Google Earth Engine: Evaluation of the scopes andlimitations for the resolve of agricultural problems in SantaLucía, Barva, Heredia
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| Autors: | , , |
|---|---|
| Format: | artículo original |
| Estat: | Versión publicada |
| Data de publicació: | 2025 |
| Descripció: | 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. |
| Pais: | Portal de Revistas UNA |
| Institution: | Universidad Nacional de Costa Rica |
| Repositorio: | Portal de Revistas UNA |
| Idioma: | Español Inglés Portugués |
| OAI Identifier: | oai:www.revistas.una.ac.cr:article/22028 |
| Accés en línia: | https://www.revistas.una.ac.cr/index.php/geografica/article/view/22028 |
| Paraula clau: | Agriculture Google Earth Engine land use satellite images Sentinel 2 Agricultura Imágenes satelitales Uso de suelo imagens de satélite Sentinel-2 uso do solo |