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Landslides are among the most intense geological disasters worldwide. Several remote sensing techniques have been used to study these phenomena over the last few decades, including Global Navigation Satellite Systems (GNSS) and Multi-Temporal Interferometric Synthetic Aperture Radars (MT-InSAR), in particular, Small Baseline Subset (SBAS) and Permanent Scatterer Interferometry (PSI). The University of Azuay and highway infrastructure (Cuenca - Ecuador) were affected by slow-moving landslides which in urban areas had more noticeable deformation effects due to their crowns. Furthermore, evidence indicates that the landslide toe was developed in a rural area. To study landslide boundary and deformation kinematics comprehensively, we need to observe two distinct scattering surfaces using SAR imagery (high coherence areas in the urban area and low coherence areas in the rural area). We can also observe different distributions in X- and C-bands due to the rural area covered by vegetation and trees at the toe of the landslide. Two sets of radar images were analyzed and compared for monitoring the aforementioned slow-moving landslide kinematics, including Sentinel1-A (S1-A) and COSMO-SkyMed (CSK). PSI and SBAS techniques have been used to measure the rate of surface deformation and displacement time series at CSK over the period (2017-2019) and S1-A units over the period (2015-2018), respectively. Furthermore, a GNSS station in the stable area was used as a reference station to integrate the PSI and SBAS results over space. Then, an unsupervised machine learning algorithm (K-medians) was used to determine the most appropriate intervals for preparing mean deformation rate maps. Finally, a comparison was made between the outputs obtained from this study and displacement recorded at two additional GNSS stations located in the area affected by deformation. As a result, by comparing and monitoring double-band SAR satellites and different SAR image processing techniques, it became possible to analyze the whole landslide of our case study appropriately. [ABSTRACT FROM AUTHOR]

Underground mining can produce subsidence phenomena, especially if orebodies are surficial or occur in soft rocks. In some countries, illegal mining is a big problem for environmental, social and economic reasons. However, when unauthorized excavation is conducted underground, it is even more dangerous because it can produce unexpected surficial collapses in areas not adequately monitored. For this reason, it is important to find quick and economic techniques able to give information about the spatial and temporal development of uncontrolled underground activities in order to improve the risk management. In this work, the differential interferometric synthetic aperture radar (DInSAR) technique, implemented in the SUBSOFT software, has been used to study terrain deformation related to illegal artisanal mining in Ecuador. The study area is located in Zaruma (southeast of El Oro province), a remarkable site for Ecuadorian cultural heritage where, at the beginning of the 2017, a local school collapsed, due to sinkhole phenomena that occurred around the historical center. The school, named "Inmaculada Fe y Alegria", was located in an area where mining activity was forbidden. For this study, the surface deformations that occurred in the Zaruma area from 2015 to 2019 were detected by using the Sentinel-1 data derived from the Europe Space Agency of the Copernicus Program. Deformations of the order of five centimeters were revealed both in correspondence of known exploitation tunnels, but also in areas where the presence of tunnels had not been verified. In conclusion, this study allowed to detect land surface movements related to underground mining activity, confirming that the DInSAR technique can be applied for monitoring mining-related subsidence. [ABSTRACT FROM AUTHOR]