Detecting Colocation Flow Patterns in the Geographical Interaction Data-Reference-Cited by-同舟云学术

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Detecting Colocation Flow Patterns in the Geographical Interaction Data

Published:2021-01-10 Issue:1 Volume:54 Page:84-103
ISSN:0016-7363
Container-title:Geographical Analysis
language:en
Short-container-title:Geographical Analysis

Author:

Zhang Haiping¹²³^ORCID,Zhou Xingxing¹⁴^ORCID,Tang Guoan¹²³^ORCID,Zhang Xueying¹²³^ORCID,Qin Jing⁵^ORCID,Xiong Liyang¹²³^ORCID

Affiliation:

1. School of Geographic Science Nanjing Normal University Nanjing210023China

2. Key Laboratory of Virtual Geographic Environment Ministry of Education Nanjing Normal University Nanjing210023China

3. State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province) Nanjing210023China

4. College of Information Engineering Yangzhou University Yangzhou225127China

5. School of Tourism Sciences Beijing International Studies University Beijing100024China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Earth-Surface Processes,Geography, Planning and Development

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/gean.12274

Reference75 articles.

1. Accidents on Belgium's Motorways: A Network Autocorrelation Analysis;Aarset B.;Journal of Transport Geography,1998

2. Enumeration of Maximal Clique for Mining Spatial Co‐Location Patterns;Al‐Naymat G.;2008 IEEE/ACS International Conference on Computer Systems and Applications,2008

3. Challenges for social flows

4. Quantile local spatial autocorrelation

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