Large earthquakes produce crustal deformation that can be quantified by geodetic measurements, allowing for the determination of the slip distribution on the fault. We used data from Global Positioning System (GPS) networks in Central Chile to infer the static deformation and the kinematics of the 2010 moment magnitude (Mw) 8.8 Maule megathrust earthquake. From elastic modeling, we found a total rupture length of ~500 kilometers where slip (up to 15 meters) concentrated on two main asperities situated on both sides of the epicenter. We found that rupture reached shallow depths, probably extending up to the trench. Resolvable afterslip occurred in regions of low coseismic slip. The low-frequency hypocenter is relocated 40 kilometers southwest of initial estimates. Rupture propagated bilaterally at about 3.1 kilometers per second, with possible but not fully resolved velocity variations.
This work is focused on deformation activity mapping and monitoring using Sentinel-1 (S-1) data and the DInSAR (Differential Interferometric Synthetic Aperture Radar) technique. The main goal is to present a procedure to periodically update and assess the geohazard activity (volcanic activity, landslides and ground-subsidence) of a given area by exploiting the wide area coverage and the high coherence and temporal sampling (revisit time up to six days) provided by the S-1 satellites. The main products of the procedure are two updatable maps: the deformation activity map and the active deformation areas map. These maps present two different levels of information aimed at different levels of geohazard risk management, from a very simplified level of information to the classical deformation map based on SAR interferometry. The methodology has been successfully applied to La Gomera, Tenerife and Gran Canaria Islands (Canary Island archipelago). The main obtained results are discussed.
In this work, the analysis of TerraSAR-X satellite images combining both conventional and advanced Differential Synthetic Aperture Radar Interferometry (DInSAR) approaches has proven to be effective to detect and monitor fast evolving mining subsidence on urban areas in the Upper Silesian Coal Basin (Poland). This region accounts for almost three million inhabitants where mining subsidence has produced severe damage to urban structures and infrastructures in recent years. Conventional DInSAR approach was used to generate 28 differential interferograms between 5 July 2011 and 21 June 2012 identifying 31 subsidence troughs that account up to 245 mm of displacement in 54 days (equivalent to 1660 mm/year). SqueeSARTM processing yielded a very dense measurement point distribution, failing to detect faster displacements than 330 mm/year, which occur within the subsidence troughs detected with conventional DInSAR. Despite this limitation, this approach was useful to delimit stable areas where mining activities are not conducted and areas affected by residual subsidence surrounding the detected subsidence troughs. These residual subsidence mining areas are located approximately 1 km away from the 31 detected subsidence troughs and account for a subsidence rate greater than 17 mm/year on average. The validation of this methodology has been performed over Bytom City were underground mining activity produced severe damages in August 2011. Conventional DInSAR permitted to successfully map subsidence troughs between July and August 2011 that coincide spatially and temporally with the evolution of underground mining excavations, as well as with the demolition of 28 buildings of Karb district. Additionally, SqueeSARTM displacement estimates were useful to delimit an area of 8.3 km2 of Bytom city that is affected by a residual mining subsidence greater than 5 mm/year and could potentially suffer damages in the midterm. The comparison between geodetic data and SqueeSARTM for the common monitoring period yields and average absolute difference of 7 mm/year, which represents 14% of the average displacement rate measured by the geodetic benchmarks. These results demonstrate that the combined exploitation of high-resolution satellite SAR data through both conventional and advanced DInSAR techniques could be crucial to monitor fast evolving mining subsidence, which may severely impact highly populated mining areas such as the Upper Silesia Coal Basin (USCB).
Landslides are widespread natural hazards that generate considerable damage and economic losses worldwide. Detecting terrain movements caused by these phenomena and characterizing affected urban areas is critical to reduce their impact. Here we present a fast and simple methodology to create maps of vulnerable buildings affected by slow-moving landslides, based on two parameters: (1) the deformation rate associated to each building, measured from Sentinel-1 SAR data, and (2) the building damage generated by the landslide movement and recorded during a field campaign. We apply this method to Arcos de la Frontera, a monumental town in South Spain affected by a slow-moving landslide that has caused severe damage to buildings, forcing the evacuation of some of them. Our results show that maximum deformation rates of 4 cm/year in the line-of-sight (LOS) of the satellite, affects La Verbena, a newly-developed area, and displacements are mostly horizontal, as expected for a planar-landslide. Our building damage assessment reveals that most of the building blocks in La Verbena present moderate to severe damages. According to our vulnerability scale, 93% of the building blocks analysed present high vulnerability and, thus, should be the focus of more in-depth local studies to evaluate the serviceability of buildings, prior to adopting the necessary mitigation measures to reduce or cope with the negative consequences of this landslide. This methodology can be applied to slow-moving landslides worldwide thanks to the global availability of Sentinel-1 SAR data.