Land subsidence is not a new phenomenon for Jakarta and Semarang areas. According to some publications, the value of Jakarta’s subsidence may reach 2-4 meter in certain place. Meanwhile, more than 2 meter of subsidence is taking place in northern part of Semarang. Some techniques are being used to derive land subsidence information in these areas such as repeated leveling measurements, GPS surveys, and InSAR measurements. The impact of land subsidence in Jakarta and Semarang could be seen in several ways, such as sea inundation (“Rob” in Javanese), problem on infrastructures, the wider expansion of flooding areas, etc. Cracking on housing, street, “sinking” on the bridges and dyke, problems on drainage are examples of infrastructures problems due to the land subsidence. Huge costs have already been spent to fixing those infrastructures problems both in Jakarta and Semarang. Since mostly liniear pattern of land subsidence are recognized in both area today and probably in the next years to come, in this case the impact especially on infrastructures are probably will getting worse. Insight look the subsidence impact to the infrastuctures in Jakarta and Semarang area would raisen the concern, and become key for adaptation and mitigation.

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.

The Quasi-Zenith Satellite System (QZSS) is the recent Japanese satellite positioning system to enhance the positioning accuracy in Japan’s urban areas. Additionally, they provide precise orbit and clock corrections and can be obtained through their experimental signals (LEX), streaming access, and published site. Multi-GNSS Advanced Demonstration tool for Orbit and Clock Analysis (MADOCA) is one of the precise products offered in QZSS services that can be obtained on a global scale. In this study, we evaluated the performance of MADOCA orbit and clock corrections, particularly for real-time positioning applications using LEX signals. Based on the simulation, we predict that 16 countries in the East Asia and Oceania regions will gain the maximum benefit of the LEX signals. However, we stress that one may have difficulties decoding the LEX signals at regions where only one QZSS satellite is observed. During our sailing expedition at Sumatran Sea, we could only decode up to 37 % LEX signals for the observation period. It profoundly increased up to 95 % at Sulawesi Strait where at least three QZSS satellites with an elevation angle of, at its minimum, 40° were observed. The orbit and clock accuracy is estimated to be 5.2 cm and 0.6 ns with respect to International GNSS Service (IGS) final products. Our simulation of using the Real-Time Precise Point Positioning (RTPPP) method revealed that the accuracy of the corresponding positioning applications was less than one decimeter. Further, we compared the MADOCA products for RTPPP applications with Apex⁵ positioning solutions in static field observations. The positioning accuracy for MADOCA-RTPPP during the field observations was estimated to be centimeter to decimeter level and is slightly worse than Apex⁵ positioning solutions. Nevertheless, we highlight vast positioning applications using MADOCA-RTPPP, e. g., survey and mapping, smart agriculture, and offshore engineering navigation.

Land registration is an important program in asset legalization with the vast land resources owned by Indonesia. The reality is that there are 48 million certificated lands out of an estimated 126 million certificates throughout Indonesia, so the Ministry of Agrarian Affairs and Spatial Planning/National Land Agency (ATR/BPN) made a breakthrough through the Complete Systematic Land Registration (PTSL) program. The grouping mechanism of the PTSL program is divided into four clusters, namely K-1, K-2, K-3, and K-4. Land parcels included in K-4 have problems, namely that they have been registered but not mapped/mapped incorrectly, so the idea of modeling the K-4 typology is needed for accelerating the improvement in land data quality (KW). The research location is in Bandung Regency, which is included in the top five land offices with the highest number of K-4 in West Java Province. This research method uses a mixed method, namely quantitative with a Slovin approach for the identification and clustering of K-4 typology and descriptive qualitative for justification of typology modeling in multiple aspects. The results of K-4 typology modeling were 128 clusters based on seven types of data criteria and obtained 4 clusters that matched the data sample, namely T-1, T-43, T-63, and T-128. The four clusters were justified against the K-4 concept in the Ministry of ATR/BPN, the FFP-LA concept, and the PESTLE framework. Dissemination of K-4 typology modeling is a breakthrough that can be implemented by the Ministry of ATR/BPN and its staff in various regions and the role of multi-concepts in this research can be an input for improving the K-4 concept that has been in effect so far.

Three-dimensional (3D) models are indispensable in managing, operating, maintaining, and repairing piping instrumentation activities in oil and gas companies. 3D models are expected to provide more interactive and representative information according to actual objects. Several technologies that can be used to generate piping instrumentation 3D maps are Terrestrial Laser Scanner (TLS) and Handheld 3D Scanner (HS). This study aims to create a 3D model of piping instrumentation using a combination of TLS and HS and analyze the results of data validation used for modeling. The results showed that a 3D modeling of piping instrumentation could be generated accurately using a combination of TLS and HS technologies. Merging between the two data is carried out through a cloud-to-cloud registration process based on the geometry of the object by considering the selection of reference data, the similarity of the scale factor, the unit of measure, and the overlap of the two data. The registration error generated in combining these two methods is less than 0.003 m. The resulting model still has drawbacks, which is the absence of coding for the pipe caused by the unavailability of the Piping and Instrumentation Diagram (P&ID) during modeling. The geometric validation of the model size value using reference data and the field size has the largest absolute difference of 0.0034 m with an average absolute deviation of 0.0016 m.