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A density-based approach for detecting network-constrained clusters in spatial point events

  • Published:2018-11-05 Issue:3 Volume:33 Page:466-488
  • ISSN:1365-8816
  • Container-title:International Journal of Geographical Information Science
  • language:en
  • Short-container-title:International Journal of Geographical Information Science

Author:

Deng Min1,Yang Xuexi1,Shi Yan123ORCID,Gong Jianya23,Liu Yang1,Liu Huimin1

Affiliation:

1. Department of Geo-informatics, Central South University, Changsha, China

2. Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, China

3. State Key Laboratory of Information Engineering in Surveying, Mapping & Remote Sensing, Wuhan University, Wuhan, China

Funder

China Postdoctoral Science Foundation

National Natural Science Foundation of China

National Key Research and Development Foundation of China

Publisher

Informa UK Limited

Subject

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

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5. Kernel Density Visualization for Big Geospatial Data: Algorithms and Applications;2023 24th IEEE International Conference on Mobile Data Management (MDM);2023-07
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