Storm Damage Detection

Storm Damage Detection is a methodological framework within forest disturbance detection that specifically identifies and quantifies tree damage caused by severe weather events, particularly storms, using remote sensing data and temporal change analysis to distinguish storm-induced impacts from other types of forest disturbances.

72

Publications

3K

Citations

265

Authors

117

Institutions

Publications per year

2017–2026

20

Authors

265

  1. KB
    Kristina Blennow

    Swedish University of Agricultural Sciences, Sweden

    3 publications · 152 citations

    3

    h-index

  2. UK
    Ulrich Kohnle

    University of Freiburg, Germany

    2 publications · 84 citations

    2

    h-index

  3. DS
    Dirk Schindler

    University of Freiburg, Germany

    2 publications · 48 citations

    2

    h-index

  4. MS
    Mart‐Jan Schelhaas

    Wageningen University & Research, Netherlands

    2 publications · 62 citations

    2

    h-index

  5. FW
    Fabian Walter

    Max Planck Institute for Astronomy, Germany

    2 publications · 70 citations

    2

    h-index

1–5 of 265

Venues

  1. Remote Sensing

    5 publications · 145 citations

    5

    h-index

  2. Forest Ecology and Management

    4 publications · 388 citations

    4

    h-index

  3. Remote Sensing of Environment

    4 publications · 192 citations

    4

    h-index

  4. Annals of Forest Science

    3 publications · 163 citations

    3

    h-index

  5. Bulletin of the American Meteorological Society

    BAMS · 3 publications · 122 citations

    3

    h-index

1–5