Clear-cut Detection

Clear-Cut Detection is a remote sensing-based methodological framework within forest disturbance monitoring that specifically identifies areas of complete canopy removal over a defined spatial extent, distinguishing itself from partial disturbance detection by targeting abrupt, large-scale deforestation events characteristic of clear-cutting practices.

25

Publications

679

Citations

82

Authors

40

Institutions

Publications per year

2017–2026

6

Authors

82

  1. JE
    Johan E. S. Fransson

    Swedish University of Agricultural Sciences, Sweden

    3 publications · 84 citations

    3

    h-index

  2. LE
    Leif E. B. Eriksson

    Chalmers University of Technology, Sweden

    2 publications · 55 citations

    2

    h-index

  3. AP
    Anssi Pekkarinen

    Food and Agriculture Organization of the United Nations, Italy

    2 publications · 51 citations

    2

    h-index

  4. MM
    Marco Marchetti

    University of Molise, Italy

    2 publications · 72 citations

    2

    h-index

  5. GC
    Gherardo Chirici

    University of Florence, Italy

    2 publications · 72 citations

    2

    h-index

1–5 of 82

Venues

  1. Remote Sensing

    4 publications · 134 citations

    4

    h-index

  2. 2

    h-index

  3. Remote Sensing of Environment

    2 publications · 77 citations

    2

    h-index

  4. PubMed

    Repository · 2 publications · 70 citations

    2

    h-index

  5. Canadian Journal of Microbiology

    1 publications · 40 citations

    1

    h-index

1–5