Thank you! 🙂

This methodology including airborne hyperspectral data achieved promising results, paving the way to enhance operational soil mapping in challenging Mediterranean ecosystems. Access the paper through doi.org/10.1016/j.ca... #RemoteSensing #SoilScience #MachineLearning @unisevilla.bsky.social

We also assessed different Machine Learning methods, such as Random Forest or Support Vector Regression, together with various Feature Selection wrappers methods based on sequential methods.

The main challenge of this study was the diversity of land covers, highlighting Spanish fir (Abies pinsapo) forests. Thus, we applied an indirect approach based on SCORPAN, including hyperspectral band and narrow-band indices representing organisms’ factor.

In this study, we explored the potential of Airborne Hyperspectral Scanner (AHS) compared with Sentinel-2 as a baseline sensor to map soil organic matter and clay content in Sierra de las Nieves, Spain, a complex Mediterranean ecosystem.

A éstos los vimos en directo este Primavera y fue increíble...