Number Of Disasters Research Articles

Beyond disaster: investigating the varied responses of regional entrepreneurship to natural disasters

This study investigates the intricate relationship between natural disasters and regional entrepreneurship in Türkiye, a developing nation highly vulnerable to earthquakes, floods, and other hazards. The study extends Hierarchical Multiple Regression (HMR) analysis (1990–2020, 81 NUTS-III regions), beyond existing literature focused on physical damage. Our findings reveal a counterintuitive effect: while the number of disasters and total property damage correlate positively with regional entrepreneurship, human life loss has a negative impact. This suggests a complex interplay between destruction and entrepreneurial spirit. Further analyses using Discriminant Function Analysis (DFA) and MANOVA-ANOVA for robustness check explores regional characteristics that contribute to entrepreneurial resilience against natural disasters. By comparing regions categorized by entrepreneurial performance and disaster exposure, the study identifies key differentiators. Regions with supportive business environments demonstrate greater resilience, highlighting the crucial role of fostering a strong entrepreneurial ecosystem in mitigating disaster effects. This research fills a critical gap by examining the understudied relationship between natural disasters and regional entrepreneurship, going beyond individual firm-level studies. By analysing interregional disparities and resilience factors, this paper provides valuable insights for both regional development and entrepreneurship & resilience literature. It emphasizes the importance of human capital alongside disaster preparedness and institutional quality in building regional resilience.

Statistical learning to identify salient factors influencing FEMA public assistance outlays

Both the number of disasters in the U.S. and federal outlays following disasters are rising. FEMA’s Public Assistance (PA) is a key program for rebuilding damaged public infrastructure and aiding local and state governments in recovery. It is the primary post-disaster source of recovery funds. Between 2000 and 2019, more than $125B (adjusted, 2020 dollars) was awarded through PA. While all who qualify for PA should have equal opportunity to receive aid, not all do, and the factors influencing how the program has been administered are complex and multifaceted. Lacking an understanding of the factors positively associated with historical receipt of aid, there is little way to objectively evaluate the efficacy of the PA program. In this work, we evaluate the salient features that contribute to the number of county-level PA applicants and projects following disasters. We use statistical learning theory applied to repetitive flooding events in the upper Midwest between 2003 and 2018 as a case study. The results suggest that many non-disaster related indicators are key predictors of PA outlays, including the state in which the disaster occurred, the county’s prior experience with disasters, the county’s median income, and the length of time between the end of the disaster and the date when a disaster is declared. Our work suggests that indicators of PA aid are tied to exposure, bureaucratic attributes, and human behavior. For equitable distribution of aid, policymakers should explore more disaster-relevant indicators for PA distribution.

Pengembangan Kapasitas Kelembagaan Desa Tangguh Bencana (Destana) di Kabupaten Magelang

Development of institutional capacity in disaster management in Magelang Regency through the Disaster Resilient Village (Destana). The number of disasters that occurred in Magelang Regency in 2022 was 624 disaster events consisting of strong winds or tornadoes, landslides, house fires, forest or land fires, floods and volcanoes. The aim of this research is to analyze the Institutional Capacity Development Policy through Disaster Resilient Villages (Destana) in Magelang Regency. The research methodology uses qualitative methods with data collection techniques through observation, interviews and documentation. The research results found that institutional strengthening in the Destana program was achieved by establishing a Village Disaster Risk Reduction Forum (PRB). This forum has been formed since 2015 and is called "Ing Sasmita Response Forum (FORTIS)". Fortis consists of representatives from the community, government, vulnerable groups and representatives from women. Fortis has 30 members with 10 women (33%). Furthermore, strengthening institutions by forming a Volunteer Team (Disaster Preparedness Team) with volunteer team members coming from members of the PRB forum and volunteers. Apart from that, the Magelang Regency government also strengthened institutions by collaborating between institutions and areas closest to the border. However, this collaboration does not yet have a cooperation agreement (MoU) agreed upon by both parties, so it is not yet binding on the parties involved in disaster management

Adapting the Shield: Ensuring Military Readiness for Flood Disaster in Malaysia's

The number of disasters is increasing day by day all over the world. In Malaysia, several peninsular states are frequently overwhelmed by flooding during the monsoon season. The military has played an imperative role in disaster management and relief. The Malaysian Armed Forces are well-trained in terms of combat. However, disaster relief is a secondary part of their social responsibilities. Malaysian Armed Forces members still try their best to complete the assigned task with total commitment, even though they have not had any specific training on this matter. There are lots of studies found that relate to the knowledge and attitude of nurses and health providers towards flood disaster management; however, more research needs to be conducted among Malaysian Armed Forces members. Due to this matter, this paper was developed to scrutinize Malaysian Armed Forces members' knowledge, willingness, and attitude toward flood disaster preparedness. This research will be based on a quantitative method distributed to the Malaysian Armed Forces members in the Ministry of Defense. Questionnaires were distributed online to the respondents among Malaysian Armed Forces members in the Ministry of Defense. The study managed to get 264 respondents from Malaysian Armed Forces members in three different services: the Army, Navy, and Air Force. The data is analyzed using descriptive, reliable, and regression analysis using the Statistical Package for Social Science (SPSS). Apart from that, regression analysis was used to test the hypothesis in this study. The finding found that knowledge of flood disaster preparedness and willingness/attitude is significant towards flood disaster preparedness. The findings imply effective practices and strategies applied by the Malaysian Armed Forces in facing disasters in the future.

Use of virtual reality exercises in disaster preparedness training: A scoping review.

The scope and number of disasters have increased over the years. This has called for more robust disaster preparedness training and plans. The use of virtual reality exercises in addition to tabletop exercises is considered a new approach to the preparation of disaster preparedness plans. Virtual reality exercises are being developed to either replace or complement current traditional approaches to disaster preparedness training. To review and summarize the current existing literature regarding the effectiveness, advantages and limitations of using virtual reality exercises in disaster preparedness as a complementary/replacement mechanism for real-time drills and tabletop exercises. In this scoping review, we searched PubMed, Cochrane, EMBASE, PLOS, and Google Scholar for research publications involving virtual reality exercises in disaster training from 2008 to 2022 using "AND" and "OR" operators for the keywords "disaster," "preparedness," "virtual reality," and "tabletop." From a total of 333 articles that resulted in our search and were then evaluated by the authors, 55 articles were finally included in this review. Virtual reality exercises are found to be better in the formulation of disaster preparedness plans compared to tabletop exercises. Virtual reality exercises can be used as the primary means of creating a real-life-like experience in disaster preparedness training and proved at least as better complementary to tabletop exercises. Virtual reality exercises have many advantages over traditional real-life or tabletop exercises and are more cost-effective, but some drawbacks are still identified. The advantages of virtual reality exercises are remarkable and underline their benefits and uses versus costs. We highly encourage decision-makers and institutions dealing in disaster preparedness to adopt using virtual reality exercises in training for disaster preparedness.

NATURAL DISASTERS AND PUBLIC CONCERN FOR THEIR CAUSES

This article describes the relationship between natural disasters and community negligence by referring to Jens Beckert's institutional theory (2010). This sociological study has relevance for the general public as well as government agencies. More than two thousand natural disasters occur in Indonesia every year, resulting in more than 10,000 deaths. In some cases, natural disasters are difficult to anticipate by science. However natural disasters caused by human negligence are also not insignificant, such as floods, fires and landslides. In this study, we discuss the community negligence factors that contribute to natural disasters. The study was conducted using the survey method via Google Form to a number of respondents spread across the Jabodetabek area. It also processed secondary data from a number of reports on natural disasters on various social media and digital media. Furthermore, this study shows that a number of disasters caused by human negligence are quite frequent. The facts show that Indonesian people quite often act rashly and without thinking about the long-term impact that their actions will bring. Based on secondary data, this article selects several cases of human negligence that have the potential to cause disaster.

Historical Analysis and Prediction of the Magnitude and Scale of Natural Disasters Globally

The aim of this study was to conduct a geospatial analysis of natural disasters occurring worldwide between 1960 and 2018. A total of 9962 disasters were considered, covering 39,953 locations. These phenomena were analysed in terms of frequency and number to determine changes over time and predict future trends. The data included information such as location and year of occurrence. The following natural disasters were included in the analyses: droughts, earthquakes, extreme temperatures, floods, landslides, earth mass movements, storms, and volcanic activity. The analyses were carried out across three dimensions: by continent, by number of disasters in relation to population, and in relation to the area of the continents concerned. An additional objective was to visualise the distribution of disasters by affected countries. This aspect shows the incidence of disasters by year during the period under study, with a 20-year forecast for the coming years.

Clustering of Precipitation in the Black Sea Region with by Fuzzy C-Means and Silhouette Index Analysis

In recent years, there has been a noticeable increase in the number of disasters caused by the effects of global climate change. In this context, various studies are carried out in our country and in the world in order to reduce the effects of climate change. The classification of regions affected by climate change into similar classes in terms of climate parameters is important in terms of applying similar methods in studies to be carried out in these regions. Thus, a correct strategy will be determined in the studies to be carried out in order to reduce the effects of climate change. The observation records evaluated within the scope of the study were used from 31 stations in the Black Sea Region of the Turkish State Meteorological Service, covering the period between 1982 and 2020. Cluster analysis was carried out using the Fuzzy C-Means. As a result of the study, the optimum cluster among the clusters formed by Fuzzy C-Means was determined by Silhouette index analysis. The optimal number of clusters is suggested as 4.

Deep Learning-Based Semantic Segmentation Methods for Pavement Cracks

As road mileage continues to expand, the number of disasters caused by expanding pavement cracks is increasing. Two main methods, image processing and deep learning, are used to detect these cracks to improve the efficiency and quality of pavement crack segmentation. The classical segmentation network, UNet, has a poor ability to extract target edge information and small target segmentation, and is susceptible to the influence of distracting objects in the environment, thus failing to better segment the tiny cracks on the pavement. To resolve this problem, we propose a U-shaped network, ALP-UNet, which adds an attention module to each encoding layer. In the decoding phase, we incorporated the Laplacian pyramid to make the feature map contain more boundary information. We also propose adding a PAN auxiliary head to provide an additional loss for the backbone to improve the overall network segmentation effect. The experimental results show that the proposed method can effectively reduce the interference of other factors on the pavement and effectively improve the mIou and mPA values compared to the previous methods.

Institutional challenges in reducing disaster risks in the remote city of Hindukush-Karakorum-Himalayan (HKH) region, Pakistan

The number of disasters caused by climate change and extreme weather events has increased in recent decades. The Hindukush-Karakorum-Himalayan region is particularly susceptible to multiple hazards. This region's remote settlements further exacerbate the vulnerabilities and risks. Gilgit city is considered a highly vulnerable settlement in the region. This study examines the challenges that authorities face in mitigating disasters and climate change risks. Primary data for this study was collected through expert interviews using a semi-structured questionnaire. Thematic analysis was used to identify key institutional challenges in the city. The results show that authorities still use conventional methods for monitoring and analyzing data related to natural hazards. Land-use planning is greatly lacking in the region, making it even more vulnerable to disasters. Major institutional challenges include a lack of public participation, limited access to vulnerable sites, unavailability of trained and well-equipped human resources, budget constraints, weak land-use and building bylaws, and a lack of risk-based master planning. There is an urgent need to develop and implement climate-sensitive development and land-use plans in the region in order to minimize future climate and disaster risks.

SISTEM INFORMASI GEOGRAFIS PEMETAAN BENCANA ALAM DI PROVINSI SULAWESI TENGAH

Natural disaster is an event related to natural phenomena that causes damage to a location on a small to large scale. According to data from the National Disaster Management Agency (BNPB), the number of disasters that occurred in Central Sulawesi in 2016–2020 totaled 251 cases. Determining the location of natural disasters will be one of the factors to facilitate government access in solving problems. Until now, the government does not have a Geographic Information System (GIS) in the form of mapping the location points of natural disasters that have occurred. Based on the problems above, a website-based information system was created, namely "Geographical Information System for Mapping the Central Sulawesi Natural Disaster. The aim is to provide information to the public, so that it can facilitate agencies in distributing information to the public in finding disaster information. Based on the results of the analysis using GIS using a questionnaire, the average results of the two variables were obtained, with an assessment of the first variable of 81.8% and the second variable of 89.4%. The average value of the two variables leads to a very good opinion,

A clustering-classification approach in categorizing vulnerability of roads and bridges using public assistance big data

In the US, the state, local, territorial, and tribal governments seek funding from the federal government to repair, restore, reconstruct, or replace the disaster damaged infrastructures through Public Assistance program. This research has utilized historical public assistance funded projects’ data in an unsupervised machine learning algorithm: agglomerative hierarchical clustering and uncovered three distinct levels of vulnerability among the roads and bridges in different counties under different natural hazard conditions. The paper shows the spatial distribution of the different levels of vulnerability. The difference in the extent and severity of infrastructure failure among different vulnerability levels was found to be statistically significant. In the second part of the research, a random forest classification model is utilized to explore whether the number of disasters, the area and population of a county, and the existing condition of roads and bridges in a county can predict the vulnerability level of the county as derived from the clustering model to cross-validate them. It has been found that the classification model can predict the vulnerability levels with 85% accuracy. It was also found that the differences in the condition of roads and bridges among the risk profiles are statistically significant and higher risk profile counties have worse roads and bridges. The segmentation of roads and bridges into different vulnerability levels can help the decision makers in planning for asymmetric initiatives for roads and bridges in different counties. Moreover, it has been established that improving the existing conditions of infrastructures can help in reducing the cost of public assistance in a county.

Koordinasi Penanganan Bencana Melalui Aplikasi E-Laporbencana Antara BPBD Provinsi Kalimantan Barat dengan Masyarakat

west kalimantan is one of the provinces with many disasters. for this reason, in handling disasters, the government must address it through the regional disaster management agency (bpdb) of west kalimantan province. in 2019, there was a significant increase in the number of disasters. the most increasing disaster is forest fires. if the disaster complaint is still in the conventional stage (without involving the information system), this complaint can be made by coming directly to the bpbd office or sending a letter to the address of the office. in 2019 there were many problems faced by bpbd. some of them are the slow reporting of disaster events and the lack of adequate information. of course, this can be handled by sending data and information quickly via e-disaster reports. the hope is that with the speedy delivery of this information, decisions and coordination with the community can be carried out quickly and precisely.

Flirting with Disaster: Impacts of natural disasters on public support for environmental spending

Policymakers must understand public opinion to craft effective policies, particularly in highly polarized areas such as environmental policy. However, the literature investigating the factors that drive public opinion on environmental spending largely ignores the role of exogenous events. This article investigates the role that natural disasters, as a form of exogenous shock, play in shaping public opinion. We construct a dataset using the General Social Survey (GSS) and National Oceanic and Atmospheric Administration’s (NOAA) natural disaster data from 1980 to 2018 and use generalized ordered logistic models to analyze the relationship between disasters and environmental opinions in the US. Our findings reveal that the number of disasters that occur significantly drives public support for environmental spending and that different types of disaster have heterogeneous impacts with wildfires and severe winter weather events being the most impactful. These results shed light on the impact of environmental events on public opinion on the environment, helping both researchers and policymakers make sense of dynamic public opinions.

Escalating post-disaster rescue missions through ad-hoc victim localization exploiting Wi-Fi networks

The number of disasters, accidents, and casualties in disasters is increasing, however, technological advancement has yet to ripe benefits to emergency rescue operations. This contrast is even more prominent in the Global South. The consequences are a huge loss of wealth and resources, but more importantly, the loss of lives. Locating victims of disasters as quickly as possible while speeding up rescue operations can lessen these losses. Traditional approaches for effective victim localization and rescue often requires the establishment of additional infrastructure during the construction period. Which in the context of countries of the global south such as - Bangladesh, is not followed for most of the industrial and household constructions. In this paper, we conduct a study to better understand the challenges of victim localization in emergency rescue operations and to overcome them using “whatever” resources available at hand without needing prior infrastructure facilities and pre-calibration. We design and develop a solution for this purpose and deployed it in several emulated disaster-like scenarios. We analyze and discuss the results obtained from our experiments. Finally, we point out the design implications of an infrastructure-independent and extensive emergency rescue system.

Some evidence on the reduction of the disasters impact due to natural hazards in the Americas and the Caribbean after the 1990s

This article identifies the method through which the International Decade for Natural Disaster Reduction and the subsequent frameworks affected the outcomes of Disaster Risk Reduction policies among the countries in the Americas and the Caribbean, particularly in data with high reliability in the databases used for monitoring the progress of these policies. This article will address the following research question: Did the international agenda adopted by the UN for Disaster Risk Reduction after the 1990s lead to a positive impact measured in terms of deaths caused by disasters due to natural hazards in the Americas and Caribbean? The EM-DAT disaster database includes data spanning over the course of 120 years, is long enough to match statistical criteria, and includes information for all countries; therefore, data from this database has been adopted for this research. The analysis was conducted on both regional and national scales, as well as for each natural disaster subgroup adopted by EM-DAT, and the results are divided into two periods: before 1990 and after 1990. On a regional scale, a 140% increase was noted in the number of disasters after the 1990s, whereas the number of deaths decreased by 70%. On the national scale, similar behavior was noted for majority of countries and for all subgroups of disasters. In this article, a simple but innovative methodology is proposed for analyzing the impacts in each country, thereby making it possible to exclude some disasters with an anomalous impact, without affecting the analysis and results.

Applications of structural equation modeling in humanitarian operations

Humanitarian operations have the primary purpose of saving lives and providing relief to the people affected by disasters. Due to the high number of disasters that occurred worldwide, the research in the domain of humanitarian operations has increased. Adequate tooling and systematic procedures are increasingly focusingon the humanitarian context to minimize the difficulties faced by operations. Thus, this article aims to review the existing literature related to applying structural equation modeling in humanitarian operations to understand the main topics covered by the studies. A review of 17 published documents provides descriptive background, such as evolution per year, main publication channels, the number of citations, and content analysis. The results show six main topics: coordination, performance management, communication, social inequality, readiness/agility, and integration. Based on that, the study offers some suggestions for future research.

Risk Assessment and Prediction of Rainstorm and Flood Disaster Based on Henan Province, China

To reasonably evaluate and predict the loss of rainstorm and flood disaster, this study is based on the rainfall data and rainstorm and flood disaster data of 18 cities in Henan Province from 2010 to 2020, using GIS technology and weighted comprehensive evaluation method to analyze the risk of rainstorm and flood disaster factors in various regions. The four risk factors of hazard risk, hazard-pregnant environment sensitivity, hazard-bearing body vulnerability, and disaster resilience were analyzed in compartment analysis. At the same time, a new rainstorm and flood disaster prediction model was constructed in combination with the hybrid PSO-SVR algorithm. The research results show that there are many rivers in Henan Province, the terrain tends to be higher in the west and lower in the east, and most areas are low plains, making most cities in Henan Province at a moderate risk level. For the more developed cities such as Zhengzhou, Luoyang, and Nanyang, the hazard risk, sensitivity, vulnerability, and disaster resistance are high, and they are prone to heavy rains and floods. For the economically underdeveloped, the terrain is high or hills, such as Sanmenxia City; Xinyang City and other places have low hazard risk and are not prone to rainstorms and floods. By constructing a hybrid PSO-SVR model, selecting two representative cities of Zhengzhou and Luoyang, and predicting the daily rainfall, the number of disasters, and the direct economic loss, the calculated RMSE and MAPE values are both less than GA-SVR, the traditional SVR, and BPNN models, which have verified the superiority of the model proposed in this study and the practical value it brings. To further verify the prediction accuracy of the hybrid model, the average value of RMSE and MAPE of other 16 cities are calculated, and the result is still smaller than other three models, and the study can provide some decision-making references for the urban rainstorm and flood management.

A fuzzy hybrid decision-making framework for increasing the hospital disaster preparedness: The colombian case

The recent increase in the number of disasters over the world has once again brought to the agenda the question of preparedness of the hospitals, which are the most necessary units of healthcare pillar to resist these disasters. The COVID-19 epidemic disease, which has affected the whole world, has caused a large number of people to die in some countries simply because of the inadequate and incomplete planning and lack of readiness of hospitals. For this reason, determining the disaster preparedness level of hospitals is an important issue that needs to be studied and it is important in terms of disaster damage reduction. In this study, a fuzzy hybrid decision-making framework is proposed to assess hospital disaster preparedness. The framework covers three important decision-making methods. For the first phase, Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) is used to assign relative weights for several disaster preparedness criteria considering uncertainty. Secondly, Intuitionistic Fuzzy Decision Making Trial and Evaluation Laboratory (IF-DEMATEL) is applied to identify interrelations among these criteria and feedback. Finally, via the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, priorities of hospitals regarding disaster readiness are obtained. A case study involving the participation of 10 Colombian tertiary hospitals is carried out to show the applicability of this fuzzy hybrid approach.

Disaster mitigation efforts based on community in coastal area of desa Berdaya Mirring

Indonesia is one of the countries that is categorized as a disaster-prone country. BNPB noted an increase in the number of disasters in Indonesia in the last 10 years, including earthquakes, volcanic eruptions to tidal waves and abrasion. West Sulawesi is one of the provinces prone to disasters, one of which is in Mirring Village, Polewali Mandar. Mirring Village is a coastal area that is prone to coastal abrasion and tidal waves, therefore the area is planted with mangroves to withstand tidal waves from the sea. Unfortunately, the people of Mirring village did not understand the function of the mangrove until finally Rumah Zakat through Relawan Inspirasi came to provide education regarding the use of mangroves, disaster mitigation to become a disaster-resilient family and an economically resilient family. This research is a descriptive study using a qualitative approach. The data collected with interview with 17 respondents. The results show that the community welcomes the community empowerment program towards a disaster-resilient village by Rumah Zakat. The community has understood the function of mangroves and participated in disaster training to become disaster-resilient families. The community also initiated the existence of crab ponds and mangrove cultivation which later could become their source of income and form an economically resilient family.