Analysis of Existence and Faults Impact on Geological Disasters Using GGMPlus Data

The existence of faults can trigger various geological natural disasters because faults will react when an earthquake occurs and volcanic activity occurs, causing effects in the form of landslides, subsidence, ground movements, and other geological disasters. This research aims to analyze the existence and impact of local faults on geological disasters around the research location using GGMPlus data. A derivative filter is used to get FHD and SVD maps based on the gravity anomaly map. Fault analysis was carried out using a graph from the FHD and SVD map incisions, which were then correlated with each other. The incision graph of the meeting point between the maximum FHD value and the zero SVD value will be interpreted as a fault structure. The results show that there were several fault indication points; these points were then drawn straight lines to get the lineaments of the faults. The fault lineaments with the location of the landslide and subsidence events are correlated so that it becomes evident that the subsidence and landslide disaster in the Brau Hamlet, Batu City, area can be associated with local faults. Based on several previous research on determining faults in coastal areas, it is known that the areas crossed by the Palu-Koro fault have experienced many disasters, such as landslides, land movement and liquefaction. The existence of local faults in an area can increase the impact of damage when natural disasters such as earthquakes and landslides occur.


Introduction
Geologically, Indonesia is traversed by the Ring of Fire, causing Indonesia to have a lot of volcanoes and faults.The existence of faults can trigger various geological natural disasters because faults will react when an earthquake occurs and volcanic activity occurs, causing effects in the form of landslides, subsidence, ground movements, and other geological disasters.These geological disasters can occur in mountainous and coastal areas, and one of the causes is the presence of faults.So, it is necessary to analyse faults in mountainous and coastal areas to determine the influence of faults in different locations with the same impact and characteristics.When regional faults or volcanoes react, they will cause local faults to react, thus triggering ground movements [1].Generally, the position of buildings on fault lines tends to receive a greater impact, so fault mapping in an area is important as a disaster mitigation strategy and building planning.
The gravity method is one of the geophysical methods commonly used to identify faults.Gravity data information can be used efficiently in various geological problems related to the exploration of the 1321 (2024) 012003 IOP Publishing doi:10.1088/1755-1315/1321/1/012003 2 earth's crust, such as natural disaster mitigation, geothermal, and fault mapping.The gravity method has advantages in determining the density limits of subsurface rocks.The gravity method measures variations in the earth's gravitational field caused by differences in the rock mass density beneath the surface [2].Gravity data can be obtained by direct measurement or secondary data in the form of GGMPlus satellite data.One of the advantages of using satellite data is that it has wide area coverage and requires little time and cost.The data obtained from GGMplus is in the form of coordinate point data, Free Air Anomaly, and elevation.The measured gravity anomaly value is directly proportional to the density of the rock, where a high anomaly value identifies rock with high density and vice versa.Therefore, the use of the gravitational method is commonly used to map the density contrast under the surface, such as the distribution of faults in a study area.
The gravity method is suitable for determining fault structures because it can identify contrasting differences in rock density, such as identifying faults in Trienggadeng, Aceh [2].The fault area has unstable rock due to the presence of two rock densities with contrasting values in one location, so it is very susceptible to geological disasters such as ground movements [3].Ground movement is the movement of soil mass from its original position so that it can develop into a landslide if mitigation is not done immediately [4].Landslide disasters will be very dangerous if they occur in densely populated areas because they can damage infrastructure and cause casualties.This research aims to analyze the existence and impact of local faults on geological disasters around the research location using Global Gravity Model Plus (GGMPlus) data.The results of this study are expected to provide information regarding the dangers of faults in a location and recommendations for disaster mitigation for the local government and increase preparedness for the surrounding community.

Material and Method
The research was conducted in Brau Hamlet, Gunungsari Village, Batu City, East Java, Indonesia.The research data was obtained from the GGMplus gravity satellite with an area of 3 x 2.5 kilometres.The area focuses on Brau Hamlet with a distance between data points of 220 meters; the measurement points are designed in the form of a grid so that they can represent the entire study area (Figure 2).Geographically, Brau Helmet is located at 7°50'46.41"S and 112°29'44.45"Ewith an altitude of about 1080 masl.Several hills surround this Hamlet, so the potential for geological disaster can come anytime.
The measurement value of gravity for each region always varies because the earth is not a precise sphere and is considered homogeneous isotropic [5].Several components, such as differences in degrees of latitude, topographical conditions, and rock density, influence the acceleration value due to gravity.GGMPlus data obtained includes Free Air Anomaly data, elevation, coordinates, and Gobs.GGMplus data is satellite data obtained from the three main constituents of Gravity, namely, the GOCE and GRACE satellites with a spatial scale from 10,000 km to 100 km, the EGM2008 satellite with a spatial scale of 100 km to 10 km, and topographical gravity from 10 km until 250 m.The data from the 3 satellites were processed using the approximative method, and the analysis process was carried out spectrally using the discrete Fourier technique to obtain a degree of variance model [6].
This method is ambiguous due to the many noise or disturbing factors in the data retrieval process, so it is necessary to make some corrections to remove the noise.Correction of data in the processing of the gravity method includes Terrain, Bouguer, and Free Air Corrections.The results obtained from the correction process are a complete bouguer anomaly map; based on a complete bouguer anomaly map, an anomaly can be separated using a butterworth filter.Separation of these anomalies aims to obtain residual and regional anomalies.The research implementation is shown in Figure 1 below.Analysis is performed to determine the presence of faults based on the residual anomaly map obtained from First Horizontal Derivative (FHD) and Second Vertical Derivative (SVD).FHD is a horizontal change in the value of the gravity anomaly, which can show the maximum and minimum values at the anomaly contact so that it is suitable for determining the presence of a fault at the geological structures.Meanwhile, SVD is used to reveal shallow sources of anomalies.SVD is an analysis that can describe residual anomalies associated with shallow structures [7].The residual anomaly map obtained is then filtered with order 1 derivatives on the x and y axes using the Oasis Montaj software, and then the GridMath option is added to get the FHD.As for the SVD, results are obtained from the second order derivative filter on the Z-axis.After obtaining the FHD and SVD maps, a path incision is made, and the analysis process uses a Microsoft Excel curve to identify the presence of faults and the type of fracture.[8], because it has the same concepts and methods and only differs in the research location.After analyzing the results of determining faults in the mountains and coasts, the influence of faults on the type of disaster and the level of risk posed is then correlated.

Fault in Mountainous
The research area is included in two regional geological maps, namely the regional geological maps of Kediri and Malang Quadrangle.Based on the geological map of the Kediri and Malang Quadrangle, the study area is included in the Old Anjasmara Volcanic Formation (Qpat).Old Anjasmara Volcanics Formation (Qpat) in Figure 3 was formed during the Quaternary period, which has an Early Pleistocene age.The formation consists of several rock types: volcanic breccia, tuff breccia, tuff, and lava.Based on observations at the location, breccia and tuff rocks were found with brown soil weathering.Hills dominate the morphological conditions of Brau Hamlet, with a height of around 1034 meters above sea level.A complete Bouguer anomaly map (Figure 4a) and residual anomaly (Figure 4b) are obtained based on the correction results.High gravity anomaly values are marked in pink and low gravity anomaly values are marked with dark blue, where the value of the gravity anomaly is directly proportional to the density of the rock.On the complete bouguer map, low density is shown in green-blue with a value range of 83.9 to 85.1 mGal; then for high density yellow-pink, the value range is 85.3 -86.8 mGal.Low anomalies on the complete Bouguer map are mostly in the southeast direction, and high anomalies are in the northwest direction, so it shows a boundary meeting of high and low anomalies, which is quite contrasting.Residual anomaly maps describe rock structures with shallow depths and irregular patterns because shallow geological structures' effects vary widely.The resulting residual anomaly map has a low anomaly with an anomaly value range of -0.5 to -0.1 mGal, while a high anomaly has a value range of 0.0 mGal to 0.4 mGal.The residual anomaly is used as a reference in filtering derivatives because this anomaly map has a shallow nature, making it suitable for making FHD and SVD maps.The FHD map is obtained from the first derivative of the residual map horizontally.This method can determine the existence of a fault where a high FHD value indicates the presence of a structure that is the boundary between high anomaly and low anomaly.The results of the FHD and SVD maps are shown in Figure 5.
The FHD map has anomaly values varying from low to high of 0.00025 to 0.00048 mGal.The distribution of anomaly values on the FHD map can indicate the presence of a lithology type contact horizontally.Meanwhile, the SVD map is the second derivative of the residual map vertically.This second vertical descent is carried out to identify the presence of shallow faults.The SVD values obtained were in the range of 0.0000646 to 0.0000322 mGal.The boundaries of high and low SVD anomaly values at close distances can indicate the presence of fault structures or shallow faults.Based on the SVD map in Figure 5b.there is a confluence of gravity anomaly values that contrast between low (blue) and high (red) anomaly values.The meeting boundary indicates that in that area, there are differences that separate the two regions.These contrast anomaly encounters can be identified by making several incisions to determine the subsurface lithology conditions (Figure 5).Derivative analysis of the FHD and SVD maps is used to identify the presence of a fault based on the lithology conditions obtained from the incisions on the two maps.The incisions are marked with straight black lines in Figures 5 (a) and (b).The values obtained from the FHD and SVD maps are then displayed in graphical form using Microsoft Excel, then an analysis of the graphs obtained from the incisions is performed.Determination of the existence of a fault from the graph is done by comparing the FHD and SVD values.The existence of a fault structure can be detected if the maximum value on the FHD section correlates with a value close to or equal to zero on the SVD section.The correlation of the two values is then interpreted as a fault structure.The results of the process of graphic analysis and identification of faults from the incisions in Figure 5 are presented as a 2D map that aims to determine the lithology of the constituent rocks.The model is shown in Figure 6 with an error of 2.068%; this value is low.Based on the 2D model, it is known that the constituent rocks at the study site consist of Clay, Tuff Breccia, and Andesite.Determination of the fracture type can be seen from the maximum and minimum values on the SVD cross-section.If the measured positive maximum value of SVD is less than the negative minimum value of SVD, then an upward fault is indicated [5].
Identification of fault lineaments is carried out by combining points indicated to have fractures based on the results of the incision analysis in Figure 6.Based on Figure 7b, it is found that in the study area, there are 2 fault alignments from north to south which are marked by the dotted lines F1 and F2.These two faults are interpreted as local faults with shallow depths.Based on the fault lineament analysis obtained, it can be connected between the existence of the fault and several disaster events such as landslides and subsidence.Based on Figure 7, the big circle (High Damage Area) shows areas with quite high disaster intensity, such as landslides and subsidence, causing damage to residents' houses.This position is on the fault lineaments, so it can indicate that the fault lineaments can trigger greater damage.In addition, at the research location, a spring was also found in a blue circle in the direction of the F2 fault indication, so this is supporting evidence that there is a local fault in Brau Hamlet.These conditions require the community to increase awareness of natural conditions.In addition, the government's role is needed in provide education regarding the geological conditions in the study area.2020), during the 2018 Palu earthquake, there were many landslides in coastal areas, as shown in Figure 9(a) [10].The research conducted by Kusumawardani et al. (2021) shows that after the 2018 earthquake in Figure 9(b), it can be seen that liquefaction occurred in a large area [11].This case can be evidence that the presence of active faults in an area can increase the risk of damage from natural disasters; earthquakes can be very destructive if there are faults in the area.Then faults can also increase the risk of other natural disasters, such as landslides and liquefaction, because the soil in the area becomes unstable and fragile.Based on several studies, it can be correlated between faults that occur on the coast and faults in the mountains.The correlation results of faults in both areas show the same characteristics, resulting in geological disasters such as liquefaction, ground movement, and landslides, thereby increasing the risk in both areas.The meeting of oceanic crust with continental crust causes oceanic crust, which has thinner plates to move downwards.The meeting of these two plates is called a subduction zone, where when movement occurs in this zone it can cause earthquakes, tsunamis and volcanic eruptions.When an earthquake occurs, the vibrations can reach hundreds of kilometres depending on the size and depth of the earthquake's epicentre.Apart from that, volcanic activity can also cause ground vibrations.Vibrations from earthquakes and volcanic activity will spread in all directions and then resonate on local faults.The local faults that resonate due to the movement of tectonic plates can increase shaking when an earthquake occurs [12], giving rise to other natural disasters such as ground movements, landslides and other geological disasters.This can indicate that areas with faults can increase the occurrence of natural disasters.

Conclusion
The presence of faults can be determined using the gravity method by analysing the FHD and SVD maps obtained from the Residual Anomaly Map.Based on the correlation graph of FHD and SVD values, it was found that there were indications of local faults in the Brau Hamlet, Batu City.When the measured positive maximum value of SVD is smaller than the minimum negative SVD value, it indicates the presence of an upward fault.If a straight line is drawn, the indication of the existence of the fault is parallel to the landslide point and several damaged residents' houses.The fault lineaments with the location of the landslide and subsidence events are correlated so that it becomes evident that the subsidence and landslide disaster in the Brau Hamlet, Batu City, can be associated with local faults.Based on several previous studies regarding determining faults in the coastal area of Palu City, it is known that the area crossed by the Palu-Koro Fault has experienced many disasters such as landslides, land movement and liquefaction.The correlation between faults located on coastal and mountainous shows that both have the same properties, and they can increase the risk of geological disasters.When vibrations occur from the movement of tectonic plates or volcanic activity, they can resonate with faults, thereby increasing fault activity.The research that has been done needs to be studied further to obtain subsurface theories and models in more detail.

Figure 2 .
Figure 2. Survey design at the research location.

Figure 6 .
Figure 6.2D Model of slice A-A'.

Figure 7 .
a. Overlay the alignment of the local fault map with the Brau Hamlet map, b.Map of SVD and slicing with fault lineaments.

3. 2 .
Fault in Coastal AreaDetermining faults in coastal areas is based on research conducted by Permana et al. (2022) using GGMplus gravity data in Palu City, Central Sulawesi, Indonesia[8].The method used is Gravity with GGMplus data, including Contour Bouguer Anomaly modelling, anomaly separation, and derivative analysis.In derivative analysis, the process of deriving the model horizontally and vertically is carried out.The first derivative horizontally is called FHD and the second derivative vertically is called SVD.The results of the two derivatives are correlated to show the maximum FHD and SVD values, where the maximum FHD value is correlated with a value close to or equal to zero in the SVD section.

Figures 8 (
Figures 8 (a) and (b) show the correlation results between FHD and SVD maps to determine faults.The meeting of the maximum values of 0.00557 -0.01087 mGal on the FHD map in the western area