Seismic and Landslide Hazard Assessment Using Iterative Observation DInSAR: Insights from the 2022 Mw 6.1 Pasaman Earthquake, Indonesia

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This study used iterative observation DInSAR with Sentinel-1A imagery to analyze ground deformation and widespread landslides triggered by the 2022 Mw 6.1 Pasaman earthquake, revealing pre-seismic deformation and post-seismic slope failures.

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This preprint studies spatial and temporal evolution of ground deformation and earthquake-triggered landslides from the 2022 Mw 6.1 Pasaman earthquake in Indonesia using an iterative observation DInSAR workflow on Sentinel-1A, alongside Sentinel-2 for vegetation-related analysis. The authors reconstruct vertical displacement through pre-seismic, co-seismic, and post-seismic phases and report progressive interferometric fringe development and vertical deformation before the mainshock, followed by widespread post-seismic landslides, especially on Mount Talamau; they corroborate slope-failure patterns using coherence change detection, NDVI analysis, and landslide velocity models. Validation against CORS geodetic data gives an RMSE of 0.009 m, supporting reliability of the vertical displacement estimates. The paper explicitly notes it is a preprint and not peer reviewed, which limits confidence in the results pending journal evaluation. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Abstract Earthquakes, particularly those along active tectonic boundaries such as Indonesia’s Semangko Fault, often trigger cascading hazards like landslides. Accurate monitoring of earthquake-induced surface deformation and secondary hazards remains critical for disaster risk reduction, especially in mountainous regions. Using a multi-sensor geospatial approach, this study investigates the spatial and temporal evolution of ground deformation and landslide activity associated with the 2022 Mw 6.1 Pasaman earthquake. We apply an Iterative Observation Differential Interferometric Synthetic Aperture Radar (IO-DInSAR) technique to Sentinel-1A imagery, enabling the reconstruction of true vertical displacements across pre-seismic, co-seismic, and post-seismic phases. The results reveal progressive interferometric fringe development and vertical deformation preceding the mainshock, followed by widespread post-seismic landslides, particularly on the slopes of Mount Talamau. Coherence change detection (CCD), Normalized Difference Vegetation Index (NDVI) analysis from Sentinel-2, and derived landslide velocity models further corroborate spatial patterns of slope failure. Validation against CORS geodetic data yields a root mean square error (RMSE) of 0.009 m, confirming the reliability of vertical displacement estimates. Unlike traditional DInSAR, the IO-DInSAR approach captures temporally continuous deformation patterns, offering deeper insights into the develcopment of earthquake-related instability. These findings highlight the utility of iterative DInSAR analysis for enhancing our understanding of cascading seismic hazards and inform early warning strategies in tectonically active regions.
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Seismic and Landslide Hazard Assessment Using Iterative Observation DInSAR: Insights from the 2022 Mw 6.1 Pasaman Earthquake, Indonesia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Seismic and Landslide Hazard Assessment Using Iterative Observation DInSAR: Insights from the 2022 Mw 6.1 Pasaman Earthquake, Indonesia Demi Stevany, Masita Dwi Mandini Manessa, Tito Latief Indra This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7353311/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Earthquakes, particularly those along active tectonic boundaries such as Indonesia’s Semangko Fault, often trigger cascading hazards like landslides. Accurate monitoring of earthquake-induced surface deformation and secondary hazards remains critical for disaster risk reduction, especially in mountainous regions. Using a multi-sensor geospatial approach, this study investigates the spatial and temporal evolution of ground deformation and landslide activity associated with the 2022 Mw 6.1 Pasaman earthquake. We apply an Iterative Observation Differential Interferometric Synthetic Aperture Radar (IO-DInSAR) technique to Sentinel-1A imagery, enabling the reconstruction of true vertical displacements across pre-seismic, co-seismic, and post-seismic phases. The results reveal progressive interferometric fringe development and vertical deformation preceding the mainshock, followed by widespread post-seismic landslides, particularly on the slopes of Mount Talamau. Coherence change detection (CCD), Normalized Difference Vegetation Index (NDVI) analysis from Sentinel-2, and derived landslide velocity models further corroborate spatial patterns of slope failure. Validation against CORS geodetic data yields a root mean square error (RMSE) of 0.009 m, confirming the reliability of vertical displacement estimates. Unlike traditional DInSAR, the IO-DInSAR approach captures temporally continuous deformation patterns, offering deeper insights into the develcopment of earthquake-related instability. These findings highlight the utility of iterative DInSAR analysis for enhancing our understanding of cascading seismic hazards and inform early warning strategies in tectonically active regions. earthquake geological landslide DInSAR IO-DInSAR earthquake prediction Sentinel 1A Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 22 Jan, 2026 Reviewers invited by journal 26 Aug, 2025 Editor assigned by journal 13 Aug, 2025 Submission checks completed at journal 13 Aug, 2025 First submitted to journal 12 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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