Geospatial Feature Extraction

Geospatial Feature Extraction is a computational process that identifies and derives meaningful, location-based attributes from raw spatial data to support higher-level analysis, distinguished by its focus on transforming georeferenced observations into structured features representing real-world phenomena.

74

Publications

4.1K

Citations

251

Authors

116

Institutions

Publications per year

2017–2026

30

Authors

251

  1. CA
    Craig A. Knoblock

    University of Southern California, United States

    4 publications · 148 citations

    4

    h-index

  2. YC
    Yao‐Yi Chiang

    University of Southern California, United States

    4 publications · 148 citations

    4

    h-index

  3. JŠ
    Josef Šivic

    Institut national de recherche en sciences et technologies du numérique, France

    3 publications · 881 citations

    3

    h-index

  4. JU
    Johannes Uhl

    University of Colorado Boulder, United States

    3 publications · 133 citations

    3

    h-index

  5. AA
    Alexei A. Efros

    University of California, Berkeley, United States

    3 publications · 881 citations

    3

    h-index

1–5 of 251

Venues

  1. Transactions in GIS

    4 publications · 74 citations

    4

    h-index

  2. 4

    h-index

  3. Computers Environment and Urban Systems

    4 publications · 80 citations

    4

    h-index

  4. Computers & Geosciences

    CAGEO · 3 publications · 110 citations

    3

    h-index

  5. arXiv (Cornell University)

    Repository · 3 publications · 42 citations

    3

    h-index

1–5