Currently, there are efforts to classify and predict future displacement events (e.g., landslides, infrastructure collapse) using machine learning from PSInSAR-derived deformation maps. This paper proposes two workflows for creating databases with information about disasters from scanned documents and online news sources. The databases can be used as ground truth to confirm that the deformation profiles from the training datasets are related to actual events or as input in future machine learning algorithms.

Kepler Space Inc. is creating a wide area Canadian Ground Motion Service (C-GMS), initially based on time series (every 6/12 days, between 2015 and 2022) of Sentinel-1 (S-1) satellite radar data and a modified Persistent Scatterers Interferometry (PSInSAR) approach to detect and map ground motion over time, with mm/year accuracy over wide areas (up to 700 km swaths). The information available through C-GMS follows the general format of the European Ground Motion Service, but with additional layers depicting seasonal motion, coherent after/before date, changes in displacement rates and break events. Presently C-GMS covers the Windsor-Quebec City corridor (roughly 1100 km in the East-West direction and around 250-500 km in the NS direction and is publicly available for viewing and data download at http://c-gms.com/.

Inspection of temporal deformation profiles from the Luțca bridge collapse, in Romania, showed that before the disaster, some PSI deformation profiles exhibits a pattern of subsidence/uplift followed by loss of coherence. In this work, it is proposed a new methodology for detecting such profiles, based on the removal of the seasonal component and piecewise linear modeling of deformation profiles. The methodology is not limited to the aforementioned types of profiles. The method is validated on an area including the Luțca bridge.

A remote operated C-band SAR sensor for agriculture applications was developed and deployed in the field. The sensor operates at a central frequency of 5.400 GHz. It comprises a 2D scanning system and monolbi-static channels which allow the operation in single- and repeatpass interferometry modes. Sensor is designed and developed as a ground-based configuration, simulating the measurement geometry of Sentinel-1 and a potential companion satellite, intended to provide single-pass interferometric products for 3D imaging applied on agricultural crops, in order to retrieve the biophysical parameters of plants and their development status.

In this paper an analysis of the temporal profiles from the national ground motion map of Romania is presented. The map was built based on Sentinel-1 A/B synthetic aperture radar images acquired between 2015 – 2019, using the persistent scatterer technique, and to date, it is the first nationwide deformation map for Romania. Two types of common deformation patterns were analyzed: periodic deformation, associated with seasonal thermal dilation, and deformation with changes in the linear trend, i.e., steps and piecewise linear deformation profiles with changes of the linear trend above a threshold. The patterns were detected using methods based on statistics and signal processing.

The short revisit time and large coverage of the Sentinel-1 sensor have opened the way for countrywide deformation maps through persistent scatterer interferometry techniques. It is impossible for a human operator to manually verify millions of data points, hence the need for automatic analysis methods. In this paper, we expand on previous work by employing the newly developed uniform manifold approximation and projection dimensionality reduction methodology to deformation profiles, in a supervised manner, and we show that it is possible to identify certain types of profiles.

In this paper, the ground stability of the city of Constanta and surrounding areas (in Romania) is analyzed using the persistent scatterer interferometry technique, applied to Sentinel-l SAR data spanning an interval of two years. Two deformation maps are computed: one where the atmospheric phase screen is estimated and removed using ERA-Interim data and spatial filtering, and another using only spatial filtering.

This paper presents the first outdoor measurements with the experimental ground based C-band synthetic aperture radar developed by the authors. A 3 meters long rail was used to generate the synthetic aperture. The results depict the first outdoor measurements, i.e. synthetic aperture radar imaging and interferometry.

The temporal evolution of pixel values in Satellite Image Time Series (SITS) is considered criterion for the characterization, discrimination and identification of terrestrial objects and phenomena. Due to the exponential behavior of sequences number with specialization, Sequential Data Mining techniques need to be applied. The spatial aspect of the data was taken into account by the introduction of connectivity measures that characterize the pixels tendency to form objects. The conjunction of corresponding Connectivity Constraints (CC) with the Support Constraint (SC) leads to the extraction of Grouped Frequent Sequential Patterns (GFSP), a concept with proved capability for preliminary description and localization of terrestrial events. This work is focused on efficient SITS extraction of evolutions that fulfil SC and CC. Experiments performed on Bucharest urban interferometric SITS are used to illustrate the potential of the approach to find interesting evolution patterns.

This work focuses on monitoring the ground motion and infrastructure stability in an urban environment, namely in the city of Bucharest. 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 piles' foundations. All these new works have an important impact upon the upper ground stability. The PSI (Persistent Scatterer Interferometry) technique is used to extract the ground deformation in Bucharest from archived C-band ESA data and from more recent TerraSAR-X data. The conducted analysis constitutes historical case studies for Bucharest City covering the intervals 1992-1999, 2003-2009 and 2011-2012.