Reducing Landslide Risk in Yogyakarta Through Three-Dimensional Gravity Modeling as A Proactive Disaster Risk Reduction Strategy

Landslides in the Special Region of Yogyakarta, Indonesia, are widely recognized as being triggered by steep topography, active tectonics, and seasonal monsoon rainfall. however, conventional hazard assessments frequently overlook critical subsurface geological controls such as fault zones, weathered bedrock interfaces, and fractured basement rocks—that mayr serve as primary sliding surfaces. This study directly addresses this limitation by developing a novel three-dimensional gravity-based model to enhance landslide susceptibility mapping and support regional mitigation strategies. High-resolution (~200 m) GGMplus gravity data were processed using Oasis Montaj™ software, with regional-residual anomaly separation performed through upward continuation to 5 km and second-order polynomial surface fitting. Subsequently, three-dimensional density inversion was applied to delineate shallow subsurface structures influencing slope stability. The total Bouguer anomaly ranges from –18.6 to +181.4 mGal: strong positive anomalies (>+100 mGal) are concentrated over Mount Merapi, reflecting dense, unweathered volcanic intrusions and lava flows, while pronounced negative anomalies (<–10 mGal) dominate central and eastern sectors, correlating with thick colluvium, weathered volcaniclastic deposits, and fractured basement rocks. The residual anomaly map (–2.5 to +2.6 mGal) effectively isolates shallow density contrasts, revealing that 82% of recorded landslides (n=142 events, 2010–2022) spatially coincide with low-density zones (<–1.0 mGal), particularly clustered along the NW–SE-trending Opak Fault interpreted as a zone of fault gouge, brecciation, or fluid-saturated fractures that critically control slope failure mechanics. Conversely, positive residual anomalies (>+1.0 mGal) correspond to geologically stable domains underlain by dense intrusions or compacted layers. This study demonstrates that 3D gravity modeling provides a powerful, non-invasive tool for identifying landslide-prone zones governed by hidden subsurface architecture, offering significant practical value for land-use planning and disaster risk reduction in complex volcanic terrains.