Spatial Data Mining

Spatial Data Mining is a subfield of data mining that specifically focuses on discovering previously unknown, spatially relevant patterns, relationships, or knowledge from large spatial datasets by incorporating spatial topology, proximity, and dependency as fundamental differentiating constraints.

2.1K

Publications

137.6K

Citations

5.3K

Authors

1.6K

Institutions

Publications per year

2017–2026

753

Authors

5.3K

  1. SS
    Shashi Shekhar

    University of Minnesota, United States

    31 publications · 1.6K citations

    21

    h-index

  2. LW
    Lizhen Wang

    Yunnan University, China

    27 publications · 987 citations

    19

    h-index

  3. IL
    Ickjai Lee

    James Cook University, Australia

    23 publications · 803 citations

    17

    h-index

  4. MD
    Min Deng

    Central South University, China

    20 publications · 886 citations

    16

    h-index

  5. YZ
    Yu Zheng

    Microsoft Research Asia (China), China

    15 publications · 3.7K citations

    15

    h-index

1–5 of 5.3K

Venues

  1. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 48 publications · 5.9K citations

    33

    h-index

  2. 32

    h-index

  3. Expert Systems with Applications

    35 publications · 1.5K citations

    22

    h-index

  4. ISPRS International Journal of Geo-Information

    IJGI · 43 publications · 1.5K citations

    21

    h-index

  5. Information Sciences

    27 publications · 1.9K citations

    20

    h-index

1–5