講演情報
[U16-P02]Volcanic Deformation Monitoring Using Sentinel-1 with Differential Interferometry Synthetic Aperture Radar (DInSAR) Method (Case Study: Mount Lewotobi, East Nusa Tenggara)
*Aswar Syafnur1、Andi Aini Rachmi2、Samsu Arif1、M. Mirnayani3 (1.Geoinformatics Laboratory, Department of Geophysics, Faculty of Mathematics and Natural Sciences, Hasanuddin University、2.Program Study of Geophysics, Department of Geophysics, Faculty of Mathematics and Natural Sciences, Hasanuddin University、3.Department of Geodetics Engineering, Faculty of Engineering, Universitas Gadjah Mada)
キーワード：
Lewotobi Volcano、DInSAR、Volcanic Deformation、Disaster Mitigation
Lewotobi is one of Indonesia’s active volcanoes with a high hazard potential. Monitoring ground deformation is a critical indicator in assessing volcanic activity, especially in the pre- and post-eruption phases. Remote sensing technology, such as DInSAR enabling wide-area and high-precision deformation monitoring, even at night. Objective. This study aims to monitor and analyze the vertical deformation of Lewotobi using the DInSAR method with Sentinel-1 data, and to identify the spatial distribution of inflation and deflation as part of volcanic hazard mitigation. This research uses 17 pairs of Sentinel-1 satellite imagery processed using the Differential Interferometry Synthetic Aperture Radar (DInSAR) method. Data processing includes coregistration, interferogram generation, phase unwrapping, conversion to displacement, and terrain correction using SNAP and QGIS software.The results show significant deformation in the form of inflation and deflation, especially on the northeastern slope of Lewotobi. The maximum inflation reached +0.241 m, and the minimum deflation reached -0.277 m. The deformation patterns strongly correlate with eruption events and seismic activity reported by PVMBG during the observation period. This study demonstrates that the DInSAR method is effective in monitoring surface deformation of Lewotobi. The research objectives were achieved by successfully detecting the magnitude and spatial distribution of inflation and deflation. These findings serve as a valuable basis for early warning systems in volcanic disaster mitigation.