Resumen
The proposed method is a neural-network-based tool for the early warning of ground settlement hazard in urban areas. On the basis of the analysis of MT-InSAR data through an unsupervised learning, the method can find precursors of similar time-evolving phenomena. The method can be applied under different warning criteria and for different hyper-parameters of the monitoring system.