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84 ta ish

Ish: A Novel Fusion Method for Soybean Yield Prediction Using Sentinel-2 and PlanetScope Imagery

  1. Random Forests

    Leo Breiman

    MaqolaOchiq kirish2001117 iqtibos
    ABI

  2. A soil-adjusted vegetation index (SAVI)

    Alfredo Huete

    Maqola198829 iqtibos
    ABI

  3. Red and photographic infrared linear combinations for monitoring vegetation

    Compton J. Tucker

    MaqolaOchiq kirish197925 iqtibos
    ABI

  4. Big Data in Smart Farming – A review

    J. Wolfert, Lan Ge, C.N. Verdouw +1

    Sharh maqolaOchiq kirish201721 iqtibos
    ABI

  5. Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications

    Jinru Xue, Baofeng Su

    Sharh maqolaOchiq kirish201710 iqtibos
    ABI

  6. 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

  7. Sarlavhasiz

    Boshqa7 iqtibos
    ABI

  8. A survey of deep neural network architectures and their applications

    Weibo Liu, Zidong Wang, Xiaohui Liu +3

    Maqola20166 iqtibos
    ABI

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

    Nizom Farmonov, Khilola Amankulova, József Szatmári +4

    MaqolaOchiq kirishRemote Sensing in AgricultureInternational Journal of Digital Earth20235 iqtibos
    ABI

  10. Sarlavhasiz

    Boshqa5 iqtibos
    ABI

  11. Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans

    Thomas J. Jackson, Daoyi Chen, Michael H. Cosh +5

    Maqola20035 iqtibos
    ABI

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

    Sudhanshu Panda, Daniel P. Ames, Suranjan Panigrahi

    MaqolaOchiq kirish20105 iqtibos
    ABI

  13. Crop Yield Prediction Using Deep Neural Networks

    Saeed Khaki, Lizhi Wang

    MaqolaOchiq kirish20195 iqtibos
    ABI

  14. Support vector regression

    Fan Zhang, Lauren J. O’Donnell

    Bob20195 iqtibos
    ABI

  15. Importance of phenological observations and predictions in agriculture

    M. Ruml, Todor Vulić

    MaqolaOchiq kirish20054 iqtibos
    ABI

  16. Crop yield prediction using machine learning: A systematic literature review

    Thomas van Klompenburg, Ayalew Kassahun, Cagatay Catal

    MaqolaOchiq kirish20204 iqtibos
    ABI

  17. Spatial patterns of seed dispersal, their determinants and consequences for recruitment

    Ran Nathan, Helene C. Muller‐Landau

    Maqola20003 iqtibos
    ABI

  18. Time-series analysis of Sentinel-2 satellite images for sunflower yield estimation

    Khilola Amankulova, Nizom Farmonov, László Mucsi

    MaqolaOchiq kirish20223 iqtibos
    ABI

  19. A comparison of random forest regression and multiple linear regression for prediction in neuroscience

    Paul F. Smith, Siva Ganesh, Ping Liu

    Maqola20133 iqtibos
    ABI

  20. SEN2-AGRI – CROP TYPE MAPPING PILOT STUDY USING SENTINEL-2 SATELLITE IMAGERY IN INDIA

    D. Vijayasekaran

    MaqolaOchiq kirish20193 iqtibos
    ABI

  21. Sarlavhasiz

    Boshqa3 iqtibos
    ABI

  22. Use of Remote‐Sensing Imagery to Estimate Corn Grain Yield

    John F. Shanahan, James S. Schepers, D. D. Francis +5

    Maqola20012 iqtibos
    ABI

  23. Studying the Feasibility of Assimilating Sentinel-2 and PlanetScope Imagery into the SAFY Crop Model to Predict Within-Field Wheat Yield

    V. S. Manivasagam, Yuval Sadeh, Gregoriy Kaplan +2

    MaqolaOchiq kirish20212 iqtibos
    ABI

  24. Global estimation of crop productivity and the impacts of global warming by GIS and EPIC integration

    Guoxin Tan, Ryosuke Shibasaki

    Maqola20032 iqtibos
    ABI

  25. Post-processing methods to eliminate erroneous grain yield measurements: review and directions for future development

    Greg Lyle, Brett A. Bryan, Bertram Ostendorf

    Maqola20132 iqtibos
    ABI