We published our research paper on remote mapping of soil erosion risk in Iceland using Sentinel-2 satellite data and machine learning in the ISPRS Archives. This study tackles the challenges of soil erosion assessment in Arctic conditions, where harsh weather and limited accessibility make ground-based monitoring difficult.
By applying a Support Vector Machine (SVM) classification model calibrated with ground truth samples, we developed a method to automate erosion risk analysis over large, remote areas. This approach enhances our ability to monitor Iceland’s landscapes and supports sustainable land management.
Read the full paper here: https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-135-2022
#RemoteSensing #SoilErosion #Sentinel2 #MachineLearning #Iceland