Evaluating Machine Learning Algorithms for Onion Mapping in Nueva Ecija, Philippines using Sentinel-2 Imagery
Authors: Reymar R. Diwa & Ariel C. Blanco
Onion is a high-value crop in the Philippines, yet its production is threatened by fluctuating climate, pest outbreaks, and limited monitoring. This study aims to develop a remote sensing-based approach to map onion fields in Nueva Ecija using Sentinel-2 imagery and machine learning, supporting precision agriculture and crop management initiatives.
This study is part of the Philippine Geomatics Symposium (PhilGEOS) on 24-25 November 2025 at the GT Toyota Asian Center Auditorium, University of the Philippines Diliman in Quezon City.
More information here.