Incorporating spatial association into statistical classifiers: local pattern-based prior tuning-Reference-Cited by-同舟云学术

Incorporating spatial association into statistical classifiers: local pattern-based prior tuning

Published:2020-03-10 Issue:10 Volume:34 Page:2077-2114
ISSN:1365-8816
Container-title:International Journal of Geographical Information Science
language:en
Short-container-title:International Journal of Geographical Information Science

Author:

Bai Hexiang¹,Cao Feng¹,Atkinson M. Peter²^ORCID,Chen Qian¹,Wang Jinfeng³,Ge Yong³

Affiliation:

1. School of Computer and Information Technology, Shanxi University, Taiyuan, Shanxi, China

2. Engineering Building, Lancaster University, Lancaster, UK

3. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shanxi Province, China

National Natural Science Foundation for Distinguished Young Scholars of China

Strategic Priority Research Program of the Chinese Academy of Science

Publisher

Informa UK Limited

Subject

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

Link

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2020.1737702

Reference68 articles.

1. Spatial Econometrics: Methods and Models

2. Local Indicators of Spatial Association-LISA

3. A Geostatistically Weightedk-NN Classifier for Remotely Sensed Imagery. 遥感影像的地统计加权k-NN分类器研究

4. Approximate computations for binary Markov random fields and their use in Bayesian models

5. Using rough set theory to identify villages affected by birth defects: the example of Heshun, Shanxi, China

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