Image-based Biomass Estimation

Image-Based Biomass Estimation is a computational method that belongs to the class of remote sensing techniques and is distinguished by its use of optical, multispectral, or hyperspectral imagery to quantitatively predict forage biomass through image-derived vegetation indices, texture features, or machine learning models.

310

Publications

19.5K

Citations

1.4K

Authors

527

Institutions

Publications per year

2017–2026

184

Authors

1.4K

  1. OM
    Onisimo Mutanga

    University of KwaZulu-Natal, South Africa

    7 publications · 1.3K citations

    7

    h-index

  2. GY
    Guijun Yang

    National Engineering Research Center for Information Technology in Agriculture, China

    7 publications · 841 citations

    7

    h-index

  3. HF
    Haikuan Feng

    National Engineering Research Center for Information Technology in Agriculture, China

    7 publications · 947 citations

    7

    h-index

  4. JY
    Jibo Yue

    National Engineering Research Center for Information Technology in Agriculture, China

    6 publications · 813 citations

    6

    h-index

  5. XJ
    Xiuliang Jin

    Institute of Crop Sciences, China

    5 publications · 343 citations

    5

    h-index

1–5 of 1.4K

Venues

  1. Remote Sensing

    34 publications · 1.8K citations

    24

    h-index

  2. Remote Sensing of Environment

    19 publications · 1.8K citations

    18

    h-index

  3. International Journal of Remote Sensing

    17 publications · 2.5K citations

    15

    h-index

  4. Computers and Electronics in Agriculture

    15 publications · 873 citations

    15

    h-index

  5. 12

    h-index

1–5