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Работы, на которые ссылается эта работа

Работ: 52

Работа: Comparison of PlanetScope, Sentinel-2, and landsat 8 data in soybean yield estimation within-field variability with random forest regression

  1. Random Forests

    Leo Breiman

    Статья2001Цитирований: 67
    ABI
  2. A soil-adjusted vegetation index (SAVI)

    Alfredo Huete

    Статья1988Цитирований: 23
    ABI
  3. Red and photographic infrared linear combinations for monitoring vegetation

    Compton J. Tucker

    Статья1979Цитирований: 19
    ABI
  4. Use of a green channel in remote sensing of global vegetation from EOS-MODIS

    Anatoly A. Gitelson, Yoram J. Kaufman, Mark N. Merzlyak

    Статья1996Цитирований: 10
    ABI
  5. Importance of phenological observations and predictions in agriculture

    M. Ruml, Todor Vulić

    Статья2005Цитирований: 4
    ABI
  6. High resolution wheat yield mapping using Sentinel-2

    Merryn Hunt, George Alan Blackburn, Luis Carrasco +2

    Статья2019Цитирований: 4
    ABI
  7. Time-series analysis of Sentinel-2 satellite images for sunflower yield estimation

    Khilola Amankulova, Nizom Farmonov, László Mucsi

    Статья2022Цитирований: 3
    ABI
  8. Random forests: from early developments to recent advancements

    Khaled Fawagreh, Mohamed Medhat Gaber, Eyad Elyan

    Статья2014Цитирований: 3
    ABI
  9. A comparison of random forest regression and multiple linear regression for prediction in neuroscience

    Paul F. Smith, Siva Ganesh, Ping Liu

    Статья2013Цитирований: 3
    ABI
  10. SEN2-AGRI – CROP TYPE MAPPING PILOT STUDY USING SENTINEL-2 SATELLITE IMAGERY IN INDIA

    D. Vijayasekaran

    Статья2019Цитирований: 3
    ABI
  11. Farming and Earth Observation: Sentinel-2 data to estimate within-field wheat grain yield

    Joel Segarra, J. L. Araus, Shawn C. Kefauver

    Статья2022Цитирований: 2
    ABI
  12. Global estimation of crop productivity and the impacts of global warming by GIS and EPIC integration

    Guoxin Tan, Ryosuke Shibasaki

    Статья2003Цитирований: 2
    ABI
  13. Ecosystem carbon fluxes and canopy spectral reflectance of a mountain meadow

    Damiano Gianelle, Loris Vescovo, Barbara Marcolla +2

    Статья2008Цитирований: 2
    ABI
  14. County-Level Soybean Yield Prediction Using Deep CNN-LSTM Model

    Jie Sun, Liping Di, Ziheng Sun +2

    Статья2019Цитирований: 2
    ABI
  15. Soybean yield prediction from UAV using multimodal data fusion and deep learning

    Maitiniyazi Maimaitijiang, Vasit Sagan, Paheding Sidike +3

    Статья2019Цитирований: 2
    ABI
  16. Assessing the fidelity of Landsat-based fAPAR models in two diverse sugarcane growing regions

    Sybrand Jacobus Muller, P. Sithole, A. Singels +1

    Статья2020Цитирований: 2
    ABI