Java Island, located in Indonesia, is the country’s main island, with a population of 150 million, more than half the population of the country. There are at least four big cities located on the island that have seen fast development in the last 30 years. The land subsidence (LS) issue caused by groundwater overexploitation, compaction, and geological setting, has been known on the island for more than 20 years. However, past studies have mostly focused on one particular important area, while the big picture of LS on the whole island is often overlooked. This study utilized Sentinel-1 Synthetic Aperture Radar (SAR) data from 2017 to 2023, analyzed using Small Baseline Subset (SBAS) interferometry, to map LS across Java Island. We used DEMNAS to eliminate the topographic signal. We found ten regions with a noticeable LS rate, affecting nearly 60 million people who reside in the LS zones, namely, Serang, Greater Jakarta, Cianjur, Bandung, Cirebon, Brebes and Tegal, Pekalongan, Greater Semarang, Surabaya, and Sidoardjo. The highest rates and the large coverage of LS were observed in Greater Jakarta (up to 150 mm/year), Bandung (200 mm/year), Semarang (160 mm/year), and Pekalongan (up to 110 mm/year). LS was also detected in smaller areas or districts, such as Serang, Cianjur, Cirebon, Brebes, Tegal, Surabaya, and Sidoarjo, with rates ranging from 60 to 140 mm/year. The two areas of Cianjur and Brebes, which have never been mentioned in previous studies, show LS rates of about 80 mm/year and 70 mm/year, respectively. The LS rate in all areas was shown to be linear over time, except in Pekalongan, which shows rate deflation after 2021. We also found that most affected regions are urban and industrial zones, indicating a strong correlation with anthropogenic activities. LS leads to widespread socioeconomic and environmental impacts, including damage to infrastructure, increased flooding, and reduced groundwater capacity.

This study evaluates the impact of incorporating lateral mass density variations into geoid models for Java, Indonesia, aiming to enhance the accuracy of regional geoid determinations. Geoid models have traditionally used a constant density assumption; however, Java’s varied topography and geological complexity suggest that density variability may significantly influence geoid accuracy. Employing the Stokes–Helmert method combined with the remove–compute–restore (RCR) technique, we calculated geoid models using both constant density and laterally variable density from the UNB TopoDens model. The models were validated against GNSS/leveling data, showing that while lateral density variations had limited effects along flat topographic profiles, they introduced notable discrepancies in regions with considerable elevation changes. Specifically, variable density models exhibited discrepancies of up to 30 cm in regions with complex terrain, underscoring the importance of selecting appropriate density models for precise geoid computations in heterogeneous landscapes. Nonetheless, a comprehensive validation using geometric geoid models is required to confirm the accuracy improvements across the entire region.