Integration of Topography Map and Land Use Change Modeling for Sustainable Tourism Development in Merapi Volcano, Indonesia

The aim of this study is to develop lahar hazard vulnerability as a warning system by introducing radar-rainfall observation to data mining technique of Naïve Bayes Classifier (NBC). NBC is used to estimate lahar occurrences based on the posterior probability of rainfall, topographic factor, soil moisture, and soil type as predictors. Rainfall intensity and working rainfall were obtained from a weather radar. The soil moisture is derived from SMAP satellite imagery. A river on Mount Merapi, a very active volcano in Indonesia, was selected as the target basin. Observed rainfall and recorded lahar events in Gendol River from October 2016 to February 2018 were divided into a training dataset and a testing dataset. Qualitative evaluation through visual assessment of the hazard map product reveals that the model could estimate the occurrences of lahar. The performance of the model in terms of accuracy, Brier score, and quantitative dichotomous quality indices showed a reasonable skill. The study suggests that the NBC technique is advantageous for estimating lahar occurrences that are displayed on hazard maps. This work is expected to contribute to debris flow hazard mitigation by the data mining approach in volcanic regions.

The arc magmatism and volcanic activity in Java are dominated by the subducting plate of Indo-Australian into the Eurasian plate. Merapi volcano is located in Central Java and known as one of the most active volcanoes in the world. Several studies have tried to estimate the magma reservoir zone in Mt. Merapi and suggested multiple layers of reservoirs with the shallow one at 1-2 km and a deeper at 6 -9 km or 15 km. The Low-Frequency Passive Seismic is one method to analyze the frequency spectrum below the recording station. Previous related studies show a promising a relation between hydrocarbon reservoir and higher amplitude at vertical component at a frequency between 0.1 – 6 Hz. An observation at the volcano sites have also been reported to display a different spectrum amplitude at the vertical component. This study exploited the same method in LFPS to analyze the frequency spectrum at Mt. Merapi and Mt. Merbabu. We use seismic data from the DOMERAPI temporary seismic network installed in the neighborhood of Merapi and Merbabu volcano. We analyze 53 broad-band seismometers data from October 2013 to mid-April 2015. We also add several stations from MERAMEX network instruments to compare spectrum analysis outside the Merapi and Merbabu volcano. We also removed some tele-seismic and regional events from the data to better analyze the LFPS signal. We have seen a higher amplitude in vertical component near Mt. Merapi and will proceed to analyze all stations.

With the increasing concerns in developing methodologies for Reducing Emissions from Deforestation and forest Degradation (REDD) projects, there is a need to understand the characteristics of existing Land‐Use/Cover Change (LUCC) modules. This research presents a modular framework for assessing predictive accuracy of business‐as‐usual deforestation in the future by comparing two existing approaches: GEOMOD Modeling (GM) and Land Change Modeler (LCM). The comparison uses data from a case study in Chiquitanía, Bolivia. Data from 1986 and 1994 are used to simulate land‐cover of 2000; the resulting maps are compared with an observed land‐cover map of 2000. GM and LCM simulate business‐as‐usual deforestations at the pixel level. The model structures of GM's linear extrapolation and LCM's Markov Chain are compared to review quantity of LUCC; and the model structures of GM's empirical frequency, LCM's logistic regression, and LCM's multilayer perceptron are compared to review (spatial) allocation of LUCC. Relative operating characteristics, figure of merit, and multiple resolution analysis are employed to assess predictive accuracy of multiple transition modeling. By design, GM lacks the potential to model multiple transitions, and the LCM's multilayer perceptron may produce different results for each simulation due to its stochastic element. Based on the model structure and predictive accuracy comparisons, the LCM seems more suitable than the GM for a REDD application. When a project is to employ a predictive method for its spatially explicit baseline setting, then it is highly recommended to use the proposed framework to assess accuracy of the baseline as part of a project design document.

The existence of Mount Merapi in Sleman Regency makes the agricultural land in the area fertile and that becomes the attraction for humans to occupy the region. A high population growth will lead to the residents demand of the availability built-up land higher, that makes the environmental carrying cappacity in Sleman Regency decrease. However, the volcanic activity of Mount Merapi becomes a threat to the people who live in the area of Disaster Prone Areas of Mount Merapi. Predictions on the availability of land as well as the relation to the disaster-prone areas, and the carrying capacity of the environment needs to be done. 2007 – 2017 population data and Landsat 7 ETM + 2007, 2012, and Landsat 8 OLI 2017 imagery will be used in this research as variable in the spatial dynamics model. Meanwhile, physical and accesibility data such as slope, distance from the river, distance from protected area, distance from road, and distance from the center of economic growth will be used as limiting factor of built-up land. Environmental carrying capacity can be observed through a dynamic system model of the relationship between population growth and land availability within the period of 2007 - 2100, then made into the spatial dynamics model to know it’s spatial stance. The results of this model show that built-up land increasing every year, packed areas that are suitable for built-up land first, then encroach on areas which not suitable for built-up land and Mount-Merapi Disaster-Prone Areas.

Simulation of eruption material flow using probabilistic model based on the Monte Carlo algorithm was conducted in this research. The simulation result was used to support the creation of zoning map of volcanic hazards and the estimation of building number which has possibility to be impacted by the Merapi Volcano eruption. Input data for the simulation was Digital Elevation Model - Shuttle Radar Topographic Mission (DEM-SRTM) with a spatial resolution of 30 meters. In addition, GeoEye satelit imagery in 2009 was used to renew settlement information of the RBI map from BAKOSURTANAL. The simulation result of material flow eruption was overlaid with building area information to estimate the magnitude of eruption impact. The simulation results from this research has similar pattern and similar eruption material distribution with the reference map (volcanic hazard map of Merapi). The flow of Merapi eruption material generally leads to the south through the Gendol Rivers to Cangkringan, and to the southwest ward through the Putih Rivers to Srumbung. Material flow eruption is shown in height simulations 2 meters and 7 meters. The wider and widening of the of simulation models material flow eruption generated, the greater impact on the settlements in the vicinity of Merapi Volcano. Key word: Simulation of eruption material flow, DEM-SRTM, volcanic hazard, Merapi Volcano

Borobudur, a basin under volcanic influence: 361,000 years BP to present

Effective evacuation planning in volcanic areas requires real-time spatial awareness, community integration, and algorithm validation. This study aims to introduce SVACO-GIS, an innovative system that integrates Ant Colony Optimization (ACO), Geographic Information Systems (GIS), and the Sister Village framework to optimize evacuation routes under volcanic hazard conditions by identifying safe and efficient evacuation routes and strengthening community-based evacuation planning. The research applies the SVACO-GIS approach using a multi-parameter asymmetric heuristic matrix that incorporates slope, river distance, red zone exclusion, shelter readiness, and population density to better represent real-world constraints and safety priorities. Simulation results show that the application of SVACO-GIS produces structurally different evacuation route patterns compared to the shortest path-based approach. Routes optimized with SVACO-GIS consistently avoid major river corridors and areas with high slope gradients previously identified as high-risk zones in the context of Mount Merapi eruptions. The resulting evacuation network is directional and does not allow movement back toward zones with higher hazard levels, aligning with the one-way evacuation principle of the Sister Village system. The integration of local wisdom with intelligent spatial computing improves evacuation efficiency and sets a replicable standard for disaster preparedness in other high-risk geographies. These findings suggest that SVACO-GIS can support more informed decision-making, strengthen the resilience of vulnerable communities, and guide the development of intelligent evacuation systems in volcanic regions in the future

Mount Merapi, located on the border of Central Java and the Special Region of Yogyakarta, and Mount Marapi in West Sumatra are active volcanoes. Eruption activities will have positive and negative impacts on the surrounding environment. The eruptions of Marapi on December 3, 2023, and Merapi on March 4, 2024, caused severe damage to road infrastructure, buildings, bridges, and settlements and resulted in casualties. This article describes the experiences of communities after the eruption of the two volcanoes. This research uses a combination of literature review and field observation methods to analyze how communities in the Mount Merapi and Mount Marapi areas prepare for disasters. The results of this study show that to increase community resilience to volcanic disasters and flash floods triggered by Mount Merapi and Mount Marapi, collaboration between the government, disaster agencies, and local residents is essential. Measures that can be taken are proactive evacuation protocols, infrastructure development such as sabo dams, and continuous education to increase awareness and preparedness. Recommendations include more intensive cooperation, educational initiatives, and strategic relocation from high-risk zones to effectively protect vulnerable communities.

Merapi is a two-sided, paradoxical volcano: on the one hand 1.8 million people live on its flanks. It is one of the most densely populated volcanoes on Earth, with population densities averaging 764 inhabitants per square kilometre within a 10 km radius from the summit. The main reasons for the high densities are land resources and associated livelihoods from agriculture, livestock, sand mining, and tourism. On the other hand, Merapi is also one of the world’s most active volcanoes. Dome-collapse pyroclastic density currents (PDCs) occur every few years (e.g. 1994, 2002, 2006), and more violent explosive episodes are generated with an average recurrence interval of several decades (e.g. 1872, 1930, 2010). Risk management at Merapi is based on volcanic hazard zonation (called KRB I, II, and III, from the less exposed to the most exposed), derived from its eruptive history. Since its first publication by the Volcanological Survey of Indonesia in 1978, the danger map has been updated twice, in 2002 and after the deadly eruption of Merapi in 2010. Most of the information is provided by scientists during the ‘raising awareness program’ phase and achieved in the framework of a Community-Based Disaster Risk Management (CBDRM), which empowers communities with self-developed ways of coping with crises due to natural hazards. In periods of emergency, the Center for Volcanology and Geological Hazard Mitigation provides four warning levels of volcanic activity. In 2010, Merapi produced its largest eruption since 1872, damaging around 12,000 buildings, claiming 367 lives, including 200 directly by PDCs, and triggering massive evacuations of up to 400,000 people, as counted in the evacuation camps.KeywordsMerapiVulnerabilityCapacitiesLand resourcesLivelihoodsRisk and crisis management

Volcanic Hazards, A. Sourcebook on the Effects of Eruptions: by R.J. Blong. Academic Press, Inc., Publishers, Orlando, FL, U.S.A., 1984, xvi + 424 pp., hardback: US$66.00/paperback US$49.50

Indonesia, home to some of the world’s most active volcanoes, faces a challenge in balancing tourism growth with disaster risk mitigation. This study explores the critical role of communication in reducing disaster risks in volcanic tourist destinations, focusing on Mount Merapi in Yogyakarta and Mount Agung in Bali. A qualitative research approach with a comparative case study design was employed. Data were collected through in-depth interviews with disaster management authorities, tourism agencies, community leaders, tourism village managers, and tourism operators in both study locations. Additional data were obtained from policy documents, disaster communication guidelines, and official reports related to volcanic risk management and tourism. Thematic analysis was applied to identify patterns of communication practices, stakeholder relationships, and coordination dynamics. Data triangulation across sources and document analysis was conducted to enhance the validity and reliability of the findings. The findings reveal that disaster risk communication in volcanic tourism destinations remains fragmented, particularly between disaster management institutions and tourism actors. While culturally embedded communication practices and community-based mechanisms effectively enhance preparedness among local residents, they are not systematically translated into communication formats accessible to tourists. Consequently, tourism actors often assume informal intermediary roles in conveying risk information to visitors without sufficient institutional support. This structural gap generates uncertainty during volcanic crises and poses challenges for tourist safety and destination trust. This study recommends the integration of tourism stakeholders and culturally grounded communication practices into formal disaster risk communication frameworks. By positioning disaster risk communication at the intersection of disaster governance, tourism governance, and local cultural systems, the study offers an original empirical and conceptual contribution to the literature on disaster risk reduction and sustainable tourism. The findings provide evidence-based insights to support the development of more inclusive, context-sensitive, and sustainable risk communication strategies for community-based tourism destinations in volcanic regions.

Mount Merapi, located in Indonesia, is an active volcano that poses a significant threat to the surrounding communities. Vegetables, including chili, are grown in the disaster-prone areas surrounding Mount Merapi, despite the risks associated with the active volcano. Based on the prevailing wind patterns in the region, the disaster-prone areas surrounding Mount Merapi have been classified into four distinct zones, namely Zones I, II, III, and IV, each characterized by distinct agroecosystems, feasibility, and risk levels. Therefore, this study aimed to describe agroecosystems, costs, income, feasibility, and risks of chili farming in in the four zones surrounding Mount Merapi. The samples of this study consist of 163 farmers from the four disaster-prone zones surrounding Mount Merapi, selected through purposive sampling. The RC ratio was employed as part of the feasibility analysis, and the production and income risks were analyzed. The results showed that chili farming in Zone IV (the area farthest from the disaster center) possessed the lowest cost, revenue, and income. On the contrary, Zone III generated the highest cost and revenue, while Zone I (the area with the highest vulnerability to disasters) had the highest income. The range of R/C values ranges from 2.40 in Zone I to 1.16 in Zone IV. Considering the results, chili farming was feasible in disaster-prone areas, where the production risk was lower than the income risk. Therefore, Zone I, the area with extremely high disaster risk, had the lowest production and income risk. This study highlighted that chili farming provides benefits to the vulnerable farmers and new perspective for agricultural sustainability in the area of Mount Merapi.

Mount Merapi is one of the most active volcanoes in the world. Seismic activity at Mount Merapi was divided into tectonic, volcanic A and B, avalanches, and multiphase. At the volcanology and mitigation station in the area of ​​Mount Merapi, the vibrations received by the seismometer installed on the mountain were then transmitted to the station to be interpreted in the form of a seismograph. Determination of the type of earthquake at the Mount Merapi station was done manually by analyzing the shape of the wave formed. Utilizing the earthquake waveform, it could be used to determine the type of earthquake using the Nntool toolbox in Matlab. So that the determination of the type of earthquake no longer needed to be done manually. The classification process began with training the system to understand earthquake-type classes. After the system understood the earthquake data belonging to each category, the classification process could be carried out. The types of earthquakes analyzed in this research were volcanic earthquakes of types A and B. The results of these classifications were used as a determinant of the type of earthquake that occurred. The results were obtained in the form of an introduction to the types of volcanic earthquakes type A and type B which were carried out automatically with a total accuracy of 91.83%. Type A earthquake recognition accuracy was 100%, type B earthquake recognition accuracy was 84.21%, the earthquake recognition accuracy of non-A & B type was 94.44%.

Mount Merapi, a stratovolcano, is the world’s most active volcano, with a relatively short eruption period. Mount Merapi formed in the Java region as a result of regional tectonics dominated by the Sunda Arc, resulting in a large earthquake. Many earth scientists are interested in studying the volcano’s subsurface conditions due to its relatively short eruption period and interesting geological features. The Receiver Function method was used in this study to determine the crust’s depth and assess the presence of a LVZ (low velocity zone) by reprocessing receiver function data. The Receiver function is used to identify the Moho discontinuity area by converting P to S waves. A total of 100 earthquake data from 8 teleseismic stations were successfully downloaded from the IRIS website, that was distributed into sections A-A′ (west side of Mount Merapi) and B-B’ (east side of Mount Merapi). The processing of the receiver function data, as shown by the stacking align results, shows that the closest teleseismic station at west side of Mount Merapi has a very strong negative amplitude response, which is represented as a LVZ or magma reservoir after the arrival of P wave. To estimate the zone for LVZ, a forward modeling receiver function technique was used to find the best correlation between the Synthetic Receiver Function curve and the Receiver Function observation curve. A forward modeling receiver function technique was used to find the best correlation between the Synthetic RFcurve and the RF observation curve to estimate the zone for the LVZ. The correlation between the synthetic RF curve from Ramdhan et al’s (2019) tomographic velocity model and the observed RF curve is poor. To improve the correlation, include the main signal source that affects the receiver function curve in the form of seismic wave velocity particularly Vs, LVZ Zone, thin sedimen layer or shallow reservoir, and depth of discontinuity by Suhardja et al (2019). The estimated depth of the LVZ at 10 - 17 km is thinning towards the south or towards Mount Merapi, according to the results of the synthetic receiver function curve modelling at the closest station to Mount Merapi.

Magma–carbonate interaction is an increasingly recognized process occurring at active volcanoes worldwide, with implications for the magmatic evolution of the host volcanic systems, their eruptive behaviour, volcanic CO2 budgets, and economic mineralization. Abundant calc-silicate skarn xenoliths are found at Merapi volcano, Indonesia. We identify two distinct xenolith types: magmatic skarn xenoliths, which contain evidence of formation within the magma; and exoskarn xenoliths, which more likely represent fragments of crystalline metamorphosed wall rocks. The magmatic skarn xenoliths comprise distinct compositional and mineralogical zones with abundant Ca-enriched glass (up to 10 wt % relative to lava groundmass), mineralogically dominated by clinopyroxene (En15-43Fs14-36Wo41-51) + plagioclase (An37-100) ± magnetite in the outer zones towards the lava contact, and by wollastonite ± clinopyroxene (En17-38Fs8-34Wo49-59) ± plagioclase (An46-100) ± garnet (Grs0-65Adr24-75Sch0-76) ± quartz in the xenolith cores. These zones are controlled by Ca transfer from the limestone protolith to the magma and by the transfer of magma-derived elements in the opposite direction. In contrast, the exoskarn xenoliths are unzoned and essentially glass-free, representing equilibration at sub-solidus conditions. The major mineral assemblage in the exoskarn xenoliths is wollastonite + garnet (Grs73-97Adr3-24) + Ca-Al-rich clinopyroxene (CaTs0-38) + anorthite ± quartz, with variable amounts of either quartz or melilite (Geh42-91) + spinel. Thermobarometric calculations, fluid-inclusion microthermometry and newly calibrated oxybarometry based on Fe3+/ΣFe in clinopyroxene indicate magmatic skarn xenolith formation conditions of ∼850 ± 45°C, < 100 MPa and at an oxygen fugacity between the NNO (nickel–nickel oxide) and HM (hematite-magnetite) buffer. The exoskarn xenoliths, in turn, formed at 510–910°C under oxygen-fugacity conditions between NNO and air. These high oxygen fugacities are likely imposed by the large volumes of CO2 liberated from the carbonate. Halogen- and sulphur-rich mineral phases in the xenoliths testify to infiltration by a magmatic brine. In some xenoliths, this is associated with the precipitation of copper-bearing mineral phases by sulphur dissociation into sulphide and sulphate, indicating potential mineralization in the skarn system below Merapi. The compositions of many xenolith clinopyroxene and plagioclase crystals overlap with that of magmatic minerals, suggesting that the crystal cargo in Merapi magmas may contain a larger proportion of skarn-derived xenocrysts than previously recognized. Assessment of xenolith formation timescales demonstrates that magma–carbonate interaction and associated CO2 release could affect eruption intensity, as recently suggested for Merapi and similar carbonate-hosted volcanoes elsewhere.