Three-dimensional (3D) modeling of tsunami events is intended to promote tsunami safety. However, the developed 3D modeling methods based on Computational Fluid Dynamics and photorealistic particle visualization have some weaknesses, such as not being similar to the original environment, not measuring the wave’s end point, and low image accuracy. The method for 3D modeling of tsunamis that results from this research can fulfil those weaknesses because it has advantages, such as being able to predict the end point of waves, similar to the original environment, and the height and area of inundation. In addition, the method produces more detailed and sharper spatial data. Modeling in this research is conducted using Agisoft Metashape Professional software to a produce 3D orthomosaic from pictures taken with Unmanned Aerial Vehicle (UAV) technique or drone (photogrammetry), and 3ds max software is used for wave simulation. We take a sample of an area in Cilacap, Indonesia that was impacted by the 2006 southwest coast tsunamis and may be vulnerable to future big megathrust earthquakes and tsunamis. The results could be used to provide several benefits, such as the creation of evacuation routes and the determination of appropriate locations for building shelters.

Low impedance contrast between the shale-sand layer, which can be found in the situation where shale layer wrapped in the sand reservoir, is a challenging case for explorationist in characterizing sand distribution from shale layer. In this paper, we present the implementation of Poisson impedance in mapping sand distribution in Gumai formation, Jambas Field, Jambi Sub-basin. Gumai formation has become a prospective zone, which contains sandstone with strong laterally change. The characteristic of facies at Gumai formation, which is laterally changing, has been properly mapped based on the Acoustic impedance (AI) and Shear impedance (SI). These two impedances, which is yielded by performing seismic simultaneous inversion, is then combined to generate Poisson impedance. The Poisson impedance is conceptually formulated as a contrast between AI and a scaled SI with the scale is estimated from the gradient of the relationship between AI and SI. Our experiment shows that the Poisson impedance map is able to separate the sand distribution from the shale layer. Therefore the sand facies has been clearly delineated from the contrast of Poisson impedance.

The geomorphological understanding of earth dynamics, including the relationship between landforms and their processes, was one of the earliest and most specific contributions to disaster prevention. Disaster geomorphology is one of the approaches in disaster studies, which includes aspects of landforms, processes, and results of physical processes that have the potential and can cause disasters. The landform is of risk factors that can turn natural hazards into natural disasters and determines the damage that disasters can cause to human activities. Following the 2006 South Java Tsunami, infrastructural development occurred massively in the 2006 South Java Tsunami inundation areas. Several tsunami risk mitigation efforts were conducted but solely based on the 2006 tsunami scenario and ignored the existence of more considerable tsunami hazards from the Sunda Megathrust. This consideration may lead to an increasing risk of future tsunamis. We evaluate and appraise favorable and unfavorable geomorphological features to reduce the risk of future tsunamis. Pangandaran has a unique landform compared to other areas on the south coast of Java, and this landform has the potential to reduce future tsunami risk. Typical landforms studied include coastal plains, alluvial plains, Tombolo, tied islands, and structural hills. The results show that the morphological features of the Tombolo and the coastal plain area are categorized as high risk when a tsunami occurs. The tied island is categorized as a favorable morphology where these morphological units have the advantage of elevation and efficient distance to the tsunami risk zone. Evacuation facilities are also needed, especially in the coastal plain and Tombolo areas (with a height of >20 meters), to reduce disaster risk, particularly mortality caused by tsunami events.

On May 27, 2006, 05:54 am local time, a moderate crustal earthquake of magnitude Mw 6,3 struck the Yogyakarta province, especially in the Bantul regency in the south part of the province. The earthquake damaged or destroyed more than 400,000 houses and buildings and caused more than 5,700 people killed. Several earthquake stations recorded the ground vibration caused by the mainshock very well, except at the stations closest to the earthquake source, namely YOGI in Gamping, West of Yogyakarta, which experienced saturation due to significant vibration. Therefore, information about the maximum ground acceleration near the source is yet not known. We model the ground vibrations near the earthquake source using a stochastic Green’s Function approach to obtain information about the ground motions’ maximum amplitude. The earthquake source parameters we referred to is the moment tensor solution from the Harvard Moment Tensor. The calculations show that the amplitude is consistent with observations recorded at the BJI Banjarnegara (0.04g) and YOGI Yogyakarta (0.3g).

The southern coast of Java, Indonesia, is situated along the active Sunda subduction margin where raised coastal landforms may record the combined influence of relative sea-level change, wave processes, sedimentation, and vertical land motion. This study presents field-based RTK-GNSS topographic profiles from four coastal sites: Pantai Ajah, Kalijali, Kulon Progo, and Wingko. Profiles were used to locate terrace treads, risers, slope breaks, residual topographic highs, and possible raised coastal surfaces. The results show spatially varying coastal morphology. Pantai Ajah has a marked riser and probable terrace tread at about 7–8.5 m elevation. Kalijali shows a lower terrace-like surface at about 4–5 m, an upper surface at about 7–9 m, and a higher local topographic high at about 12–13 m. Kulon Progo is characterized by a low-elevation coastal surface that is only weakly expressed in the topography, whereas Wingko contains a distinct slope break and a broad landward surface at approximately 5–6.5 m elevation. Across the four profiles, broad low-gradient surfaces recur within two elevation ranges, approximately 4–6.5 m and 7–9 m. These ranges are treated as provisional morphometric groupings rather than correlated or coeval terrace levels. Higher isolated elevations are described as ridge-like or residual topographic highs whose origin and age remain unresolved. No direct chronological or sedimentological constraints are currently available, so correlations with Holocene or older sea-level highstands are only tentative. The results show the usefulness of RTK-GNSS profiling for the documentation of local coastal terrace morphology and for the identification of priority sites for future dating, sedimentological analysis, and coastal-hazard assessment.