Random Forest for rice yield mapping and prediction using Sentinel-2 data with Google Earth Engine

Google Earth Engine: Planetary-scale geospatial analysis for everyone

Noel Gorelick, M. Hancher, Mike Dixon et al. · Remote Sensing of Environment · 2017 · 13.1K citations · Full text

Engineering, Geovisualization, Geocomputation +18

Crop yield prediction using machine learning: A systematic literature review

Thomas van Klompenburg, Ayalew Kassahun, Cagatay Catal · Computers and Electronics in Agriculture · 2020 · 1.6K citations · Full text

Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery

Xiang Zhou, Haimin Zheng, Xiaoqing Xu et al. · ISPRS Journal of Photogrammetry and Remote Sensing · 2017 · 604 citations

Grain Yield, Digital Imagery, Precision Agriculture +12

Smallholder maize area and yield mapping at national scales with Google Earth Engine

Zhenong Jin, George Azzari, Calum You et al. · Remote Sensing of Environment · 2019 · 356 citations

Precision Agriculture, Engineering, Land Use +12

Accurate prediction of sugarcane yield using a random forest algorithm

Yvette Everingham, Justin Sexton, Danielle Skocaj et al. · Agronomy for Sustainable Development · 2016 · 335 citations · Full text

Precision Agriculture, Sugarcane Yield, Engineering +7