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Interferometric Synthetic Aperture (InSAR) time series measurements are widely used to monitor a variety of processes including subsidence, landslides, and volcanic activity. However, interpreting large InSAR datasets can be difficult due to the volume of data generated, requiring sophisticated signal-processing techniques to extract meaningful information. We propose a novel framework for interpreting the large number of ground displacement measurements derived from InSAR time series techniques using a three-step process: (1) dimensionality reduction of the displacement time series from an InSAR data stack; (2) clustering of the reduced dataset; and (3) detecting and quantifying accelerations and decelerations of deforming areas using a change detection method. The displacement rates, spatial variation, and the spatio-temporal nature of displacement accelerations and decelerations are used to investigate the physical behaviour of the deforming ground by linking the timing and location of changes in displacement rates to potential causal and triggering factors. We tested the method over the Bandung Basin in Indonesia using Sentinel-1 data processed with the small baseline subset InSAR time series technique. The results showed widespread subsidence in the central basin with rates up to 18.7 cm/yr. We identified 12 main clusters of subsidence, of which three covering a total area of 22 km2 show accelerating subsidence, four clusters over 52 km2 show a linear trend, and five show decelerating subsidence over an area of 22 km2. This approach provides an objective way to monitor and interpret ground movements, and is a valuable tool for understanding the physical behaviour of large deforming areas. [ABSTRACT FROM AUTHOR]

Abstract: Jakarta is the capital of Indonesia. It is one of the largest cities with an around 10 million population as for 2010, covering an area of about 661 square kilometers. The land subsidence phenomena in several areas of Jakarta are well known for many years. Land subsidence does damage infrastructures in the city; therefore, it has to be closely monitored and analysed. In this paper, the authors have demonstrated the capability of the PALSAR sensor aboard the Japanese ALOS satellite for large-scale mapping of land subsidence in Jakarta. Mapping results were produced from 17 ALOS PALSAR L-band radar images using persistent scatterer radar interferometry (PSI). The GEOS-PSI software, developed by the Geodesy and Earth Observing Systems group at UNSW for PSI analysis, was used to detect and map those land subsidence. The results showed that the land in the area of Jakarta was deforming at different rates across several zones. The land subsidence measured from ALOS PALSAR imagery were cross-examined with the subsidence values obtained from 4 GPS campaign surveys by the authors at 19 stations between 2007 and 2010. The magnitudes and trends of the deformation obtained from both techniques agreed well in general for those pinpoints of GPS. After the removal of 2 suspected outliers in GPS measurements, the subsidence rate difference between the two techniques range from −29 to 6mm/year, with a standard deviation of 9mm/year and an average absolute difference of 8mm/year. This research has suggested that PSI with L-band ALOS PALSAR data can be a promising technique to complement the GPS surveying for monitoring land subsidence in super large cities like Jakarta. [Copyright &y& Elsevier]