Hydrometeorological phenomena, including mass movements, are a frequent threat that can generate a great impact at different levels. In order to estimate the susceptibility to mass movements, this work contains a new proposal to estimate the susceptibility to mass movements using a supervised learning algorithm designed using AutoML (Automated machine learning). Pixel-level information from Sentinel-2 multispectral images was used to train the model, and an expert’s susceptibility map was used as labels.
Hydrometeorological phenomena, including mass movements, are a frequent threat that can generate a great impact at different levels. In order to estimate the susceptibility to mass movements, this work contains a new proposal to estimate the susceptibility to mass movements using a supervised learning algorithm designed using AutoML (Automated machine learning). Pixel-level information from Sentinel-2 multispectral images was used to train the model, and an expert’s susceptibility map was used as labels. Read More
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