A Self-Adjusting Approach to Identify Hotspots-Reference-Cited by-同舟云学术

A Self-Adjusting Approach to Identify Hotspots

Published:2017 Issue:2 Volume:5 Page:104-112
ISSN:2187-3666
Container-title:International Review for Spatial Planning and Sustainable Development
language:en
Short-container-title:IRSPSD International

Author:

Han Haoying¹,Shu Xianfan²

Affiliation:

1. Department of Regional and Urban Planning, College of Civil Engineering and Architecture, Zhejiang University

2. Department of Land Management, School of Public Affairs ,Zhejiang University

Publisher

International Community of Spatial Planning and Sustainable Development

Subject

Management, Monitoring, Policy and Law,Urban Studies,Geography, Planning and Development

Link

https://www.jstage.jst.go.jp/article/irspsd/5/2/5_104/_pdf

Reference23 articles.

1. Anderson, T. (2007). "Comparison of Spatial Methods for Measuring Road Accident ‘Hotspots': A Case Study of London". Journal of Maps, 3(1), 55-63.

2. Anselin, L. (1995). "Local Indicators of Spatial Association—Lisa". Geographical analysis, 27(2), 93-115.

3. Cai, Y., Xie, K., & Ma, X. (2004). "An Improved Dbscan Algorithm Which Is Insensitive to Input Parameters". Acta Scicentiarum Naturalum Universitis Pekinesis, 40(3), 480-486.

4. Chakraborty, S., & Nagwani, N. K. (2014). "Analysis and Study of Incremental Dbscan Clustering Algorithm". arXiv preprint arXiv:1406.4754.

5. Davies, D. L., & Bouldin, D. W. (1979). "A Cluster Separation Measure". IEEE Transactions on Pattern Analysis and Machine Intelligence, (2), 224-227.

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