Spatial data mining is a research field and methodological approach concerned with the discovery of interesting, useful, and non-trivial patterns and knowledge from large spatial datasets. It addresses the unique characteristics of spatial data, such as spatial autocorrelation and spatial heterogeneity, to uncover relationships and anomalies that are spatially referenced, proving significant for analyzing geographical, environmental, and urban phenomena.
240
Publications
15.3K
Citations
544
Authors
241
Institutions
Publications per year
2017–2026
38
Publications
240
Fosca Giannotti, Mirco Nanni, Fabio Pinelli et al. · 2007 · 1K citations
Location-acquisition Technologies, Trajectory Patterns, Trajectory Pattern Mining +15
DBSCAN: Past, present and future
2014 · 569 citations
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Authors
544
Leading researchers in Spatial Data Mining. Counts cover only their work on this concept, not their overall record.
| Publications | Citations | H-Index | |
|---|---|---|---|
LW Yunnan University | 9 | 231 | 9 |
SW Beijing Institute of Technology | 7 | 198 | 7 |
SS University of Minnesota | 5 | 529 | 5 |
CF University of Houston | 5 | 104 | 5 |
WP North Dakota State University | 5 | 183 | 5 |
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Institutions
241
Leading universities and research organizations in Spatial Data Mining. Counts cover only their work on this concept, not their overall record.
| Publications | Citations | H-Index | |
|---|---|---|---|
 Wuhan, China | 25 | 722 | 12 |
 Burnaby, Canada | 19 | 2.8K | 9 |
 Minneapolis, United States | 19 | 2.2K | 7 |
 Kunming, China | 21 | 495 | 7 |
 Beijing, China | 8 | 247 | 6 |
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Venues
Leading journals and conferences in Spatial Data Mining. Counts cover only their publications on this concept, not their overall record.
| Publications | Citations | H-Index | |
|---|---|---|---|
8 | 535 | 8 | |
7 | 1.7K | 7 | |
6 | 308 | 6 | |
5 | 161 | 5 | |
4 | 230 | 4 |
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