Our Research & Publications Team, led by Eromanga Adermann and Daniel Fernández, has published an article in the remote sensing journal MDPI titled ‘Comparative Analysis of Machine Learning Algorithms for Soil Erosion Modelling Based on Remotely Sensed Data’.
The study shows the effectiveness of using remote sensing based methods for soil erosion assessment in the Arctic region, where ground studies are difficult to perform. We developed a process that can be automated to predict soil erosion risk for larger, less accessible areas from sentinel2 images. Our findings will contribute to the growing body of knowledge in this field.
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