An adaptive detection of multilevel co-location patterns based on natural neighborhoods-Reference-Cited by-同舟云学术

An adaptive detection of multilevel co-location patterns based on natural neighborhoods

Published:2020-06-16 Issue:3 Volume:35 Page:556-581
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Liu Qiliang¹²,Liu Wenkai²,Deng Min²,Cai Jiannan²^ORCID,Liu Yaolin³

Affiliation:

1. Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha, Hunan, P.R. China

2. Department of Geo-informatics, Central South University, Changsha, Hunan, P.R. China

3. School of Resource and Environmental Science, Wuhan University, Wuhan, P.R. China

Funder

National Natural Science Foundation of China

National Key Research and Development Foundation of China

Natural Science Foundation of Hunan Province

The Innovation-Driven Project of Central South University

Publisher

Informa UK Limited

Subject

Library and Information Sciences,Geography, Planning and Development,Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2020.1775235

Reference46 articles.

1. Mining Statistically Significant Co-location and Segregation Patterns

2. FARICS: a method of mining spatial association rules and collocations using clustering and Delaunay diagrams

3. The Ecology of Mutualism

4. Adaptive detection of statistically significant regional spatial co-location patterns

5. Nonparametric Significance Test for Discovery of Network-Constrained Spatial Co-Location Patterns

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