Single-image Height Estimation

Single-Image Height Estimation is a methodological framework within remote sensing and computer vision that enables the prediction of tree height from a single two-dimensional image by leveraging geometric priors, scene constraints, or deep learning models, distinguishing it from multi-view or multi-sensor height estimation approaches.

24

Publications

1.2K

Citations

65

Authors

42

Institutions

Publications per year

2017–2026

17

Authors

65

  1. XX
    Xiao Xiang Zhu

    Technical University of Munich, Germany

    3 publications · 191 citations

    3

    h-index

  2. HA
    Hossein Arefi

    University of Tehran, Iran

    3 publications · 165 citations

    3

    h-index

  3. LM
    Lichao Mou

    Technical University of Munich, Germany

    3 publications · 191 citations

    3

    h-index

  4. HA
    Hamed Amini Amirkolaee

    University of Tehran, Iran

    2 publications · 152 citations

    2

    h-index

  5. YS
    Yao Sun

    Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), Germany

    2 publications · 90 citations

    2

    h-index

1–5 of 65

Venues

  1. 5

    h-index

  2. IEEE Geoscience and Remote Sensing Letters

    GRSL · 3 publications · 207 citations

    3

    h-index

  3. Remote Sensing

    3 publications · 148 citations

    3

    h-index

  4. Computer Vision and Image Understanding

    CVIU · 2 publications · 47 citations

    2

    h-index

  5. arXiv (Cornell University)

    Repository · 1 publications · 101 citations

    1

    h-index

1–5