Types Of Disasters Research Articles

Flood Exposure of Residential Areas and Infrastructure in Greece

Worldwide, floods are the most common and widespread type of disaster during the 21st century. These phenomena have caused human fatalities, destruction of infrastructures and properties, and other significant impacts associated with human socioeconomic activities. In this study, the exposure of infrastructure (social, industrial and commercial, transportation) and residential areas to floods in Greek territory was considered. To accomplish the goal of the current study, freely available data from OpenStreetMap and Corine 2018 databases were collected and analyzed, as well as the flood extent zones derived under the implementation of the European Union’s (EU) Floods Directive. The results will be useful for policy-making and prioritization of prone areas based not only on the extent of flood cover but also on the possible affected infrastructure types. Moreover, the aforementioned analysis could be the first step toward an integrated national-wide flood risk assessment.

Fertility Following Natural Disasters and Epidemics in Africa

Abstract This paper uses dozens of large-scale household surveys to measure average changes in fertility following hundreds of droughts, floods, earthquakes, tropical cyclones, other storms, and epidemics in Africa between 1980 and 2016. Droughts are the largest and longest-lasting type of disaster on average, and fertility decreases by between 3.5 and 6.8 percent in the five years after droughts. Fertility changes are smaller or less clear after other types of disasters. Comparisons between countries, rather than within countries, drive these findings. There is substantial geographic heterogeneity in the direction and magnitude of the changes in fertility after disasters, driven by characteristics of the disasters and survey respondents. Fertility decreases especially after more recent droughts and in areas prone to drought. Fertility also decreases after longer floods. Fertility decreases after epidemics for women near the start and end of their childbearing careers, but increases for women in their late twenties and early thirties.

Applications of Stacking/Blending ensemble learning approaches for evaluating flash flood susceptibility

Flash floods are a type of catastrophic disasters which cause significant losses of life and property worldwide. In recent years, machine learning techniques have become powerful tools for evaluating flash flood susceptibility. This research applies stacking and blending ensemble learning approaches to assess the flash flood potential in Jiangxi, China. Four base models – linear regression, K-nearest neighbours, support vector machine, and random forest – are adopted to build the two ensemble models. All models are evaluated by three metrics (accuracy, true positive rate, and the area under the receiver operating characteristic curve) and compared with a Bayesian approach. The results suggest that the blending approach is superior to all the other models, which has then been selected to evaluate the vulnerability of flash floods for all the catchments in Jiangxi. The derived maps of flash flood susceptibility suggest that over half of the province, in terms of either area or the number of catchments, are prone to flash floods, in particular the north, northeast and south. These empirical findings can help to develop plans for disaster prevention and control, as well as improving public knowledge of flash flood hazards.

A Study on Improvement of Disaster Management Resources Support System

Large-scale complex disasters and new types of disasters are occurring due to climate changes and changes in the social environment. As the type of disaster changes to a complex and large-scale trend, disaster management resources are being mobilized to minimize damage to life and property caused by large-scale complex disasters. However, because there are various types of disaster management resources and a huge number of demand stockpiles are required, it is difficult task to possess and utilize resources for each type of disaster. In addition, since the response system to the occurrence of a large-scale complex disaster is insufficient, analysis is needed to improve the problems of the disaster management resource management system. In this study, a survey was conducted focusing on the disaster management resource support and system. The survey showed that the difference in perception of distributed management in the disaster management resource-related laws showed statistically significant differences according to age. Based on the results of the survey, problems and improvement plans for disaster management resources support system were derived.

건설업 협력업체 근로자의 안전사고경험 및 안전감시단에 대한 인식조사 연구

In the domestic construction industry, the safety monitoring groups, which plays a role of assisting in disaster prevention work in the form of outsourcing due to the lack of manpower, has emerged. The safety monitoring groups has limitations in the manufacturing and quality involvement of workers at the parent company due to personnel outside the workplace, and is limited to the lack of expertise in safety management and work safety centered on workers at subcontractors need to strengthen safety management capabilities. Therefore, this study was conducted for the purpose of confirming the necessity, qualification, and understanding of the work of the workplace safety monitoring groups and using manpower to prevent industrial accidents. The subject of the study was a self-written survey of workers at Company A's construction partner in Yeosu, Jeollanam-do, and workers at construction partner companies receiving basic safety and health education in the construction industry, and statistical analysis was conducted on 365 people. As a result, 69.5% of the main tasks were aware of the risk, and the experience of accidents caused by the surrounding environment was high. The types of disasters that threaten the safety of the workplace were in the order of drop, hit by objects, and hit. 71.5% of those who experienced safety monitors at workplaces, and 39.1% of those who experienced non-compliance experienced criticism from safety monitors. Men and regular workers are more aware of the need for safety monitors and the understanding of the qualifications and work of safety monitors, and the higher the age and experience, the higher the awareness of safety monitors. The experience group of the safety monitoring groups at the workplace showed 2.029 times higher awareness of the qualifications and understanding of the work of the safety monitoring groups than the inexperienced group. This study is expected to increase the effectiveness of securing expertise in the operation of the safety monitoring groups, so it is necessary to define the activities of the safety monitoring groups without the current qualification criteria as a law or system. In addition, measures should be prepared to increase utilization in disaster prevention in the field by presenting clarity of the scope of work with safety management personnel.

Mechanochemical effect of spontaneous combustion of sulfide ore

Spontaneous combustion of sulfide ore is a typical disaster in mining, which can cause a series of environmental and safety problems. In order to reveal the mechanical activation’s influence on the spontaneous combustion of sulfide ore during the mining process, the changes in the microstructure of sulfide minerals and their spontaneous combustion kinetics before and after activation were studied in this paper. The most probable mechanism function, apparent activation energy, and pre-exponential factor were derived using the Malek and Friedman methods, respectively. The results showed that mechanical activation leads to aggregation of mineral particles, defect generation in crystals, reduction in crystallize size, and increase in lattice distortion rate, which result in samples more actively. In the process of oxidation and spontaneous combustion, the main products were Fe2O3 and SO2 gas. And the mechanochemical effect will cause the reaction rate to become faster and lead the reaction to move toward low temperature. The mechanochemical effect will also lead to chemical reactions at low temperatures, causing some ore samples to be oxidized without changing the samples’ reaction mechanism functions. After mechanical force, the average apparent activation energy decreased by 26.27 kJ/mol, 32.73 kJ/mol, 27.01 kJ/mol, and 35.30 kJ/mol, respectively, and the sample’s spontaneous combustion tendency increased. In addition, ore samples’ active surface and grain boundary area increased under the mechanical forces, the lattice was distorted and dislocated, and a sub-stable amorphous phase was formed. In this process, the mechanical energy was partially converted into energy storage in the solid material, significantly increasing reactivity.

Multiform flood risk in a rapidly changing world: what we do not do, what we should and why it matters

Abstract There is an urgent need to raise awareness of the risks for generalizing ‘flood’ within the development of new risk assessment framework and adaptation strategies, and further outline opportunities for ensuring current and future multiform flood risk can be both assessed and reduced in particular for the most vulnerable populations. This requires enhancing modelling capabilities to embed the different yet interlinked dimensions of subtypes of climate shocks and their feedbacks. As we continue to see an increase in occurrence of compound risk, the importance of flood type specificity will grow, especially as areas experience certain types of floods for the first time. In this perspective we review current efforts to integrate flood risk within public and private sectors across the hazard modelling, financial and macroeconomic and humanitarian communities. We argue that while there are ongoing efforts in compound risk assessment, compound risk financing and compound risk anticipatory action, they remain almost exclusively focused on compounding of a primary disaster type, and fail to highlight the important differences of ‘subtypes’ of events (which from an impact profile perspective, can be as different as primary types). We then provide recommendations for developing climate change-responsive risk assessment methods and risk mitigation policy for multiform flood events.

Business recovery from disasters: Lessons from natural hazards and the COVID-19 pandemic

This paper compares economic recovery in the COVID-19 pandemic with other types of disasters, at the scale of businesses. As countries around the world struggle to emerge from the pandemic, studies of business impact and recovery have proliferated; however, pandemic research is often undertaken without the benefit of insights from long-standing research on past large-scale disruptive events, such as floods, storms, and earthquakes. This paper builds synergies between established knowledge on business recovery in disasters and emerging insights from the COVID-19 pandemic. It first proposes a disaster event taxonomy that allows the pandemic to be compared with natural hazard events from the perspective of economic disruption. The paper then identifies five key lessons on business recovery from disasters and compares them to empirical findings from the COVID-19 pandemic. For synthesis, a conceptual framework on business recovery is developed to support policy-makers to anticipate business recovery needs in economically disruptive events, including disasters.Findings from the pandemic largely resonate with those from disasters. Recovery tends to be more difficult for small businesses, those vulnerable to supply chain problems, those facing disrupted markets, and locally-oriented businesses in heavily impacted neighborhoods. Disaster assistance that is fast and less restrictive provides more effective support for business recovery. Some differences emerge, however: substantial business disruption in the pandemic derived from changes in demand due to regulatory measures as well as consumer behaviour; businesses in high-income neighborhoods and central business districts were especially affected; and traditional forms of financial assistance may need to be reconsidered.

SOSIALISASI TENTANG MITIGASI BENCANA ALAM DALAM KEGIATAN PERSAMI DI SMP NEGERI 3 PEUSANGAN

This community service activity (PKM) aims to broaden the knowledge and understanding of students of SMP N 3 Peusangan who are members of the scout organization and become participants in the Persami about the types and character of natural disasters as well as disaster management actions and disaster mitigation principles. Socialization activities are carried out by the activity implementation team by delivering material on the type and character of natural disasters as well as disaster management actions and disaster mitigation principles. Based on the results of PKM activities that have been carried out by the Community Service team consisting of lecturers and students of the Postgraduate Social Science Education Study Program at Almuslim University, Bireuen Aceh, are as follows: 1) improve the knowledge and understanding of students of SMP N 3 Peusangan who are members of scout organizations in Persami activities about the types and character of natural disasters as well as disaster management actions and disaster mitigation principles; and 2) increasing enthusiasm of students in implementing the knowledge they learned in this program on their scouting activities, so as to create a generation that can work together in groups of organizations and individuals who are ready to face various unpredicted natural conditions.

Modeling the Desire to have Children Post-Disaster Palu – Indonesian 2018

The impact of a family death, especially on children, causes demographic changes, one of which is the mother's desire to have children. This research problem is how to model with a logistic regression approach and spatial modeling with overlay technique on the desire to have children. The purpose of this study is to model desire to have children with a logistic regression and overlay modeling approach. This research was conducted in Palu City. Participants in this study amounted to 382 mothers with proportional stratified random sampling method as the sampling technique, the data were analyzed using logistic regression modeling and spatial modeling with overlay techniques. In general, the results of logistic regression modeling show a significant effect between the type of disaster and geographical location on the desire to have children after the disaster in Palu City. Mothers who experience disasters (earthquake, tsunami, liquefaction) and live in disaster-prone zones have the opportunity to have children. The results of spatial modeling using the overlay technique show that the parameters of the disaster-affected area have a high priority, indicating that the zone/area of these parameters tends to have children.

Analysis of the Influence of Agricultural Natural Disaster on Farmers’ Technology Adoption Decision

Xinjiang is the main cotton-producing area in China. However, its natural environment is special, and natural disasters frequently occur during the agricultural production process. Fortunately, the application of modern agricultural production technology provides a good tool for cotton farmers to reduce disaster losses. In order to analyze the impact of agricultural natural disasters on farmers’ adoption of agricultural production technology, based on the survey data of 216 cotton farmers in the main cotton production areas, this study uses a binary logistic model to analyze the impact of disaster types and stages on cotton farmers’ application of drip irrigation water-saving technology. The results show that hail, drought, and disease disasters have a significant impact on the application of drip irrigation water-saving technology, considering that the damage to equipment and technology’s control of disasters are the reasons behind; post-disaster remediation in the growth or maturity period also has a significant impact, which can reduce losses; and market price risk for cotton also has a significant impact.

Analysis of Maximum-Rainfall-Infiltration-Induced Slope Stability Using the Transient Rainfall Infiltration and Grid-based Regional Slope-stability Model in Cililin, West Java, Indonesia

DOI:10.17014/ijog.9.2.263-278Landslide is one type of geological disasters that frequently occurs during the rainy season. Rainfall infiltration can cause soil saturation that increases the positive pore water pressure, disturbing the slope stability. Therefore, knowledge of future landslide-triggering rainfall is required for mitigation efforts and reducing the risk of landslide hazards. This paper presents slope-stability modeling in the Cililin area using the well-established infinite slope model called the transient rainfall infiltration and grid-based regional slope-stability (TRIGRS). The modeling used the rainfall data obtained from the statistical analysis of the maximum daily rainfall by using the Gumbel distribution. The present study applied six scenarios in the modeling. Scenario I is the initial condition without rainfall, showing the slope stability influenced by topography, slope, and soil characteristics. TRIGRS modeling involves rainfall infiltration in scenarios II, III, IV, V, and VI. The maximum rainfalls used in the modeling are 66, 76, 101, 120, and 132 mm/d, showing that rainfall infiltration affected the slope stability. The result indicates that rainfall triggered an increase and expansion of the area distributions critical to the slope stability.

The Annual Global Incidence Rate of Extreme Weather Event Disasters Appears Positively Correlated with World GDP, 1961-2020.

This study compared the per capita annual global incidence rate of disasters caused by natural hazards with the annual world real gross domestic product, GDP (per global capita), as reported during 1961 through 2020. Sixty (60) values for the world real GDP per global capita (in constant 2015 $USD) were compared to corresponding annual values for global incidence rates for five natural disaster subgroups and then for a total of twelve individual disaster types that comprise the subgroups; each expressed as an annual global incidence rate (in terms of annual incidence per 100,000 persons). Calculations of multiple linear regression, ANOVA, and Pearson's correlation coefficient were performed for comparing population-adjusted values for GDP to corresponding values. Four out of five hydrological and meteorological disasters were found to have a positive correlation with GDP. Results of the analysis revealed a relatively high degree of correlation between world GDP and the annual incidence of flood and storm disasters (P = 6.21 × 10-10 and P = 4.23 × 10-4, respectively). The annual incidence of heat waves and cold weather disasters also appeared to correlate with GDP (P = .002 and P = .019, respectively). In comparison, wet landslides indicated no such correlation (P = .862). No significant associations were found among the seven other individual biological, climatological, and geophysical disasters and GDP. The global incidence of four extreme weather (hydrometeorological) disasters appear to be positively associated with world real GDP during 1961-2020. These findings contradict previous postulates that the risk of disaster incidence is inversely associated with the capacity of the population.

Meta-Analysis and Visualization of the Literature on Early Identification of Flash Floods

Flash flood is one of the extremely destructive natural disasters in the world. In recent years, extreme rainfall events caused by global climate change have increased, and flash flood disasters are becoming the main types of natural disasters in the world. Due to the characteristics of strong suddenness, complex disaster-causing factors, great difficulty in prediction and forecast, and the lack of historical data, it is difficult to effectively prevent and control flash flood disaster. The early identification technology of flash floods is not only the basis of flash flood disaster prediction and early warning, but also an effective means of flash flood prevention and control. The paper makes a meta-analysis and visual analysis of 475 documents collected by the Web of Science Document Platform in the past 31 years by comprehensively using Citespace, Vosviewer, Origin, etc. We systematically summarize the research progress and development trend of early identification technology of flash flood disasters from five key research subfields: (1) precipitation, (2) sediment, (3) sensitivity analysis, (4) risk assessment, (5) uncertainty analysis. In addition, we analyze and discuss the main problems encountered in the current research of several subfields and put forward some suggestions to provide references for the prevention and control of flash flood disasters.

Pandemic-Resilient Sustainable Settlement Model in Makassar City

A pandemic is one of many types of disasters that must be considered in emergency response planning. Currently the Covid-19 pandemic is sweeping the world, including Indonesia, so there is increasing concern about urban settlements that have high density and vulnerability to Covid-19 because housing is one of the important factors during the pandemic. Based on this, it is deemed necessary to conduct a study on a sustainable urban settlement model that is resilient to pandemics so that it can facilitate and overcome pandemic cases that have or will occur. Resilient housing is a residential area or residence inhabited by people who are ready to face any threat, including Covid-19. The research location is a residential real estate located in the city of Makassar. The research method used is multiple regression, t test and f test. As a result, the most influential factor on the security of housing residents during the pandemic is supervision, while the most influential factor in increasing the transmission of Covid-19 is the vulnerability of socio-economic mix, both of which are the most dominant variables in increasing housing resilience to the pandemic. There are various control strategies with a pandemic resilient sustainable housing model, namely increasing supervision, limiting socio-economic mixing, principles of resilience and sustainability.

The Design of Microcontroller Based Early Warning Fire Detection System for Home Monitoring

Fire is a type of disaster that can occur anytime and anywhere as a result of any accidental or intentional causes. Without exception, houses are also very vulnerable to fire. To anticipate the catastrophic effects of fire that can destroy houses, advanced technology, such as the Internet of Things (IoT) can be utilized to detect the smoke and fire. This study aims to design an early warning fire detection system for home monitoring using smoke detection sensors based on Arduino microcontroller together with NodeMCU ESP8266. This early warning fire detection system is expected to function by notifying homeowners when detecting the presence of smoke in their homes. With the aid of this detection system, the issue of potential damage, death, or material loss caused by fire can be significantly reduced. The results and testing of the designed system will be discussed in the paper.

PEMETAAN PENGETAHUAN PENELITIAN TENTANG MITIGASI BENCANA DI INDONESIA PADA GOOGLE SCHOLAR

Knowledge mapping is needed today. Knowledge of various topics falls within the scope of library and information science. One of the knowledge mapping is the study of scientific articles in the field of Disaster Mitigation in Indonesia. During 2021, Indonesia has been hit by 2,841 disasters. Even starting in 2020, Indonesia was hit by the Covid-19 disease outbreak until now. This knowledge mapping has a position as a supporter of the development of science regarding Disaster Mitigation which can make the Indonesian people more alert. This study aims to determine the mapping of science that is within the scope of the study of Disaster Mitigation in Indonesia, to find out the distribution of research articles on the research topic "Disaster Mitigation in Indonesia" on Google Scholar and to provide an overview of the state of disaster mitigation in Indonesia based on the findings. study. Qualitative research methods by means of thematic analysis. The results of the research show that mapping using VosViewer shows the relationship between disaster mitigation efforts and disaster studies, disaster mitigation concepts, types of disasters, data, mitigation policies, and forms of real efforts in the community. The conclusion of the research is that VosViewer can map the field of study on Disaster Mitigation in Indonesia.

Palu Housing Reconstruction Process: Reviewing and Learning after the 2018 Earthquake

The strong earthquake that hit the Province of Central Sulawesi on 28 September 2018 (M7.4), followed by tsunami and liquefaction has caused many casualties, injuries as well as damages in the housing sector. In the rehabilitation and reconstruction (R&R) program, the Government policy was to provide the affected community with aid to rebuild their houses (for houses outside the red zone), the Government also will build new settlements for relocation (for houses inside the red zone), which both are expected to be more earthquake-resistant. In order to understand what happens in the field related to various issues, an investigation to study the whole processes and to document the lessons learnt from the reconstruction process is conducted in Central Sulawesi Province. One of the highlights of this study is the impact of the three types of disasters that occurred in Palu Municipality (earthquake, tsunami, and liquefaction) on the housing reconstruction process after the disaster occurred. The primary field survey and Focus Group Discussion were conducted through interviews with various parties in the earthquake-affected areas to reveal the findings of problems and obstacles in the field during its two years of implementation, from 2018 to 2020. This study focuses on reviewing and learning from the post-disaster housing sector reconstruction process. The result of this study is expected to provide future lessons for the post-disaster housing reconstruction process in Indonesia and other countries.

Co-Evolutionary Fuzzy Deep Transfer Learning for Disaster Relief Demand Forecasting

Relief demand forecasting is vital to the success of disaster relief operations, but it is associated with challenges including insufficient training samples, incomplete and imprecise inputs, and inaccurate demands. This article presents a co-evolutionary fuzzy deep transfer learning (CoFDTL) method for relief demand forecasting where different types of disasters (e.g., earthquake, typhoon, and flood) are considered as different tasks. CoFDTL consists of three stages. First, a deep fuzzy learning model is used to learn latent representation of the shared inputs of all tasks. Second, a co-evolutionary algorithm is used to simultaneously learn task-specific features and the shared regressor. Third, the shared regressor is re-trained based on the best solutions obtained for different tasks in the second stage. Experiments demonstrate that CoFDTL exhibits significant performance improvements over the selected popular fuzzy learning, deep learning, and transfer learning models. This article also reports the application of CoFDTL to two real-world disasters in China, 2018. The proposed CoFDTL that integrates fuzzy deep learning, transfer learning, and co-evolutionary learning can be used for many other complex multi-task transfer learning problems with insufficient samples and uncertain information.

Afet Yönetiminde Bir Sivil Toplum Kuruluşu: Türk Kızılay

Afetler, ilk çağlardan bu yana insan yaşamının ayrılmaz bir parçasıdır. Başta depremler olmak üzere yangınlar, büyük kazalar, patlamalar, sel baskınları, heyelan, terör olayları, salgınlar gibi afet olayları tarih boyunca fiziksel çevrede ve insan topluluklarında çok büyük kayıplara yol açmıştır. Bu kayıpları en aza indirmek ve olası afetleri önlemek için sistemli bir afet yönetimi gerekmektedir. Felaketlerin çeşitliliği ve büyüklüğünün yanı sıra can ve mal kayıplarına yol açmaları nedeniyle yasal düzenlemeler de zamanla değişmiştir. 17 Ağustos 1999 İzmit Körfezi ve 12 Kasım Düzce depremleri en büyük depremler olarak tarihimizde yer aldı. Özellikle bu depremler Türkiye için önemli bir dönüm noktasını oluşturmuş ve bu alanda sivil toplum örgütlerinin faaliyetlerini hızlandırmıştır. Ülkemizde afet yönetimi kapsamında kurulan pek çok sivil toplum kuruluşu bulunmaktadır. Bunlar arasında yer alan Türk Kızılay afet yönetiminde önemli roller üstlenmektedir. Bu çalışmada afet yönetimi kavramsal çerçevede tanımlanmakta, sivil toplum kuruluşuna yer verilmekte ve afet yönetiminde bir sivil toplum kuruluşu olan Türk Kızılay ulusal ve uluslararası alanda çalışmaları ile Covid-19 salgınıyla mücadeledeki hizmetlerine değinilmektedir.