Cloud Contamination Detection

Cloud Contamination Detection is a methodological framework in remote sensing that identifies and filters cloud-affected pixels in satellite imagery to ensure accurate surface temperature retrieval by distinguishing cloudy from clear-sky conditions based on spectral, temporal, or spatial anomalies.

167

Publications

10K

Citations

635

Authors

264

Institutions

Publications per year

2017–2026

57

Authors

635

  1. GF
    G. Fedosejevs

    University of Arizona, United States

    3 publications · 148 citations

    3

    h-index

  2. JS
    Jeffrey S. Reid

    United States Naval Research Laboratory, United States

    3 publications · 308 citations

    3

    h-index

  3. BW
    Brian White

    Cranfield University, United Kingdom

    3 publications · 132 citations

    3

    h-index

  4. YL
    Ying Li

    Northwestern Polytechnical University, China

    3 publications · 175 citations

    3

    h-index

  5. JS
    Jiancheng Shi

    State Key Laboratory of Remote Sensing Science, China

    3 publications · 162 citations

    3

    h-index

1–5 of 635

Venues

  1. 20

    h-index

  2. International Journal of Remote Sensing

    19 publications · 1.1K citations

    16

    h-index

  3. Remote Sensing

    14 publications · 630 citations

    13

    h-index

  4. IEEE Geoscience and Remote Sensing Letters

    GRSL · 7 publications · 460 citations

    7

    h-index

  5. Atmospheric measurement techniques

    7 publications · 354 citations

    7

    h-index

1–5