Remote Sensing-based Estimation

Remote Sensing-Based Estimation is a methodological approach that belongs to the genus of environmental monitoring techniques and is differentiated by its reliance on satellite or aerial sensor data to infer biophysical parameters, specifically Leaf Area Index, through empirical, physical, or machine learning models.

761

Publications

54.4K

Citations

3.1K

Authors

1K

Institutions

Publications per year

2017–2026

391

Authors

3.1K

  1. AA
    Anatoly A. Gitelson

    University of Nebraska–Lincoln, United States

    27 publications · 9.7K citations

    26

    h-index

  2. DC
    Donald C. Rundquist

    University of Nebraska–Lincoln, United States

    13 publications · 5.1K citations

    13

    h-index

  3. YP
    Yi Peng

    Wuhan University, China

    13 publications · 1.8K citations

    13

    h-index

  4. KS
    Kaishan Song

    Northeast Institute of Geography and Agroecology, China

    11 publications · 626 citations

    11

    h-index

  5. SL
    Shunlin Liang

    University of Maryland, College Park, United States

    9 publications · 1.7K citations

    9

    h-index

1–5 of 3.1K

Venues

  1. Remote Sensing

    124 publications · 5.7K citations

    47

    h-index

  2. Remote Sensing of Environment

    67 publications · 11.9K citations

    47

    h-index

  3. International Journal of Remote Sensing

    40 publications · 2.5K citations

    26

    h-index

  4. 21

    h-index

  5. Agricultural and Forest Meteorology

    15 publications · 1.6K citations

    15

    h-index

1–5