Google Earth Engine: Evaluation of the scopes andlimitations for the resolve of agricultural problems in SantaLucía, Barva, Heredia - Bastos Gutiérrez, Sara (2025)
Google Earth Engine (GEE) is presented as an innovative tool for agricultural manage- ment through the geospatial analysis of satellite imagery. In this study, GEE was used to classify soils at the Santa Lucía Experimental Farm (FESL), employing Sentinel-2 imagery from the Copernicus program with a resolution of 20 × 20 m throughout the year 2022. Four training classes were considered (pastures, forests, coffee, and infras- tructure) using the Random Forest classifier. Additionally, a pixel-by-pixel confusion matrix was generated for both the training and validation processes. The results show an overall accuracy of 96% for the training set and 61% for the validation set, highlighting the model’s efficiency in class distinction, although with potential for improvement in distinguishing between coffee and forest classes.