Terrain Data Fusion
Terrain Data Fusion is a methodological framework that integrates heterogeneous terrain datasets from multiple sources into a unified, coherent representation by resolving inconsistencies in spatial resolution, geometry, and semantics to enhance modeling accuracy and completeness.
27
Publications
744
Citations
97
Authors
54
Institutions
Publications per year
2017–2026
11
Parents
27
1–5 of 27
97
2
h-index
2
h-index
2
h-index
1
h-index
1
h-index
1–5 of 97
54

The University of Sydney
Sydney, Australia
2 h-index
8 publications
160 citations

University of Calgary
Calgary, Canada
2 h-index
3 publications
87 citations
Australian Centre for Robotic Vision
Brisbane, Australia
2 h-index
8 publications
160 citations

University of Wrocław
Wroclaw, Poland
1 h-index
1 publications
40 citations

Shanghai Jiao Tong University
Shanghai, China
1 h-index
2 publications
66 citations
Friedrich-Alexander-Universität Erlangen-Nürnberg
Erlangen, Germany
1 h-index
1 publications
21 citations
Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
Cologne, Germany
1 h-index
1 publications
36 citations

Makerere University
Kampala, Uganda
1 h-index
1 publications
29 citations
1–8 of 54
2 publications · 63 citations
2
h-index
1 publications · 28 citations
1
h-index
1 publications · 14 citations
1
h-index
1 publications · 40 citations
1
h-index
1 publications · 12 citations
1
h-index
1–5