At CARCAVA, we are pleased to share the publication of our latest research in the scientific journal Agronomy MDPI, where we address one of the main challenges for soil sustainability in Mediterranean basins: gully erosion.
This study aims to automatically map the gully network in the olive-growing landscapes of the Guadalquivir basin (Spain) using Machine Learning (ML) algorithms. We evaluated four models (Random Forest, SVM, Decision Tree, and Logistic Regression), integrating 17 predictive variables (including hydrotopographic, climatic, and edaphic factors) and the Gully Head Initiation (GHI) index.
This work demonstrates the potential of combining physically based indices with machine learning algorithms to generate high-resolution cartography of gully networks—an essential tool for soil conservation planning in Mediterranean olive-growing systems.
Want to know the results? We invite you to read the full article in Agronomy: https://www.mdpi.com/2073-4395/16/6/622
Authors: Paula Gonzalez Garrido, Adolfo Peña Acevedo, Francisco Javier Mesas Carrascosa y Juan R. Julca Torres.
DOI: https://doi.org/10.3390/agronomy16060622
Download: Agronomy-Regional Scale Mapping of Gully Network in Mediterranean Olive Landscapes