Topological Data Structures
Topological Data Structures is a data organization framework in geographic information science that explicitly represents the spatial relationships among vector geometric entities—such as points, lines, and polygons—by encoding adjacency, connectivity, and containment to ensure logical consistency and support advanced spatial analysis.
554
Publications
28.1K
Citations
1.5K
Authors
689
Institutions
Publications per year
2017–2026
288
Parents
554
Gunnar Carlsson · Bulletin of the American Mathematical Society · 2009 · 2.3K citations · Full text
Map-matching for low-sampling-rate GPS trajectories
Yin Lou, Chengyang Zhang, Yu Zheng et al. · 2009 · 784 citations
Computing, Geoinformatics, Geographic Information Systems +14
A roadmap for the computation of persistent homology
Nina Otter, Mason A. Porter, Ulrike Tillmann et al. · EPJ Data Science · 2017 · 761 citations · Full text
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Chinese Academy of Sciences
Beijing, China
14 h-index
44 publications
1.8K citations
Stanford University
Stanford, United States
13 h-index
34 publications
5.2K citations
University of Oxford
Oxford, United Kingdom
10 h-index
29 publications
4.7K citations
Columbia University
New York, United States
9 h-index
24 publications
809 citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
8 h-index
16 publications
1.3K citations
University of Utah
Salt Lake City, United States
8 h-index
25 publications
833 citations

Delft University of Technology
Delft, The Netherlands
8 h-index
18 publications
396 citations

Tanta University
Tanta, Egypt
8 h-index
12 publications
304 citations
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Repository · 30 publications · 719 citations
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TVCG · 10 publications · 452 citations
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10 publications · 355 citations
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8 publications · 342 citations
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7 publications · 408 citations
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