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What is Detecting FAW in Maize with Sentinel-2 about?
This study investigates the detection of Fall Armyworm (FAW) infestations in maize fields during vegetative growth stages using Sentinel-2 satellite imagery and Random Forest classification. It demonstrates that spectral reflectance varies significantly among different levels of FAW infestation, achieving an accuracy between 74% and 84% in classification. The findings highlight the potential of remote sensing and machine learning techniques for effective pest monitoring and management in agriculture.
- Author
- Pavuluri Yasaswini
- Language
- EN