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Trend surface analysis of geographic flows

文献类型：期刊论文

作者Guo, Beiyang4,5; Pei, Tao2,3,4; Song, Ci3,4; Shu, Hua3,4; Wu, Mingbo3,4; Guo, Sihui3,4; Jiang, Jingyu4,5; Du, Peijun1,2,5
刊名INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
出版日期2022-10-06
页码20
关键词origin-destination (OD) flow flow space flow trend trend surface analysis
ISSN号1365-8816
DOI10.1080/13658816.2022.2129660
通讯作者Pei, Tao(peit@lreis.ac.cn)
英文摘要An origin-destination (OD) flow is the movement of objects from an origin to a destination. Determining how the flows vary across geographic locations helps understand the mechanism of flow distributions; however, it has rarely been studied. Here, we propose a trend surface model with polynomial functions to quantify the flow distribution with coordinates in the flow space. This model assumes that an observed data-record is composed of the trend value and the residual, and is represented by the orthogonal polynomial with O and D coordinates as independent variables and flow properties as dependent variables. The simulation experiments based on the linear and quadratic models indicated that the trend surface function could reflect the increasing/decreasing variation of flows with OD locations (i.e. flow trends) in different patterns. Applying this model to a case study of taxi OD flows in the broad Central Business District of Beijing, we found that the flows exhibited a rising trend toward the southwest. The trend surface characteristics are associated with the distributions of urban functional patches, where the workplaces and residences increased toward the southwest in the study area. Notably, the spatial deviations of trend surface model can help in identifying site pairs that attract flows at a high density (e.g. commerce centers and big communities), facilitating the planning of public transportation to mitigate the congestion.
WOS关键词SPATIAL INTERACTION ; AUTOCORRELATION ; COMPONENTS
资助项目National Natural Science Foundation of China[42071436] ; National Natural Science Foundation of China[42101431] ; National Key R&D Program of China[2017YFB0503604]
WOS研究方向Computer Science ; Geography ; Physical Geography ; Information Science & Library Science
语种英语
WOS记录号WOS:000865036700001
出版者TAYLOR & FRANCIS LTD
资助机构National Natural Science Foundation of China ; National Key R&D Program of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/185552]  
专题中国科学院地理科学与资源研究所
通讯作者Pei, Tao
作者单位1.Minist Nat Resources China, Key Lab Land Satellite Remote Sensing Applicat, Nanjing, Peoples R China
2.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
5.Nanjing Univ, Sch Geog & Ocean Sci, Nanjing, Peoples R China
推荐引用方式
GB/T 7714		 Guo, Beiyang,Pei, Tao,Song, Ci,et al. Trend surface analysis of geographic flows[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2022:20.
APA Guo, Beiyang.,Pei, Tao.,Song, Ci.,Shu, Hua.,Wu, Mingbo.,...&Du, Peijun.(2022).Trend surface analysis of geographic flows.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,20.
MLA Guo, Beiyang,et al."Trend surface analysis of geographic flows".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE (2022):20.

入库方式： OAI收割

来源：地理科学与资源研究所

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