Feature Selection For Spatial Data
Feature Selection for Spatial Data is a methodological process in spatial feature engineering that identifies and retains the most relevant spatial and non-spatial attributes from a dataset while accounting for spatial autocorrelation, heterogeneity, and scale, thereby distinguishing it from conventional feature selection techniques that ignore spatial dependencies.
27
Publications
2.5K
Citations
89
Authors
58
Institutions
Publications per year
2017–2026
15
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58

Ghent University
Ghent, Belgium
2 h-index
6 publications
462 citations
Philipps University of Marburg
Marburg, Germany
2 h-index
4 publications
1.9K citations
Quaid-i-Azam University
Islamabad, Pakistan
1 h-index
3 publications
63 citations
Purdue University West Lafayette
West Lafayette, United States
1 h-index
1 publications
21 citations
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
Cologne, Germany
1 h-index
1 publications
62 citations

University of Leicester
Leicester, United Kingdom
1 h-index
1 publications
35 citations
Universidad Complutense de Madrid
Madrid, Spain
1 h-index
1 publications
15 citations
King Khalid University
Abhā, Saudi Arabia
1 h-index
1 publications
21 citations
1–8 of 58
2 publications · 28 citations
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1 publications · 143 citations
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1 publications · 11 citations
1
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1 publications · 29 citations
1
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TVCG · 1 publications · 18 citations
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