Object-based Forest Analysis

Object-Based Forest Analysis is a remote sensing interpretation method that segments multispectral imagery into meaningful image objects based on spectral, spatial, and contextual characteristics, distinguishing itself from pixel-based approaches by enabling hierarchical, object-level classification and measurement of forest structures.

186

Publications

10.5K

Citations

708

Authors

297

Institutions

Publications per year

2017–2026

96

Variants

Object-based Forest Image Analysis

Authors

708

  1. SE
    Steven E. Franklin

    University of Calgary, Canada

    4 publications · 413 citations

    4

    h-index

  2. HZ
    Helmi Zulhaidi Mohd Shafri

    Universiti Putra Malaysia, Malaysia

    3 publications · 140 citations

    3

    h-index

  3. GC
    Gang Chen

    University of North Carolina at Charlotte, United States

    3 publications · 153 citations

    3

    h-index

  4. MA
    Michael A. Wulder

    Canadian Forest Service, Canada

    3 publications · 305 citations

    3

    h-index

  5. GJ
    Geoffrey J. Hay

    University of Calgary, Canada

    3 publications · 273 citations

    3

    h-index

1–5 of 708

Venues

  1. Remote Sensing

    27 publications · 1.5K citations

    20

    h-index

  2. Forests

    11 publications · 446 citations

    11

    h-index

  3. Photogrammetric Engineering & Remote Sensing

    10 publications · 764 citations

    10

    h-index

  4. Remote Sensing of Environment

    10 publications · 1.9K citations

    10

    h-index

  5. 9

    h-index

1–5