Unsupervised learning applied to Persistent Scatterer Interferometry datasets for the characterisation of ground motion patterns in northern Germany

2021 ◽  
Author(s):  
Nicolas Jakob Wagener ◽  
Andre Cahyadi Kalia
Keyword(s):  
Unsupervised Learning ◽  
Ground Motion ◽  
Northern Germany ◽  
Persistent Scatterer Interferometry ◽  
Motion Patterns ◽  
Persistent Scatterer

scholarly journals InSAR Greece with Parallelized Persistent Scatterer Interferometry: A National Ground Motion Service for Big Copernicus Sentinel-1 Data

2020 ◽  
Vol 12 (19) ◽  
pp. 3207
Author(s):  
Ioannis Papoutsis ◽  
Charalampos Kontoes ◽  
Stavroula Alatza ◽  
Alexis Apostolakis ◽  
Constantinos Loupasakis
Keyword(s):  
Time Series ◽  
Ground Motion ◽  
Large Scale ◽  
Persistent Scatterer Interferometry ◽  
Persistent Scatterers ◽  
Processing Chain ◽  
Persistent Scatterer ◽  
Basin Scale ◽  
Wide Range ◽  
The Impact

Advances in synthetic aperture radar (SAR) interferometry have enabled the seamless monitoring of the Earth’s crust deformation. The dense archive of the Sentinel-1 Copernicus mission provides unprecedented spatial and temporal coverage; however, time-series analysis of such big data volumes requires high computational efficiency. We present a parallelized-PSI (P-PSI), a novel, parallelized, and end-to-end processing chain for the fully automated assessment of line-of-sight ground velocities through persistent scatterer interferometry (PSI), tailored to scale to the vast multitemporal archive of Sentinel-1 data. P-PSI is designed to transparently access different and complementary Sentinel-1 repositories, and download the appropriate datasets for PSI. To make it efficient for large-scale applications, we re-engineered and parallelized interferogram creation and multitemporal interferometric processing, and introduced distributed implementations to best use computing cores and provide resourceful storage management. We propose a new algorithm to further enhance the processing efficiency, which establishes a non-uniform patch grid considering land use, based on the expected number of persistent scatterers. P-PSI achieves an overall speed-up by a factor of five for a full Sentinel-1 frame for processing in a 20-core server. The processing chain is tested on a large-scale project to calculate and monitor deformation patterns over the entire extent of the Greek territory—our own Interferometric SAR (InSAR) Greece project. Time-series InSAR analysis was performed on volumes of about 12 TB input data corresponding to more than 760 Single Look Complex Sentinel-1A and B images mostly covering mainland Greece in the period of 2015–2019. InSAR Greece provides detailed ground motion information on more than 12 million distinct locations, providing completely new insights into the impact of geophysical and anthropogenic activities at this geographic scale. This new information is critical to enhancing our understanding of the underlying mechanisms, providing valuable input into risk assessment models. We showcase this through the identification of various characteristic geohazard locations in Greece and discuss their criticality. The selected geohazard locations, among a thousand, cover a wide range of catastrophic events including landslides, land subsidence, and structural failures of various scales, ranging from a few hundredths of square meters up to the basin scale. The study enriches the large catalog of geophysical related phenomena maintained by the GeObservatory portal of the Center of Earth Observation Research and Satellite Remote Sensing BEYOND of the National Observatory of Athens for the opening of new knowledge to the wider scientific community.

scholarly journals Persistent Scatterer Interferometry analysis of multi-temporal Sentinel-1 radar imagery to detect ground subsidence in the city of Tirana, Albania

2019 ◽  
Vol 9 (3) ◽  
pp. 108
Author(s):  
Enton Bedini
Keyword(s):  
Ground Motion ◽  
Groundwater Resources ◽  
Urban Expansion ◽  
Tall Buildings ◽  
Ground Subsidence ◽  
Persistent Scatterer Interferometry ◽  
Persistent Scatterer ◽  
Radar Imagery ◽  
Over Exploitation ◽  
The City

Persistent Scatterer Interferometry (PSI) analysis of Sentinel-1 C-band radar spaceborne imagery was carried out to detect ground subsidence zones in the city of Tirana, Albania. Fifty-eight Sentinel-1A Interferometric Wide (IW) images of the time period January 2017 – December 2018, with a temporal resolution of 12 days, were used as input to the PSI. The PSI technique can detect millimeter-scale ground motion. The results show a zone of ground subsidence of about 7 mm/year along a segment of the Tirana Outer Ring road, where numerous tall buildings have been constructed in the last twenty years. In the northern part of the Kamza municipality a ground subsidence of about 2-3 mm/year is observed. In the western part of the Kamza municipality, it is also observed a ground subsidence of about 7 mm/year. In general, the areas where ground subsidence was detected from the PSI analysis, are characterized by urban expansion in the last thirty years. The ground subsidence could be a result of the lowering of the water table from the construction works or from over exploitation of groundwater resources. The study represents the first reported analysis of the Sentinel-1 imagery for ground motion detection in the city of Tirana. Further monitoring and detailed studies on the causes of the ground subsidence in this important urban area are necessary.

scholarly journals Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets

2019 ◽  
Vol 11 (14) ◽  
pp. 1675 ◽  
Author(s):  
Tomás ◽  
Pagán ◽  
Navarro ◽  
Cano ◽  
Pastor ◽  
...  
Keyword(s):  
Regional Scale ◽  
Central Italy ◽  
Geographical Information ◽  
External Information ◽  
Automatic Identification ◽  
Persistent Scatterer Interferometry ◽  
Active Deformation ◽  
Persistent Scatterers ◽  
Persistent Scatterer ◽  
Map Scale

This work describes a new procedure aimed to semi-automatically identify clusters of active persistent scatterers and preliminarily associate them with different potential types of deformational processes over wide areas. This procedure consists of three main modules: (i) ADAfinder, aimed at the detection of Active Deformation Areas (ADA) using Persistent Scatterer Interferometry (PSI) data; (ii) LOS2HV, focused on the decomposition of Line Of Sight (LOS) displacements from ascending and descending PSI datasets into vertical and east-west components; iii) ADAclassifier, that semi-automatically categorizes each ADA into potential deformational processes using the outputs derived from (i) and (ii), as well as ancillary external information. The proposed procedure enables infrastructures management authorities to identify, classify, monitor and categorize the most critical deformations measured by PSI techniques in order to provide the capacity for implementing prevention and mitigation actions over wide areas against geological threats. Zeri, Campiglia Marittima–Suvereto and Abbadia San Salvatore (Tuscany, central Italy) are used as case studies for illustrating the developed methodology. Three PSI datasets derived from the Sentinel-1 constellation have been used, jointly with the geological map of Italy (scale 1:50,000), the updated Italian landslide and land subsidence maps (scale 1:25,000), a 25 m grid Digital Elevation Model, and a cadastral vector map (scale 1:5,000). The application to these cases of the proposed workflow demonstrates its capability to quickly process wide areas in very short times and a high compatibility with Geographical Information System (GIS) environments for data visualization and representation. The derived products are of key interest for infrastructures and land management as well as decision-making at a regional scale.

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