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

Authors

925

  1. LZ
    Liangpei Zhang

    Wuhan University, China

    13 publications · 1.7K citations

    13

    h-index

  2. YZ
    Yanfei Zhong

    Wuhan University, China

    9 publications · 1.1K citations

    9

    h-index

  3. ZZ
    Zhuo Zheng

    Wuhan University, China

    9 publications · 1.1K citations

    9

    h-index

  4. AM
    Ailong Ma

    Wuhan University, China

    8 publications · 1.1K citations

    8

    h-index

  5. LB
    Lorenzo Bruzzone

    University of Trento, Italy

    6 publications · 997 citations

    6

    h-index

1–5 of 925

Venues

  1. 32

    h-index

  2. Remote Sensing

    18 publications · 1.4K citations

    15

    h-index

  3. arXiv (Cornell University)

    Repository · 18 publications · 638 citations

    14

    h-index

  4. 13

    h-index

  5. 13

    h-index

1–5