Automated Generalization

Automated Generalization is a computational methodology within cartographic generalization that systematically applies algorithms and rules to transform geographic data at varying scales with minimal human intervention, distinguishing itself by its reliance on formalized processes for feature simplification, selection, displacement, and classification in map production.

125

Publications

9.3K

Citations

201

Authors

94

Institutions

Publications per year

2017–2026

26

Authors

201

  1. RW
    Robert Weibel

    University of Zurich, Switzerland

    9 publications · 350 citations

    11

    h-index

  2. DB
    Dirk Burghardt

    Technische Universität Dresden, Germany

    6 publications · 226 citations

    7

    h-index

  3. GT
    Guillaume Touya

    Institut national de l’information géographique et forestière, France

    7 publications · 249 citations

    7

    h-index

  4. CD
    Cécile Duchêne

    Institut national de l’information géographique et forestière, France

    6 publications · 248 citations

    6

    h-index

  5. JS
    Jantien Stoter

    Delft University of Technology, Netherlands

    6 publications · 277 citations

    6

    h-index

1–5 of 201

Venues

  1. 14

    h-index

  2. Cartography and Geographic Information Science

    14 publications · 574 citations

    14

    h-index

  3. The Cartographic Journal

    16 publications · 761 citations

    13

    h-index

  4. 8

    h-index

  5. ISPRS International Journal of Geo-Information

    IJGI · 6 publications · 176 citations

    7

    h-index

1–5