Monitoring Urban Subsidence in Bucharest City with TerraSAR-X

This work focuses on monitoring the ground motion and infrastructure stability in an urban environment, namely in the city of Bucharest. The city is located in the southeast of Romania and covers an urban area of about 285 km2. Due to its position on the banks of Dambovita River and high underground water levels, the risk of subsidence in the area is significant. Moreover, its closeness to Vrancea seismic area increases the risk of seismic induced deformation in the area. Bucharest is a fast developing city with the average construction rate of 8-20% new buildings with respect to the existing ones. Consequently, the civil engineering industry faced new challenges related to the need of having taller buildings with deeper underground levels, a developing network of subway lines and more bridges with large diameter pilars’ foundations. All these new works have an important impact upon the upper ground stability

Practical InSAR Lectures

The current role of InSAR was illustrated

Multi-sensor wetland mapping over the Peace Athabasca Delta

The joint use of diverse sensors is of major interest in the remote sensing community. With view to the repeata-bility of acquisitions, todays satellite sensor systems provide a temporal resolution of about one month in the Shannon sense. Thus, the joint use of different sensor systems is unavoidable for monitoring purposes. This contribution designs a novel similarity transformation that extracts class similarities based on local distributions from any available image independent of sensor (TerraSAR-X, RADARSAT-2, Sentinel-1) or polarimetric mode (Quad, Dual-Co, Dual-Cross, Single). The resulting class probability development characterizes the temporal change of the Peace Athabasca Delta in Northern Canada

Evaluation of C-Band SAR for Identification of Flooded Vegetation in Emergency Response Products

A synthetic aperture radar (SAR) data set of the Peace Athabasca Delta, Alberta, was used to evaluate approaches to flooded vegetation mapping. A primary objective was to identify how to add a flooded vegetation layer to the Emergency Geomatics Service (EGS) SAR-derived flood products. Field data were used to identify non-flooded and flooded vegetation. A combination of statistical analyses and box plot visual inspection was used to evaluate the magnitude-only images, the polarimetric and compact polarimetric parameters/decompositions, and the coherence products for mapping flooded vegetation. This paper provides some background on the use of SAR for flood mapping, describes the data and processing methods, and presents the results of this comparison. To some degree all polarizations and techniques were effective for mapping flooded vegetation due to the increased backscatter intensity and the phase shift from the double bounce scattering. In particular, all polarization combinations, the HH/HV ratio, Shannon entropy, and the m-chi double bounce produce good separation. The water/vegetation interface remains coherent when flooded, also allowing flooded vegetation to be identified with seasonal coherence. These results demonstrate that the use of multi-mode RADARSAT Constellation Mission data for providing a flooded vegetation layer to EGS flood maps is possible

Insar coherence analysis for wetlands in alberta, canada using time-series sentinel-1 data

Wetlands are valuable natural resources which provide numerous services to the environment. Many studies have demonstrated the potential of various types of remote sensing datasets and techniques for wetland mapping and change analysis. However, there are a relatively low number of studies that have investigated the application of the Interferometric Synthetic Aperture Radar (InSAR) coherence products for wetland studies, especially over large areas. Therefore, in this study, coherence products over the entire province of Alberta, Canada (~661,000 km2 ) were generated using the Sentinel-1 data acquired from 2017 to 2020. Then, these products along with large amount of wetland reference samples were employed to assess the separability of different wetland types and their trends over time. Overall, our analyses showed that coherence can be considered as an added value feature for wetland classification and monitoring. The Treed Bog and Shallow Open Water classes showed the highest and lowest coherence values, respectively. The Treed Wetland and Open Wetland classes were easily distinguishable. When analyzing the wetland subclasses, it was observed that the Treed Bog and Shallow Open Water classes can be easily discriminated from other subclasses. However, there were overlaps between the signatures of the other wetland subclasses, although there were still some dates where these classes were also distinguishable. The analysis of multi-temporal coherence products also showed that the coherence products generated in spring/fall (e.g., May and October) and summer (e.g., July) seasons had the highest and lowest coherence values, respectively. It was also observed that wetland classes preserved coherence during the leaf-off season (15 August–15 October) while they had relatively lower coherence during the leaf-on season (i.e., 15 May–15 August). Finally, several suggestions for future studies were provided.Geo-engineerin