale population gridded map generated by this novel method was more accurate (mean prediction error = 8.47%). For all the testing samples, the relative errors of the population gridded data were between -13.54% and 16.04%. Thus, this study suggested that HOR could be a key indicator for fine-scale population modelling. Furthermore, the proposed method could be employed in generating fine-scale population gridded maps and could provide credible and fundamental data for rapid response and decision-making.
DOI10.1080/01431161.2019.1579387
WOS KeywordBUILDING POPULATION ; CHINA ; DENSITY ; IMAGERY ; PATTERNS
Indexed BySCI
Language英语
Funding ProjectStrategic Priority Research Program of Chinese Academy of Sciences[XDA20010203] ; National Natural Science Foundation of China[41771460] ; National Key Research and Development Program of China[2017YFC0503803] ; Key project of the Chinese Academy of Sciences[ZDRW-ZS-2017-4]
Funding OrganizationStrategic Priority Research Program of Chinese Academy of Sciences ; National Natural Science Foundation of China ; National Key Research and Development Program of China ; Key project of the Chinese Academy of Sciences
WOS Research AreaRemote Sensing ; Imaging Science & Photographic Technology
WOS SubjectRemote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000465406100001
PublisherTAYLOR & FRANCIS LTD
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/48094
Collection中国科学院地理科学与资源研究所
Corresponding AuthorYang, Xiaohuan
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Tianjin Univ, Sch Environm Sci & Engn, Key Lab Indoor Air Environm Qual Control, Tianjin, Peoples R China
4.CIGIS CHINA Ltd, Beijing, Peoples R China
5.Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB, Canada
Recommended Citation
GB/T 7714
Han, Dongrui,Yang, Xiaohuan,Cai, Hongyan,et al. Modelling spatial distribution of fine-scale populations based on residential properties[J]. INTERNATIONAL JOURNAL OF REMOTE SENSING,2019,40(14):5287-5300.
APA Han, Dongrui.,Yang, Xiaohuan.,Cai, Hongyan.,Xu, Xinliang.,Qiao, Zhi.,...&Liu, Andi.(2019).Modelling spatial distribution of fine-scale populations based on residential properties.INTERNATIONAL JOURNAL OF REMOTE SENSING,40(14),5287-5300.
MLA Han, Dongrui,et al."Modelling spatial distribution of fine-scale populations based on residential properties".INTERNATIONAL JOURNAL OF REMOTE SENSING 40.14(2019):5287-5300.
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