Semantic Change Detection
Semantic Change Detection is a change detection paradigm that identifies meaningful transformations in land cover or land use by interpreting multisensor, multitemporal imagery through semantic hierarchies and contextual knowledge, distinguishing itself from pixel- or feature-level change analysis by emphasizing human-interpretable categorical and functional transitions over mere geometric or radiometric differences.
301
Publications
22.7K
Citations
925
Authors
332
Institutions
Publications per year
2017–2026
213
301
1–5 of 301
925
13
h-index
9
h-index
9
h-index
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h-index
6
h-index
1–5 of 925
332
Wuhan University
Wuhan, China
30 h-index
140 publications
16.5K citations
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Wuhan, China
22 h-index
81 publications
8.2K citations

Chinese Academy of Sciences
Beijing, China
17 h-index
53 publications
4.1K citations
University of Chinese Academy of Sciences
Beijing, China
11 h-index
30 publications
2.5K citations

University of Trento
Trento, Italy
9 h-index
19 publications
2.6K citations

University of Helsinki
Helsinki, Finland
9 h-index
23 publications
673 citations

Nanjing University of Information Science and Technology
Nanjing, China
8 h-index
24 publications
2.9K citations

Xidian University
Xi'an, China
7 h-index
29 publications
1.5K citations
1–8 of 332
40 publications · 3.9K citations
32
h-index
18 publications · 1.4K citations
15
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Repository · 18 publications · 638 citations
14
h-index
13 publications · 2.7K citations
13
h-index
14 publications · 528 citations
13
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1–5