Kernel-based Spatial Features
Kernel-Based Spatial Features is a spatial feature engineering method that uses kernel functions to transform and capture localized spatial dependencies by mapping geographic points into a higher-dimensional space through weighted neighborhood interactions.
35
Publications
2.4K
Citations
112
Authors
56
Institutions
Publications per year
2017–2026
16
Parents
35
Detecting spatial hot spots in landscape ecology
Trisalyn Nelson, Barry Boots · Ecography · 2008 · 220 citations
Slum mapping in polarimetric SAR data using spatial features
Michael Wurm, Hannes Taubenböck, Matthias Weigand et al. · Remote Sensing of Environment · 2017 · 113 citations
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Deakin University
Burwood, Australia
4 h-index
12 publications
303 citations
Nanjing University of Science and Technology
Nanjing, China
4 h-index
6 publications
201 citations

Nanjing University of Information Science and Technology
Nanjing, China
3 h-index
11 publications
762 citations
Sungkyunkwan University
Seoul, South Korea
2 h-index
2 publications
160 citations
University of Iceland
Reykjavik, Iceland
2 h-index
2 publications
289 citations
Jiangnan University
Wuxi, China
2 h-index
5 publications
54 citations

Cornell University
Ithaca, United States
2 h-index
3 publications
96 citations

Imperial College London
London, United Kingdom
2 h-index
4 publications
156 citations
1–8 of 56
3 publications · 91 citations
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3 publications · 113 citations
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2 publications · 32 citations
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Conference · 1 publications · 46 citations
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1 publications · 69 citations
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