Generalization Quality Assessment
Generalization Quality Assessment is a systematic evaluation framework within cartographic generalization that quantifies the fidelity and effectiveness of generalized map representations relative to their source data and intended purpose, distinguishing itself by its focus on measuring spatial accuracy, semantic consistency, and visual quality across transformation processes.
22
Publications
819
Citations
72
Authors
41
Institutions
Publications per year
2017–2026
8
Parents
22
The Geometric Properties of Numerical Generalization
Robert McMaster · Geographical Analysis · 1987 · 52 citations · Full text
1–5 of 22
72
Institut national de l’information géographique et forestière, France
4 publications · 158 citations
4
h-index
3
h-index
1
h-index
1
h-index
Institut national de l’information géographique et forestière, France
1 publications · 27 citations
1
h-index
1–5 of 72
41
Institut national de l’information géographique et forestière
Saint-Mandé, France
4 h-index
11 publications
365 citations
University of Zurich
Zurich, Switzerland
2 h-index
3 publications
312 citations

Delft University of Technology
Delft, The Netherlands
2 h-index
2 publications
124 citations
Technical University of Denmark
Kongens Lyngby, Denmark
2 h-index
5 publications
76 citations
Shanghai Artificial Intelligence Laboratory
Shanghai, China
1 h-index
4 publications
92 citations

Sun Yat-sen University
Guangzhou, China
1 h-index
1 publications
37 citations
Institute for Theoretical and Experimental Physics
Moscow, Russia
1 h-index
1 publications
146 citations
Berkeley College
New York, United States
1 h-index
1 publications
10 citations
1–8 of 41
3 publications · 89 citations
3
h-index
2 publications · 70 citations
2
h-index
1 publications · 11 citations
1
h-index
JOSIS · 1 publications · 12 citations
1
h-index
1 publications · 52 citations
1
h-index
1–5