Investigating climate-phenology relationships among the most common Italian forest species using Sentinel-2-derived vegetation phenology and productivity products
Elia Vangi, Giovanni D’Amico, Vincenzo Saponaro, Mattia Niccoli, Gioele Tiberi, Saverio Francini, Costanza Borghi, Alessio Collalti, Francesco Parisi, Gherardo Chirici
This study examines climate-phenology relationships in Italian forest species using remote sensing and machine learning, finding growing season lengthening and species-specific responses to climate factors.
Agricultural and Forest Meteorology · Sep 29, 2026Peer-reviewedEcology