Spatial Machine Learning
Spatial Machine Learning is a computational methodology that extends conventional machine learning approaches to explicitly model and analyze spatial dependencies, heterogeneities, and patterns inherent in geographically referenced data.
333
Publications
18.4K
Citations
1.2K
Authors
540
Institutions
Publications per year
2017–2026
261
333
1–5 of 333
1.2K
9
h-index
6
h-index
4
h-index
4
h-index
4
h-index
1–5 of 1.2K
540

Chinese Academy of Sciences
Beijing, China
12 h-index
37 publications
1.3K citations

Zhejiang University
Hangzhou, China
11 h-index
32 publications
3.4K citations
Wuhan University
Wuhan, China
10 h-index
28 publications
623 citations

University of Twente
Enschede, The Netherlands
9 h-index
22 publications
921 citations
University of Chinese Academy of Sciences
Beijing, China
9 h-index
16 publications
440 citations

University of Minnesota
Minneapolis, United States
7 h-index
22 publications
671 citations
University of Alabama
Tuscaloosa, United States
6 h-index
11 publications
332 citations
University of Münster
Münster, Germany
6 h-index
14 publications
1.2K citations
1–8 of 540
13 publications · 682 citations
13
h-index
IJGI · 10 publications · 378 citations
10
h-index
8 publications · 400 citations
8
h-index
8 publications · 209 citations
8
h-index
7 publications · 744 citations
7
h-index
1–5