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50 ta ish

Ish: Integrating the Sentinel-1, Sentinel-2 and topographic data into soybean yield modelling using machine learning

  1. Random Forests

    Leo Breiman

    Maqola200167 iqtibos
    ABI

  2. A soil-adjusted vegetation index (SAVI)

    Alfredo Huete

    Maqola198823 iqtibos
    ABI

  3. Red and photographic infrared linear combinations for monitoring vegetation

    Compton J. Tucker

    Maqola197919 iqtibos
    ABI

  4. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features

    Stuart K. McFeeters

    Maqola199612 iqtibos
    ABI

  5. Use of a green channel in remote sensing of global vegetation from EOS-MODIS

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

    Maqola199610 iqtibos
    ABI

  6. Sunflower crop yield prediction by advanced statistical modeling using satellite-derived vegetation indices and crop phenology

    Khilola Amankulova, Nizom Farmonov, Uzbekkhon Mukhtorov +1

    MaqolaRemote Sensing in AgricultureGeocarto International20237 iqtibos
    ABI

  7. Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques

    Sudhanshu Panda, Daniel P. Ames, Suranjan Panigrahi

    Maqola20105 iqtibos
    ABI

  8. Combining PlanetScope and Sentinel-2 images with environmental data for improved wheat yield estimation

    Nizom Farmonov, Khilola Amankulova, József Szatmári +4

    MaqolaRemote Sensing in AgricultureInternational Journal of Digital Earth20233 iqtibos
    ABI

  9. A five‐year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States

    Yingxin Gu, Jesslyn F. Brown, J. P. Verdin +1

    Maqola20073 iqtibos
    ABI

  10. Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

    Yingxin Gu, Eric Hunt, Brian Wardlow +3

    Maqola20083 iqtibos
    ABI

  11. Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics

    Douglas K. Bolton, M. A. Friedl

    Maqola20132 iqtibos
    ABI

  12. The Control of Errors in Momentary Yield Data from Combine Harvesters

    Lars Thylén, Donal Patrick Murphy

    Maqola19962 iqtibos
    ABI

  13. Predicting Wheat Yield at the Field Scale by Combining High-Resolution Sentinel-2 Satellite Imagery and Crop Modelling

    Yan Zhao, Andries Potgieter, Miao Zhang +2

    Maqola20202 iqtibos
    ABI

  14. An analysis of cropland mask choice and ancillary data for annual corn yield forecasting using MODIS data

    Yang Shao, James B. Campbell, Gregory N. Taff +1

    Maqola20152 iqtibos
    ABI

  15. Ecosystem carbon fluxes and canopy spectral reflectance of a mountain meadow

    Damiano Gianelle, Loris Vescovo, Barbara Marcolla +2

    Maqola20082 iqtibos
    ABI

  16. Remote Sensing for Precision Agriculture: Sentinel-2 Improved Features and Applications

    Joel Segarra, Ma. Luisa Buchaillot, J. L. Araus +1

    Maqola20202 iqtibos
    ABI

  17. Soya Yield Prediction on a Within-Field Scale Using Machine Learning Models Trained on Sentinel-2 and Soil Data

    Branislav Pejak, Predrag Lugonja, Aleksandar Antić +7

    Maqola20222 iqtibos
    ABI

  18. Random decision forests

    Tin Kam Ho

    Maqola20022 iqtibos
    ABI

  19. Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications

    Amanda Veloso, Stéphane Mermoz, Alexandre Bouvet +4

    Maqola20172 iqtibos
    ABI

  20. Crop Yield Prediction using Machine Learning Techniques

    Ramesh Medar, Vijay S. Rajpurohit, Shweta Shweta

    Maqola20192 iqtibos
    ABI

  21. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  22. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  23. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  24. Sarlavhasiz

    Boshqa1 iqtibos
    ABI

  25. Sarlavhasiz

    Boshqa1 iqtibos
    ABI