Search

InSAR information to record dynamic changes on the surface using remote sensor has been obtained for the Metropolitan Area of San Salvador and compared with surface dynamic situation and fixed GPS surface movement information. The city is located in an active tectonic depression between the tectonic remains of ancient volcanoes and active volcanic centers. This area has been historically affected by earthquakes, volcanic activity, erosion, mass movements, and flooding. The morphology of the area has been changed by human activities, most of the time without any respect to natural processes thus increasing the problems. There are sectors that show subsidence close to Ilopango Caldera that could be connected to diastrophic block tectonic movements connected to post-seismic episodes after 2012 earthquake, and aquifer level changes due effects of climate change and overexploitation of aquifers. These movements may increase the huge problems of erosion and mass wasting through las Canas basin. In addition, after 2017 seismic swarm a horizontal movement was recorded with the satellite radar interferometry (InSAR) in two areas, which reflects the possible movement of faults that crosses the area of study. This type of information provides important data for the decision-making of land, protection and mitigation zones, monitoring of governmental institutions, and for regional planning.

The Sentinel-1 satellite system continuously observes European countries at a relatively high revisit frequency of six days per orbital track. Given the Sentinel-1 configuration, most areas in Czechia are observed every 1–2 days by different tracks in a moderate resolution. This is attractive for various types of analyses by various research groups. The starting point for interferometric (InSAR) processing is an original data provided in a Single Look Complex (SLC) level. This work represents advantages of storing data augmented to a specifically corrected level of data, SLC-C. The presented database contains Czech nationwide Sentinel-1 data stored in burst units that have been pre-processed to the state of a consistent well-coregistered dataset of SLC-C. These are resampled SLC data with their phase values reduced by a topographic phase signature, ready for fast interferometric analyses (an interferogram is generated by a complex conjugate between two stored SLC-C files). The data can be used directly into multitemporal interferometry techniques, e.g., Persistent Scatterers (PS) or Small Baseline (SB) techniques applied here. A further development of the nationwide system utilising SLC-C data would lead into a dynamic state where every new pre-processed burst triggers a processing update to detect unexpected changes from InSAR time series and therefore provides a signal for early warning against a potential dangerous displacement, e.g., a landslide, instability of an engineering structure or a formation of a sinkhole. An update of the processing chain would also allow use of cross-polarised Sentinel-1 data, needed for polarimetric analyses. The current system is running at a national supercomputing centre IT4Innovations in interconnection to the Czech Copernicus Collaborative Ground Segment (CESNET), providing fast on-demand InSAR results over Czech territories. A full nationwide PS processing using data over Czechia was performed in 2017, discovering several areas of land deformation. Its downsampled version and basic findings are demonstrated within the article., This work was supported by The Ministry of Education, Youth and Sports from the National Programme of Sustainability (NPU II) project “IT4Innovations excellence in science—LQ1602” and from the Large Infrastructures for Research, Experimental Development and Innovations project “IT4Innovations National Supercomputing Center—LM2015070”.

Space-borne Synthetic Aperture Radar (SAR) Interferometry (InSAR) is now a key geophysical tool for surface deformation studies. The European Commission’s Sentinel-1 Constellation began acquiring data systematically in late 2014. The data, which are free and open access, have global coverage at moderate resolution with a 6 or 12-day revisit, enabling researchers to investigate large- scale surface deformation systematically through time. However, full exploitation of the potential of Sentinel-1 requires specific processing approaches as well as the efficient use of modern computing and data storage facilities. Here we present LiCSAR, an operational system built for large-scale interferometric processing of Sentinel-1 data. LiCSAR is designed to automatically produce geocoded wrapped and unwrapped interferograms and coherence estimates, for large regions, at 0.001° resolution (WGS-84 system). The products are continuously updated in a frequency depending on prioritised regions (monthly, weekly or live update strategy). The products are open and freely accessible and downloadable through an online portal. We describe the algorithms, processing, and storage solutions implemented in LiCSAR, and show several case studies that use LiCSAR products to measure tectonic and volcanic deformation. We aim to accelerate the uptake of InSAR data by researchers as well as non-expert users by mass producing interferograms and derived products., This work was partially undertaken on ARC4, part of the High Performance Computing facilities at the University of Leeds, UK.

After two decades of SAR satellite operation, their data, processed by interferometric techniques (InSAR), allows for a sensitive detection of terrain movements. Various projects have risen towards the detection of landslide activity and thus possibility of early warning system based on SAR data. The ability of InSAR techniques to detect a slope stability is limited and depends on slope orientation, movement rate, vegetation cover and temporal and spatial image resolution. This paper presents common issues found in past projects of the team of authors observing landslides using available satellite SAR data processed by various InSAR techniques. It is demonstrated that in some cases the basic differential InSAR combining only two images provides more valuable information compared to advance multi-temporal InSAR techniques. The paper aims at providing guidelines for maximal successful detection of landslide activity and to introduce pros and cons of the InSAR method, which often discussed in geology and geophysics circles. We prove the potential of techniques using satellite-based InSAR to identify creeping movement of structures built at moving slopes and the limited possibility to detect movements at moderately vegetated slopes by using especially the L-band or a combination of winter-season SAR and other images within very short temporal difference. It is possible to overcome misinterpretation of results by proper understanding of InSAR source phase component at slopes, including phase distortions due to SAR geometry, vegetation movement (vegetated mass movement) and atmospheric pressure changes correlated with height differences.

The topic of this work covers current implementation of satellite radar (SAR) interferometry (InSAR) techniques for routine identification of dynamic land processes such as downhill creep and landslide activity, subsidence or displacements of various objects of infrastructure. With the emerge of European Copernicus programme, the need of effectivity in satellite Big Data processing increased. There are two Sentinel-1 satellites observing the Earth with 6 days revisit time, sending daily 100 TB of data to be archived. In case of the relatively small area of Czechia, the amount of data to be archived in a Czech national mirror is around 24 GB per day. Czech CESNET e-infrastructure has accepted the role of assessing Copernicus Ground Segment programme. A database mirroring Sentinel data over Czechia is established, however still in its early stage. A potential service based on an interferometric processing of Sentinel-1 data from this database has been prepared in Czech national supercomputing center IT4Innovations. As a basis of the system, several open-source projects were deployed, including MySQL-based burst metadatabase (TU Leeds), ISCE TOPS Processor (NASA/JPL), Doris coregistration algorithm (TU Delft) and StaMPS Small Baselines processor (Stanford University). Though more functionality can be rapidly developed, incorporating some of the own post-processing algorithms, even current early version of the system can yield interesting results by a fully automatic processing chain.

This short paper summarizes the effects of DEM errors influencing precision of deformation monitoring results using satellite SAR interferometry and presents basic mathematical approaches to quantify DEM accuracy needed for proper estimation of SAR interferometry parameters. While in case of appropriately large SAR dataset for Multi-Temporal Interferometry (MTI) processing the height difference is usually well estimated, still DEM accuracy should be carefully considered in case of using low number of images—and especially in case of processing differential InSAR with only one image pair. Depending on the interferogram pair combination characteristics, especially parameter known as perpendicular baseline (Bperp) describing the distance between satellite positions during their image acquisitions, the interferogram is more or less prone to DEM accuracy errors. In case of higher Bperp, a relatively high quality DEM is necessary to remove stereoscopic effect apparent in interferogram in order to distinguish interferogram phase element caused by temporal terrain deformation.

Part of Czech highway D1 connecting Ostrava city with Prague and Poland, is built over an undermined area of Ostrava-Svinov, with mines closed since 1991 in the area. Soon after its opening ceremony in 2008, the highway began to exhibit various significant deformations. An attempt of InSAR monitoring using ERS, Envisat and several TerraSAR-X Spotlight acquisitions was done in order to monitor progress of deformations, to consider suitability of satellite InSAR for such purposes and to search for footprints whether the deformations were caused by fading subsidence due to undermining or by another, local, reason. Only shallow subsidence was found in the area from Envisat data ranging 2005-2010. Highway deformations in late 2011 are observable from processing of limited set of 5 TerraSAR-X images using different methods. Detected deformations are very probably due to longitudinal thermal expansion of the observed highway bridge. This publication contains issues to be taken into consideration for appropriate interpretation and processing if the available input dataset is limited and not optimal.