Utilization of Sentinel-1 satellite imagery data to support land subsidence analysis in DKI Jakarta, Indonesia

Mohammad Ardha; Argo Galih Suhadha; Atriyon Julzarika; Fajar Yulianto; Dipo Yudhatama; Rofifatuz Zulfa Darwista

doi:10.15243/jdmlm.2021.082.2587

Utilization of Sentinel-1 satellite imagery data to support land subsidence analysis in DKI Jakarta, Indonesia

Mohammad Ardha, Argo Galih Suhadha, Atriyon Julzarika, Fajar Yulianto, Dipo Yudhatama, Rofifatuz Zulfa Darwista

J. Degrade. Min. Land Manage. , pp. 2587-2593

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DOI https://doi.org/10.15243/jdmlm.2021.082.2587

Abstract

Land subsidence had been a significant problem in DKI Jakarta and Semarang, with at least 20 kilometres of roads affected. Repairing them will require at least US $ 1 million per kilometre. Land subsidence monitoring has been carried out using terrestrial methods (GPS and levelling), which are believed to have a high degree of accuracy. The high accuracy of the terrestrial method results in a lack of precision over a large area. On the other hand, remote sensing technology as a non-terrestrial method has developed to monitor land subsidence which can produce high precision over a large area. This study aimed to test the Sentinel-1 satellite data using the Differential Interferometric Synthetic Aperture Radar (DInSAR) method in monitoring land subsidence in DKI Jakarta. DInSAR is a method in Remote Sensing that utilizes radar sensors to analyze the phase differences of a SAR data pair that have different times of capture and have been catalogued to obtain displacement along the area of collection. The results showed that the North Jakarta area experienced the highest land subsidence in the entire Jakarta area. The annual average rate from 2017-2019 is 3.4 cm. The value of 3.4 cm is the average value of all samples in the North Jakarta area. The second area where high land subsidence is West Jakarta, where the maximum amount value of subsidence is 2.8 cm. The accuracy-test results with the MONAS test point showed that the difference between field data and DInSAR results was ± 6.5 cm. The results of this research indicate that the DInSAR method is quite capable of describing land subsidence in the DKI Jakarta area with a relatively good level of precision.

Keywords

DInSAR; Jakarta; land subsidence; remote sensing; Sentinel-1

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