Automated Map Generalization

Automated Map Generalization is a computational methodology within cartographic science that systematically reduces or hierarchically simplifies geographic data complexity to produce generalized maps at varying scales, distinguished from manual generalization by its reliance on algorithmic rules, models, and procedures to autonomously perform selection, displacement, simplification, and symbolization tasks.

87

Publications

3.7K

Citations

168

Authors

73

Institutions

Publications per year

2017–2026

16

Authors

168

  1. GT
    Guillaume Touya

    Institut national de l’information géographique et forestière, France

    10 publications · 329 citations

    10

    h-index

  2. RW
    Robert Weibel

    University of Zurich, Switzerland

    9 publications · 309 citations

    9

    h-index

  3. WM
    William Mackaness

    University of Edinburgh, United Kingdom

    7 publications · 299 citations

    7

    h-index

  4. JS
    Jantien Stoter

    Delft University of Technology, Netherlands

    7 publications · 323 citations

    7

    h-index

  5. CD
    Cécile Duchêne

    Institut national de l’information géographique et forestière, France

    6 publications · 248 citations

    6

    h-index

1–5 of 168

Venues

  1. 11

    h-index

  2. Cartography and Geographic Information Science

    10 publications · 409 citations

    10

    h-index

  3. The Cartographic Journal

    7 publications · 190 citations

    7

    h-index

  4. 6

    h-index

  5. Cartography and Geographic Information Systems

    6 publications · 337 citations

    6

    h-index

1–5