Assessing field experts yield maize estimations with satellite information derived from Sentinel-2 - Carcedo, Diego; Pons, Diego Hernan; Alonso, Cesar; Fiant, Silvina; Scavuzzo, Carlos Marcelo; Marinelli, María Victoria (Universidad Técnica Federico Santa María, Chile, 2024)
Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Earth observation data from space can contribute to agricultural monitoring, including crop yield assessment and forecasting. In this study, we present a multiple regression site-specific crop yield model based on the Normalized Difference Vegetation Index (NDVI) extracted from Sentinel – 2 data at 10 meters resolution calibrated with yield corn estimations reported by local experts at a field level.