Crop loss identification at field parcel scale using satellite remote sensing and machine learning
Santosh Hiremath, Samantha Wittke, Taru Palosuo, Jere Kaivosoja, Fulu Tao, Maximilian Proll, Eetu Puttonen, Pirjo Peltonen‐Sainio, Pekka Marttinen, Hiroshi Mamitsuka
This study uses satellite imagery and machine learning to classify crop loss at field parcel scale, achieving an average AUC of 0.688 using random forest.
PLoS ONE · Dec 16, 2021Peer-reviewedBioinformatics