This study proposes a new simple procedure for extracting coastline from Synthetic Aperture Radar (SAR) images by utilizing a low-pass filter and edge detection algorithm. The low-pass filter is used to improve the histogram of the pixel value of the SAR image. It provides better distribution of pixel value and makes it easy to separate between sea and land surfaces. This study provides the processing steps using open-source software, i.e., SNAP SAR processor and QGIS application. This procedure has been tested using dual polarization Sentinel-1 (10x10 meters resolution) and single polarization ALOS-2 (3x3 meters resolution) dataset. The results show that using Sentinel-1 with dual polarization (VH) provides a better result than single polarization (VV). In the ALOS-2 case, only single polarization (HH) is available. However, even using only HH polarization, ALOS-2 provides a good result. In terms of resolution, ALOS-2 provides a better coastline than Sentinel-1 data due to ALOS-2 has better resolution. This procedure is expected to be helpful to detect coastline changes and for coastal area management.

Tuzla City, Bosnia and Herzegovina, is very famous for salt mining. The intensive extraction of brine from the underground salt deposit caused accumulative subsidence of up to -12 m from 1956 to 2003. It induced serious damage to residences, buildings, and infrastructures. Although the activity of brine extraction was officially stopped in 2007, reports of subsidence are still on-going for some areas of Tuzla City according to a previous study. In the present study, a satellite-based method, i.e., Differential Synthetic Aperture Radar (DInSAR), is applied for the subsidence monitoring of the induced underground brine extraction. Since October 2014, SAR data obtained by the Sentinel-1A and -1B satellites (European Space Agency: ESA) and Small Baseline Subset (SBAS) multi-temporal analyses have been employed to obtain the spatial distribution and the temporal transition of the land subsidence. The accuracy and effectiveness of the SBAS-DInSAR method are assessed and evaluated by using the real-time kinematic GNSS monitoring system. DInSAR detected that the subsidence is still on-going at a velocity of -36.4 mm/year in some areas, especially in an area northeast of the center of the city. This study presents the validity and effectiveness of SBAS-DInSAR as a useful subsidence monitoring tool.

Land subsidence in Semarang is a famous environmental problem in Indonesia. This Subsidence was monitored by GPS ground surveys from 2008 to 2016 and Interferometric Synthetic Aperture Radar (InSAR) by other researchers. In this study, the SBAS-DInSAR is applied to monitor Subsidence in Semarang using ALOS-2 and Sentinel-1 SAR data. Both SAR datasets, ALOS-2 and Sentinel-1, are almost in the same observation period (2015 to 2023). This study presents the first application of SBAS-DInSAR using the ALOS-2 dataset. The updated Subsidence in Semarang City obtained by SBAS-DInSAR using ALOS-2 and Sentinel-1 is presented. The SAR dataset, ALOS-2, and Sentinel-1 show that the maximum accumulated Subsidence over eight years (from 2015 to 2023) is about 90-100 cm with an average subsidence velocity of about 11-12.5 cm/year. The subsidence area is mainly located in the north and northeast areas. The subsidence results obtained by ALOS-2 and Sentinel-1 coincide from spatial distribution and temporal transition points of view. The discrepancy between ALOS-2 and Sentinel-1 is less than 1 cm on average.