Physical assessment of coastal vulnerability under enhanced land subsidence in Semarang,Indonesia, using multi-sensor satellite data

Research has been conducted in Semarang, Indonesia, to assess coastal vulnerability under enhanced land subsidence using multi-sensor satellite data, including the Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR), Landsat TM, IKONOS, and TOPEX/Poseidon. A coastal vulnerability index (CVI) was constructed to estimate the level of vulnerability of a coastline approximately 48.68?km in length using seven physical variables, namely, land subsidence, relative sea level change, coastal geomorphology, coastal slope, shoreline change, mean tidal range, and significant wave height. A comparison was also performed between a CVI calculated using seven parameters and a CVI using six parameters, the latter of which excludes the land subsidence parameter, to determine the effects of land subsidence during the coastal vulnerability assessment. This study showed that the accuracy of coastal vulnerability was increased 40% by adding the land subsidence factor (i.e., CVI 6 parameters?=?53%, CVI 7 parameters?=?93%). Moreover, Kappa coefficient indicated very good agreement (0.90) for CVI 7 parameters and fair agreement (0.3) for CVI 6 parameters. The results indicate that the area of very high vulnerability increased by 7% when land subsidence was added. Hence, using the CVI calculation including land subsidence parameters, the very high vulnerability area is determined to be 20% of the total coastline or 9.7?km of the total 48.7?km of coastline. This study proved that land subsidence has significant influence on coastal vulnerability in Semarang.     

Monitoring of long-term land subsidence from 2003 to 2017 in coastal area of Semarang,Indonesia by SBAS DInSAR analyses using Envisat-ASAR,ALOS-PALSAR,and Sentinel-1A SAR data

Land subsidence is a critical issue that large cities located in coastal areas, such as Semarang, Indonesia, must address. The monitoring of land subsidence is vital for predicting and mitigating the disasters that such subsidence may cause. Therefore, an economical and effective monitoring method, which can continuously provide accurate measurements over extensive areas, is highly required. Differential Interferometry Synthetic Aperture Radar (DInSAR) has the potential to be a powerful technique that can meet the above demands. Actually, DInSAR has been applied to monitor the subsidence in Semarang, but it was for a limited period before 2012.In order to clarify the transition of the long-term subsidence behavior in Semarang, the Small Baseline Subset (SBAS) method, which is one type of time-series DInSAR, is employed in this research. The sets of data of Envisat-ASAR (2003–2007), ALOS-PALSAR (2007–2011), and Sentinel-1A (2015–2017) are employed for the analyses. Then, the validity of the SBAS results is discussed from the viewpoints of both spatial distribution and temporal transition using GPS displacement measurement results and the geological conditions of the ground.On the other hand, as the lifespan of SAR satellites is commonly designed to be around 5–7?years, an appropriate method, which can connect the subsidence provided independently by the unlinked time-series data sets of the three different SAR satellite data, is required. This study uses the Hyperbolic Method (HM) to connect the above unlinked SBAS results. The HM is often used to fit the monitored subsidence in practice as a geotechnical engineering tool. Using this method, 14?years of the temporal behavior of the subsidence in Semarang is evaluated.It is found that the transition of the subsidence is different depending on the location, and that the subsidence rate is still increasing in the north and northeast parts of the coastal area. This study shows that SBAS DInSAR can be a useful tool for long-term continuous subsidence monitoring.