Geospatial Feature Engineering

Geospatial Feature Engineering is a geospatial data preprocessing methodology that involves the creation, transformation, and selection of spatial and non-spatial attributes from raw georeferenced data to enhance the performance and interpretability of machine learning models in geographical context analysis.

171

Publications

9.1K

Citations

676

Authors

325

Institutions

Publications per year

2017–2026

109

Authors

676

  1. SW
    Scott Workman

    University of Kentucky, United States

    4 publications · 533 citations

    4

    h-index

  2. NJ
    Nathan Jacobs

    University of Kentucky, United States

    4 publications · 533 citations

    4

    h-index

  3. RS
    Richard Souvenir

    University of North Carolina at Charlotte, United States

    3 publications · 402 citations

    3

    h-index

  4. WC
    Wei Chen

    Xi'an University of Science and Technology, China

    3 publications · 165 citations

    3

    h-index

  5. HR
    Hamid Reza Pourghasemi

    Shiraz University, Iran

    3 publications · 1.3K citations

    3

    h-index

1–5 of 676

Venues

  1. Remote Sensing

    7 publications · 317 citations

    7

    h-index

  2. 5

    h-index

  3. Computers Environment and Urban Systems

    5 publications · 181 citations

    5

    h-index

  4. Transactions in GIS

    4 publications · 232 citations

    4

    h-index

  5. 4

    h-index

1–5