Google Earth Engine: Evaluation of the scopes andlimitations for the resolve of agricultural problems in SantaLucía, Barva, Heredia
সংরক্ষণ করুন:
| লেখক: | , , |
|---|---|
| বিন্যাস: | artículo original |
| বর্তমান অবস্থা: | Versión publicada |
| প্রকাশনার তারিখ: | 2025 |
| বিবরন: | 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. |
| দেশ: | Portal de Revistas UNA |
| প্রতিষ্ঠান: | Universidad Nacional de Costa Rica |
| Repositorio: | Portal de Revistas UNA |
| ভাষা: | Español Inglés Portugués |
| OAI Identifier: | oai:www.revistas.una.ac.cr:article/22028 |
| অনলাইন ব্যবহার করুন: | https://www.revistas.una.ac.cr/index.php/geografica/article/view/22028 |
| মুখ্য শব্দ: | Agriculture Google Earth Engine land use satellite images Sentinel 2 Agricultura Imágenes satelitales Uso de suelo imagens de satélite Sentinel-2 uso do solo |