Model-assisted Inventory

Model-Assisted Inventory is an inventory estimation framework within forest inventory design that belongs to the class of model-based inference methods and is distinguished by its integration of a statistical or machine learning model to assist in improving the precision of design-unbiased estimators through the use of auxiliary data.

9

Publications

389

Citations

41

Authors

22

Institutions

Publications per year

2017–2026

5

Authors

41

  1. GG
    Gretchen G. Moisen

    Rocky Mountain Research Station, United States

    2 publications · 72 citations

    2

    h-index

  2. EN
    Erik Næsset

    Norwegian University of Life Sciences, Norway

    1 publications · 48 citations

    1

    h-index

  3. CM
    Christoph Müller

    Potsdam Institute for Climate Impact Research, Germany

    1 publications · 130 citations

    1

    h-index

  4. JH
    Jameel Hasan

    West Virginia University at Parkersburg, United States

    1 publications · 12 citations

    1

    h-index

  5. AK
    Annika Kangas

    University of Helsinki, Finland

    1 publications · 48 citations

    1

    h-index

1–5 of 41

Venues

  1. Forests

    1 publications · 43 citations

    1

    h-index

  2. Omega

    1 publications · 12 citations

    1

    h-index

  3. Canadian Journal of Remote Sensing

    1 publications · 61 citations

    1

    h-index

  4. Medicine

    1 publications · 20 citations

    1

    h-index

  5. Frontiers in Forests and Global Change

    1 publications · 29 citations

    1

    h-index

1–5