Spatial Data Quality Assessment
Spatial Data Quality Assessment is a systematic evaluation process that belongs to the category of geospatial data validation methods, differing from its peers by specifically quantifying the accuracy, completeness, consistency, and reliability of spatial data within defined metric frameworks to support informed decision-making in applications such as geospatial uncertainty modeling and mine lease surveying.
187
Publications
11.3K
Citations
586
Authors
243
Institutions
Publications per year
2017–2026
64
187
A new map of permafrost distribution on the Tibetan Plateau
Defu Zou, Lin Zhao, Yu Sheng et al. · The cryosphere · 2017 · 869 citations · Full text
Quality Assessment of the French OpenStreetMap Dataset
Jean‐François Girres, Guillaume Touya · Transactions in GIS · 2010 · 672 citations · Full text
Computing, Geography, Geoinformatics +17
1–5 of 187
586
6
h-index
6
h-index
4
h-index
4
h-index
3
h-index
1–5 of 586
243
Heidelberg University
Heidelberg, Germany
7 h-index
18 publications
2.4K citations
Politecnico di Milano
Milan, Italy
6 h-index
13 publications
951 citations
China University of Geosciences
Wuhan, China
5 h-index
11 publications
458 citations

Université Laval
Québec, Canada
5 h-index
13 publications
861 citations
Wageningen University & Research
Wageningen, The Netherlands
4 h-index
9 publications
941 citations
Wuhan University
Wuhan, China
4 h-index
11 publications
740 citations

The University of Sydney
Sydney, Australia
4 h-index
8 publications
599 citations
University of Nebraska–Lincoln
Lincoln, United States
3 h-index
10 publications
906 citations
1–8 of 243
19 publications · 899 citations
15
h-index
11 publications · 1.6K citations
11
h-index
IJGI · 10 publications · 756 citations
10
h-index
8 publications · 243 citations
8
h-index
CAGEO · 4 publications · 104 citations
4
h-index
1–5