High Disaster Risk Research Articles

Implementasi Business Intelligence Menggunakan ETL dan K-MEANS untuk Visualisasi Data Bencana Alam di Jawa Barat

In addition to its abundant natural wealth, West Java also harbors a high potential for disasters. The increasing frequency of natural disasters in recent years, such as earthquakes, landslides, and floods, has caused significant losses to the community. Climate change and environmentally unfriendly human activities are the main factors causing these disasters. Therefore, mitigation and preparedness efforts are key in facing future disaster threats. Business Intelligence can be used to process data and provide relevant information, which is a part of information technology. The purpose of this research is to visualize areas affected by natural disasters in West Java Province by implementing Business Intelligence. The method of this research is obtained in the form of a dataset sourced from the West Java Provincial Community and Village Empowerment Office, obtained through https://opendata.jabarprov.go.id/id for the period from 2020 to 2022. In this research, ETL (Extract, Transform, Load) is used to handle data, including extraction (Extract), transformation (Transform), and loading (Load), as well as K-Means calculations to cluster regions based on clusters. The result of this research is in the form of a dashboard report with the help of Google Data Studio, displaying data visualization results for the West Java region affected by natural disasters. Based on the visualization results, the areas in West Java Province with a high risk of natural disasters that fall into the first cluster in 2020 had 2 regions, in 2021 had 4 regions, and in 2022 had only 1 region.

Mitigasi Bencana Berbasis Kearifan Lokal oleh Masyarakat Kabupaten Pasaman

This research aims to understand disaster mitigation based on local wisdom implemented by the community in Pasaman Regency. In this study, the researcher applies WN. Charter's disaster mitigation theory, which divides the concept of disaster mitigation into two parts: structural mitigation and non-structural mitigation. This research uses a qualitative descriptive method. Data collection techniques include observation, interviews, and documentation. The data analysis techniques employed are data reduction, data presentation, conclusion drawing, and verification. The unit of analysis in this research is groups specifically, community groups with a high disaster risk index in Pasaman Regency, such as South Mapat Tunggul Subdistrict, Panti Subdistrict, and Tigo Nagari Subdistrict. The findings reveal that disaster mitigation based on local wisdom in Pasaman Regency has not been optimally implemented. This is evidenced by the lack of proper and comprehensive adoption of local wisdom methods in disaster mitigation activities. For instance, the institutional formation indicator shows that there is no institution beyond the existing organizations involved in this process. Furthermore, the training and education indicators show no visible utilization of the local community's wisdom as a medium for disaster mitigation. However, local wisdom methods that already exist in the community are evident in the early warning system indicator. The community uses natural signs and loudspeakers at places of worship within residential areas as an early warning system. These loudspeakers serve as an information system for the community to conduct self-initiated and independent evacuations.

AI-Powered Weather System with Disaster Prediction

This project develops an AI-powered weather system that aims to improve disaster prediction and preparedness through advanced machine learning algorithms and real-time meteorological data. By collecting data from the OpenWeatherMap API, the system analyzes key environmental indicators, including rainfall, temperature, and wind speed, to detect risks of floods, droughts, cyclones, hailstorms, and wildfires. Through machine learning models like linear regression and threshold-based heuristics, the system achieves high predictive accuracy for natural disasters. This study demonstrates the effectiveness of AI in early warning systems, thus enhancing community preparedness and supporting timely interventions by authorities. The threshold-based heuristics method involved setting predetermined weather condition limits based on historical disaster data, where surpassing these thresholds indicates high disaster risk. Linear regression was used to forecast variables like rainfall and temperature, essential for early warning in disaster management. Both techniques were implemented in tandem, with linear regression providing probabilistic outputs that feed into the heuristic system to improve prediction accuracy

Knowledge Mapping and Trend Analysis of Disaster Mitigation Research in the Sulawesi Islands of Indonesia: A Bibliometric Study Using VOSviewer

Indonesia, as an archipelagic country located on the Pacific Ring of Fire, faces a high risk of natural disasters, including earthquakes, tsunamis and volcanic eruptions. Sulawesi Island, which frequently experiences disasters, is the focus of this research to analyze trends and map knowledge related to disaster mitigation. The aim of this research is to highlight the effectiveness of existing mitigation strategies and identify areas that require further attention. The method used is bibliometric analysis with VOSviewer software, using Publish or Perish 8, of key terms in scientific literature. Data includes articles published between 2019 and 2024, with strict inclusion criteria to ensure relevance to disaster mitigation in Sulawesi. Research findings show that the four main types of disasters are floods, landslides, volcanic eruptions and tsunamis. disaster mitigation in Sulawesi. In addition, there is a lack of knowledge and implementation of sustainable mitigation strategies, as well as the need for active involvement of local communities in mitigation programs. The implications of this research emphasize the importance of evaluating existing disaster mitigation programs and more effective development policies, which can increase community preparedness and resilience to disasters. It is hoped that this research can make a significant contribution to efforts to reduce disaster risk in the region, as well as encourage collaboration between government, institutions and society in improving disaster mitigation.

Incipient particle motion in the expansion of water-inrush channel by considering the 3D relative exposure degree

Water inrush is a high-risk disaster in the construction of water-rich tunnels. The loss of particles on the sidewall of the water inrush channel is the key factor. To study the incipient particle motion in the expansion of water-inrush channel by considering the 3D relative exposure degree, the analysis for incipient flow velocity of the water inrush channel is conducted. The BP neural network and triaxial test are used to get the mesoscopic parameters. Through the DEM–CFD coupling, numerical simulation for the incipient particle motion is implemented. The effects of the 3D relative exposure degree on the incipient flow velocity are analyzed. Finally, the incipient flow velocity in the expansion of water inrush channel is verified by the laboratory test and engineering field test. The results show that: (1) the large particles have greater incipient flow velocity; (2) the particles in large dip angle are easier to move; (3) the 3D relative exposure degree of particle conforms to the Weibull distribution and the exponential distribution; (4) the incipient flow velocity of particles is closer to the critical flow velocity of rolling instability; (5) the incipient flow velocity is determined by the particles at the bottom of expansion channel.

Mapping Drought Disaster Risk Due to Climate Change in Kulon Progo District, Indonesia

Kulon Progo Regency is one of the regencies that always experiences severe drought. One of the factors that cause drought in Kulon Progo Regency is climate change due to global warming which causes changes in rainfall. The existence of drought certainly causes many problems in life due to the lack of water supply. Therefore, the purpose of this research is to conduct disaster risk mapping to obtain information on how to mitigate drought. The method used is to calculate the drought index using the Thornthwaite Matter method, calculate vulnerability based on BPS data, and calculate regional capacity based on the Regulation of BNBP Number 3 of 2012. After that, the calculation of disaster risk is then mapped. In this study, disaster risk is divided into two, disaster risk per year and dry months. The results of the annual disaster risk found that almost all sub-districts experienced low drought disaster risk, except for the Grimulyo sub-district which experienced moderate drought disaster risk. For the results of disaster risk in dry months, it is found that five sub-districts are classified into the low disaster risk category, namely Temon, Wates, Panjatan, Galur, and Nanggulan sub-districts. In addition, there are five sub-districts that fall into the medium disaster risk category, namely Lendah, Sentolo, Pengasih, Kokap, and Kalibawang. Finally, there are two sub-districts that fall into the high disaster risk category, namely Girimulyo and Samigaluh sub-districts.

Hot spots for risk-based planning in Greece – the cases of floods and forest fires

ABSTRACT Recent flood and forest fire disasters in Greece highlight the local spatial development history and territorial vulnerability as principal causes. However, despite the strong spatial aspects of disaster risk, disaster management rarely finds its way into spatial planning. The article attempts to locate high disaster risk areas (hot-spots) in Greece and activate risk-based planning. The approach combines theoretical assumptions on the spatial dimension of disaster risk; macro-scale hazard zoning at the national-regional level through past disaster event mapping; meso-scale territorial vulnerability analysis to delimit disaster risk hot-spots; and discussion on statutory planning tools and scales of intervention for risk mitigation.

Understanding Socioeconomic Risk and Vulnerability to Climate Change–Induced Disasters: The Case of Informal Settlements in KwaZulu-Natal, South Africa

This study employs a qualitative research approach to spatially delineate the risk and vulnerability of informal settlements in KwaZulu-Natal, South Africa. This comes after devastating floods that occurred in KwaZulu-Natal, South Africa, in April 2022. This disaster emphasised the necessity for South Africa to proactively address natural hazards by implementing risk reduction strategies rather than attempting to mitigate the impact after the damage has occurred. Evidence indicates that the risk and vulnerability associated with climate-induced disasters, such as flooding, are exacerbated by socioeconomic factors, including housing shortages, which compel individuals to construct dwellings in flood-prone areas. Opportunities exist to enhance the understanding of disaster risk reduction in Africa, and South Africa in particular, through science-informed initiatives employing spatial techniques, including geographic information systems, hazard exposure mapping, and socioeconomic risk and vulnerability mapping. These techniques are crucial for humanitarian planning focused on long-term risk reduction, early recovery, shelter, reconstruction, and psychosocial support for climate change disaster recovery. Furthermore, an understanding of the nature and location of areas with high disaster risk, such as flooding, is essential for the formulation of disaster risk reduction strategies, including early warning systems.

Characterization of extreme rainfall changes and response to temperature changes in Guizhou Province, China

Different geographical zones have regional heterogeneity in underlying earth surface structure and microclimate which result in different evolution trends and their response to climate change varies in extreme rainfalls in these zones. In the Guizhou province of China, there are complex landforms, which lead to spatial redistribution of rainfall, frequent extreme rainfall, and disasters high risk of geologic disasters. Research on extreme climate in Guizhou mostly paid attention to its spatio-temporal characteristics and modeling, but lack of analysis on its characteristics of extreme rainfall variability and response to temperature changes under different subsurface conditions. This study investigated the characteristics of the extreme rainfall spatiotemporal and recurrence periods in Guizhou province and discussed the relationship between the response of extreme rainfall to temperature change. Daily rainfall data from 1990 to 2020 and 2021–2100 at 31 meteorological observation stations throughout the province were collected to calculate extreme precipitation. This research had the following results. (1) Both historical and future periods show an upward trend in extreme rainfall in Guizhou province, with a spatial distribution pattern of “high in the south and low in the north, high in the east and low in the west” and “high in the southeast and low in the northwest”, respectively; the spatial distribution of extreme rainfall under each recurrence period is consistent with the non-recurrence period. (2) Both historical and future periods show an upward trend in temperature in Guizhou province, with a spatial distribution consistent with that of the extreme rainfall in the corresponding period. (3) The change in extreme rainfall intensity with increasing temperature is almost always greater than the C–C rate for different periods and underlying earth surface structure; Extreme rainfall has a Hook response structure to temperature change, and the climate response structure shifts to the right with climate warming. The results of the study can provide a basis for decision-making on regional disaster prevention and mitigation in the context of temperature change.

Association between Disaster Knowledge Level and the First Step of Stockpiling Food for a Disaster.

This study clarifies the association between disaster knowledge levels and beginning to stockpile food at home as a disaster preparedness. This survey was conducted between 18-20 December 2019 using a self-administered web-based questionnaire. The participants were recruited from panel members of an online survey company. A total of 1,200 adults living in the five Japanese prefectures with the highest predicted food shortages after the anticipated Nankai Trough earthquake, took part in the study. Multivariable logistic regression analyses revealed a significant positive relationship between disaster knowledge level and beginning food stockpiling (p for trend <0.001). Compared with those who had a low level of disaster knowledge, participants who had a medium level of knowledge were 2.11 times more likely to begin stockpiling food (adjusted odds ratio [OR]: 2.11, 95% confidence intervals [CI]: 1.49-2.97), whereas those with the highest knowledge level were 2.52 times more likely to begin stockpiling food (adjusted OR: 2.52, 95% CI: 1.79-3.56). Beginning food stockpiling can be the first step toward disaster preparedness. It is considered that people with low disaster knowledge levels are more likely to have no beginning food stockpiling and are at high risk for disasters. These findings suggest ways to approach prioritizing people facing high disaster risk.

Determinants influencing tourists’ willingness to visit Türkiye – Impact of earthquake hazards on Serbian visitors’ preferences

Abstract Earthquakes are a rather complex natural phenomenon that cannot be prevented, and their effects can be catastrophic and have profound implications on various economic sectors (especially tourism). This study investigates the relationships between subjective factors (gender, age, education, previous experience, and disaster anxiety), the perceived travel risk, and the travel intention of tourists from Serbia to destinations in Türkiye. The pilot study was done in March 2023 with 110 respondents from the Faculty of Science, Department of Geography, Tourism, and Hotel Management, Novi Sad. After the validation of the instruments, the main survey was conducted in the period from March to June 2023. The subjects of interest were residents of Serbia over the age of 18. The data from this study are analyzed using the confirmatory factor analysis and path analyses. This study aims to enhance the understanding of perceived risk and travel intention, specifically focusing on Türkiye. The assessed outcome relates to how tourists perceive three specific categories of risk when traveling to destinations with a high risk of natural disasters, such as earthquake-prone areas. The findings suggest that older respondents tend to perceive lower physical and financial travel risks, even though the influence of age on the perception of socio-psychological risks was inconclusive. Further results reveal that individuals with prior experience tend to hold a heightened perception of physical, financial, and socio-psychological risks. An examination of the relationship between disaster anxiety and perceived travel risks indicates that physical, financial, and socio-psychological risks exert a negative influence on travel intention. Thus, this study may provide a conceptual foundation for both theoretical and practical implications for the improvement of risk management techniques at a specific travel destination in areas prone to earthquake hazards.

Assessing Sustainable Development in Community Welfare and Economic Resilience to Extreme Weather in Indonesia

In recent decades, Indonesia has experienced a surge in natural disasters, resulting in increased casualties and disruptions to economic growth and welfare. This study investigates the impact of various types of natural disasters, focusing on how economic growth (measured by provincial GDP) and welfare levels (measured by the Human Development Index, HDI) influence the number of victims affected by extreme weather. Data on gross regional domestic product and the Human Development Index for each province in Indonesia were obtained from Statistics Indonesia. We employed multivariable negative binomial regression to analyze the relationships between the number of victims affected by extreme weather, provincial HDI, and provincial GDP. The results indicate significant correlations between provincial GDP, HDI, and the number of victims. Higher HDI correlates with fewer victims, whereas higher GDP is associated with an increase in victims. Additionally, we used the Self-Organizing Map (SOM) method, identifying two clusters as the optimal model. Cluster 1 comprises 31 provinces, while Cluster 2 comprises 3 provinces, with the latter highlighting the provinces with the highest disaster risk. Consequently, provinces such as West Java, Central Java, and East Java require heightened attention from various stakeholders involved in disaster management efforts. By examining these relationships, our study contributes to the understanding of sustainable development and resilience against natural disasters. It underscores the importance of improving welfare and economic policies to mitigate the impacts of extreme weather events.

Photogrammetry of airborne image set at high landslide disaster risk region using Meshroom and Blender

Abstract We report the application of the photogrammetry method to reconstruct three-dimensional topographic mesh at a high disaster risk region. This work is aimed to identify the landslide potencies of the area by means of slope analysis of the given area around the Bandung Basin rim. Our method proposes a low-cost aerial survey and an effective algorithm in order to map the local landslide tendencies. In order to perform image processing and 3D representation we utilized the photogrammetric pipeline in the Meshroom software. The post-processing of the 3D model was performed using Blender. In this research, we use a commercial camera drone as an image capturing device. As a test case we processed 183 images of an area of 51 m². The image-processing takes about 39 minutes on a 12 cores computer accompanied with a GPU card. From this set of images, we have yielded a three-dimensional slope structure comprising a total of 85,850 mesh nodes. As the result of this research, we propose the optimization of the image set and a list of post processing works of the nodes that can be used in order to characterize landslide disaster risk of the disaster-prone region in a fast and accurate manner.

Characteristics Analysis of Public Buildings on the Tsunami Risk Area in Banda Aceh City

Public buildings are structures used to serve the activities of the community at large. These buildings become gathering places for many people at one time. As venues for community activities, the presence of public buildings in tsunami-prone areas can increase vulnerability for their users. Therefore, it is necessary to understand the characteristics of public buildings located in regions at risk of tsunamis. This study aims to determine the reliability of public buildings based on the distribution of building zones, building structures, building heights, and the orientation of building locations. The results show that there are 328 public building units spread across the study area, which have varying levels of tsunami risk from low, medium, to high. The percentage breakdown of building classifications includes government buildings (31.1%), educational facilities (40.5%), health services (6.1%), places of worship (17.1%), commercial buildings (2.1%), and other facilities (3.0%). In terms of zone distribution, public buildings are predominantly located in alert zones that have a high risk of tsunami disasters. The building structures are generally permanent, made of reinforced concrete, with the majority being two or three stories high. The buildings are distributed across sparse, medium, and dense locations. Buildings with good reliability characteristics, such as strong structures resistant to tsunami waves and medium to high building heights, can be considered as alternative vertical evacuation sites for tsunamis. In Banda Aceh, public buildings are mostly low-rise, while medium-rise buildings include office and health service buildings. To ensure safety and security, it is necessary to enhance the quality of public buildings in the future, especially in areas with high tsunami risk.

DISASTER-SAFE-SCHOOL BASED PROGRAM FOR THE PSYCHOLOGICAL PREPAREDNESS OF ELEMENTARY SCHOOL STUDENTS

Background: Earthquake and tsunami are high risk disasters in the coastal areas of Java. The lack of psychological preparedness in coastal areas poses a threat to risk groups, especially school-aged children. Prevention efforts that can be carried out are through disaster-safe school-based programs through disaster management educational vehicles Objectives: The aim of this research was to analyze the influence of disaster-safe school-based programs on psychological preparedness in facing earthquake and tsunami disasters in school-aged children Methods: . The method used was a pre-experimental design. The sampling technique used purposive sampling with a sample size of 54 respondents. The sample was school age children who lived on the coast of Malang Regency. The measuring tool used the Psychological Preparedness for Disaster Threat Scale (PPDTS) questionnaire. The statistical test used was the paired t-test Results: The results showed that there were differences in psychological preparedness before and after school-aged children were given a school-based program that was safe from earthquake and tsunami disasters (0.000). Conclusion: The conclusion is that there is an influence/impact of disaster-safe school-based programs on the psychological preparedness of school-aged children in facing earthquakes and tsunamis.

UJI VALIDITAS IBFWS (IMPACT BASE FORECAST AND WARNING SERVICES) DALAM MEMPREDIKSIKAN WILAYAH YANG BERPOTENSI TERDAMPAK BANJIR DI KALIMANTAN SELATAN

South Kalimantan is one of the provinces in Indonesia which has a high risk of flood disasters seen from its physical condition, which geographically is mostly located below sea level. In 2021, 11 out of a total of 13 districts and cities in South Kalimantan were affected by flooding on a large scale, which caused tens of thousands of residents to suffer losses and even lost family members. IBFWS (Impact Base Forecast and Warning Services) is present as the latest innovation from the Meteorology, Climatology and Geophysics Agency as an impact-based weather forecast information service. To determine the accuracy of the IBFWS service information, it is necessary to validate the prediction results issued by IBFWS with the actual situation. By using spatial analysis methods, it is hoped that it can describe which areas are potentially affected by flooding and continued with the calculation of the contingency table so that the accuracy value of IBFWS is obtained in predicting areas potentially affected by flooding in South Kalimantan. IBFWS validation results in predicting areas potentially affected by flooding in South Kalimantan during the rainy season range between 0.85 – 1.00 which mean 85% - 100% the IBFWS prediction results are correct, during the transition season in general is 0.77 which mean 77% the IBFWS prediction results are correct, and during the dry season it ranges between 0.92 – 1.00 which mean 92% - 100% the IBFWS prediction results are correct.

Application of the drilling mechanical properties of rock to determine confining pressure in shallow geological formations

Confining pressure is an essential factor to consider in geological disasters in geothermal reservoirs and deep geological formations. Assessing the confining pressure holds practical importance, particularly in mitigating high-risk disasters associated with resource production. This study focuses on the development of a theoretical model for the mechanical properties of drilled rocks, specifically considering the impact of elevated confining pressure during the drilling process. Digital drilling experiments with different confining pressures are carried out to investigate the effect of confining pressure on the drilling mechanical properties of rock. A new method for identifying confining pressure and strength parameters using digital drilling is proposed. A comparison between the predicted confining pressure and the measured confining pressure is conducted to verify the accuracy of the model. The results show that the cutting force and the normal thrust at the cutting point increase with an increase in confining pressure. The drilling parameters (the bit rake angle a, the contact friction angle θ, the friction angle of rock φ, the cohesion of rock c, the effective stress generated by the drill torque St, the effective stress generated by the thrust along the normal axis Sn.) also increase gradually as confining pressure increases. Digital drilling technology offers shorter testing cycles and lower costs in comparison to traditional confining pressure testing techniques such as stress relief and hydraulic fracturing. The predicted confining pressure is consistent with the actual value. In summary, the method of determining confining pressure based on digital drilling has practical engineering significance.

The Sub-Criteria for Evacuation-Based Pedestrian Route Design Parameters

Indonesia, surrounded by three major tectonic plates—the Indo-Australian plate, the Pacific plate, and the Eurasian plate—faces a relatively high disaster risk. The city of Padang in West Sumatra, located on the western side of Sumatra Island and in proximity to tectonic plates, is particularly susceptible to earthquakes and tsunamis. To mitigate disaster risk, Padang requires evacuation-focused road infrastructure, including pedestrian paths. This study aims to assess the validity of sub-criteria parameters for creating pedestrian evacuation routes in Padang. It employs quantitative descriptive research methods, utilizing Aiken's V and Cronbach Alpha. The study involved distributing validation forms to five experts, comprising two Civil Engineering lecturers and three members of Padang City's BPBD (Regional Disaster Management Agency) specializing in Planning and Preparedness. The participants' responses, recorded through the forms, served as data for analyzing and identifying sub-criteria for evacuation-oriented pedestrian route design parameters. The study's findings reveal that one sub-criteria—Safety Fence from the Amenities parameter with a value of V = 0.7—is invalid.

The Impact of Economic Recovery Budget and Innovative Disaster Financing Schemes on Indonesia's Sustainability of Disaster-Affected Businesses

This study investigates the impact of implementing an economic recovery budget and innovative disaster financing schemes on Indonesia's disaster-affected businesses' sustainability. Indonesia is one of the countries that has many areas with high risk of natural disasters. Business resilience is crucial so that business institutions can immediately recover after a disaster; some efforts that can be made include the availability of an adequate economic recovery budget and innovative disaster impact financing schemes to adjust to the needs of disaster-affected businesses so that disaster-affected businesses recover quickly. This research was designed using quantitative analysis with a survey through a questionnaire. This study involved 180 MSE actors with sampling techniques using probability sampling. Data analysis was done using multiple linear regression analysis with the help of IBM Statistical software SPSS. The results found that the economic recovery budget significantly affects the sustainability of disaster-affected businesses in Indonesia. Then, the Innovative Disaster Financing Scheme significantly affects the sustainability of disaster-affected businesses in Indonesia. In addition, this study also found that the Innovative Disaster Financing scheme has the greatest effect on the sustainability of disaster-affected businesses in Indonesia. In conclusion, this study successfully investigated the impact of implementing the economic recovery budget and the effect of the innovative disaster financing scheme, which is 18.8 percent, which can contribute to increasing the sustainability of disaster-affected businesses in Indonesia.

Disaster risk assessment of educational infrastructure in mountain geographies using PROMETHEE-II

This study delves into the crucial realm of disaster risk assessment pertaining to educational infrastructure in mountain geographies, employing the PROMETHEE-II (Preference Ranking Organization Method for Enrichment Evaluations) technique. The study was carried out in Central Kashmir which is susceptible to various hazards, making the assessment of risks to educational facilities imperative for ensuring the safety and resilience of these crucial establishments. The AHP technique was used to assess the seismic, flood and landslide vulnerabilities of the sample institutions in the study area. The vulnerabilities were then treated against the preparedness levels using the PROMETHEE-II model. The findings reveal that out of 620 sample institutions, about 215 institutions are having high disaster risk and only about 60 sample institutions fall in low-risk category. Through the application of this method, this research aims to provide a comprehensive understanding of the vulnerabilities and potential risks faced by educational infrastructure in mountainous areas. The outcomes of the study will contribute significantly to enhancing disaster preparedness, mitigation strategies, and resource allocation for safeguarding educational institutions in these challenging terrains.