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Floods are one of the most frequent natural disasters, often resulting in widespread devastation. Identifying floods accurately is crucial for disaster management as it helps to locate areas requiring urgent assistance and streamline post-flood evacuation processes. Recently, deep learning models, such as Convolutional Neural Networks (CNN), have become predominant for image classification tasks, as well as flood classification problems. Deep ensemble techniques,i.e. combining several deep learning architectures, are still quite new in many fields and have not been studied extensively despite showing promising results in flood classification. In this research, we develop an ensemble deep learning framework that utilizes eight state-of-the-art CNN architectures, namely MobileNet V2, ResNet 50, VGG 16, DenseNet 201, Inception V3, EfficientNet B5, NasNet Large, and Xception. The aim is to address the gap of deep ensemble learning in flood classification and provide a more effective approach to identifying potential flooding scenarios from a wide range of visual datasets. We utilize FloodNet and flood area segmentation datasets to train, test, and validate our models. In the testing phase, our ensemble model outperforms several individual benchmark models, achieving a training accuracy of 98.9% and a test accuracy of 97.4%. Our proposed methodology will predict floods and conduct early assessments of affected areas efficiently. [ABSTRACT FROM AUTHOR]

Natural disasters such as earthquakes and floods cause loss of life, destruction of infrastructure, housing, and facilities, leading to material, moral, and psychological damage that can last for many years. The fear of natural disasters has grown in many countries around the world, as these disasters have become a threat to life no less dangerous than the damage caused by wars, conflicts, and deadly diseases. This has led us to challenge all circumstances in order to find ways to manage natural disasters, crises, and major risks. Algeria is one of the countries that has been hit by many natural disasters, the most prominent of which are earthquakes. It has relied on temporary and immediate solutions to deal with the aftermath of earthquakes without relying on disaster management mechanisms before and after their occurrence. Algeria, like other countries exposed to these natural hazards, has tried to work to reduce their impact by adopting a legal and strategic system that intervenes during and after disasters. This is done by taking a set of decisions aimed at preventing major hazards and managing them. The Boumerdès earthquake was one of the most important natural disasters that effectively contributed to the revision of the legal and regulatory framework for major risks in Algeria. The huge losses caused by this earthquake necessitated a complete review by the Algerian legislator to develop a preventive strategy before, during, and after the disaster in order to achieve sustainable environmental and economic development. [ABSTRACT FROM AUTHOR]

The role of the Kodam XIV / Hasanuddin and TNI health teams in natural disaster management is essential to provide health services and prevent more casualties. However, a deeper understanding of the effectiveness and challenges faced is needed. This study aims to analyze the role of Kodam XIV / Hasanuddin Health in natural disaster management, focusing on mitigation governance, early warning, and disaster preparedness. This research uses qualitative descriptive methods to describe what is happening in the field in related agencies. Data is collected through observation, interviews, and documentation by applying source, data, and time triangulation to ensure the validity and credibility of the information obtained. This research was conducted in West Sulawesi, a province prone to floods, tsunamis, earthquakes, etc. The Health Team of Kodam XIV / Hasanuddin plays an active role in disaster risk management by carrying out mitigation in the form of wave containment infrastructure development and normalization, as well as conducting early warning through the installation of EWS tools controlled by BPBD and BMKG, and conducting training, socialization, and preparing disaster risk reduction plans in the preparedness cycle. It was concluded that the health team of Kodam XIV/Hasanuddin has a central role in disaster risk management by implementing various programs such as mitigation, early warning, and preparedness, as well as providing education and training to the community to increase awareness and response to disasters.

Transportation systems, such as railways, are considered critical infrastructure. It is essential to identify potential hazards that can affect the functionality of these systems and quantify metrics that can be used for resilience-informed decision-making. This paper develops an integrated probabilistic model for seismic multi-hazard risk and restoration assessment of railway systems by accounting for the effects of seismic waves propagation, liquefaction and landslide as main phenomena affecting the integrity of distributed networked infrastructure; this is done via a GIS-based user interface. An illustrative case study is then presented to assess the seismic risk and restoration of the Tehran-Sari railway in Iran. The implementation results demonstrate the capability of the presented methodology to quantify physical metrics (including combined damage state of network components, component- and system-level functionality and restoration) and economic loss. These metrics can assist officials with implementing retrofit plans to reduce loss and improve the resilience of railway system segments. [ABSTRACT FROM AUTHOR]

Interventions after earthquakes are very important for saving human life and returning the survivors to their normal lives. Earthquakes are one of the most devastating natural hazards and can have serious economic, social and environmental impacts. As a result of earthquakes from the past to the present, millions of people have been affected and lost their lives. Being prepared for disasters will provide an opportunity to prevent possible losses and will provide an idea about how to act in case of disaster. In this paper, post-disaster response and recovery situations in disaster management and rescue after earthquakes in Turkey are discussed. Disaster management situations after the Gölcük, Van, Elazığ, and İzmir earthquakes in Turkey were analyzed and presented in terms of natural disaster and emergency management. As a result of the study, there was an improvement in disaster relief and response situations depending on the years of earthquakes in Turkey. However, the recent earthquakes show that there is still a need to work on this issue. [ABSTRACT FROM AUTHOR]

Climate change is a major concern in Rajasthan's water-stressed state. Climate change has a direct impact on the water resources in many parts of the state. In comparison to the rest of the country, the state has a larger portion of desert or arid lands (58% of the total geographical area) and limited water resources. Therefore, any adverse climate change conditions will likely have a catastrophic impact on the state's already vulnerable water resource system. Attempts have been made in this study to understand the state's climate conditions and highlight isolated past events that suggest climate change may occur in the state. It is emphasised that climate change modelling for various types of climate is required. To develop optimal water resource management strategies for different zones, cutting-edge tools such as remote sensing and geospatial tools must be used. The study's overarching goal is to comprehend the impact of climate change on the study area's water resources. The study's objectives are as follows: (1) to determine the effects of climate change on the water resources of the study location, (2) to investigate the nature and impact of climate change-induced drought disasters in the study area, (3) to identify methods and strategies for mitigating potential risks and vulnerabilities due to climatic variations and (4) determine the scope of research and policy action in response to identified current and future vulnerabilities, as well as the anticipated effects of climate change. The descriptive study used both quantitative and qualitative data collection methods. A total of 100 respondents were chosen from the villages of Rajasthan's Tonk district for quantitative data collection and 05 in-depth interviews with various stakeholders were conducted for qualitative analysis. The study revealed that indigenous knowledge systems have allowed various communities in the area to live in harmony with their environments for generations and that their traditional knowledge systems are essential tools in environment conservation and natural disaster management. Again, according to the study, the majority of respondents believe that climate change is a cause of drought disasters, which should be addressed through effective participatory research. The qualitative interviews made known themes such as stakeholder participation, climate modelling, the impacts of climate change on key development sectors, adaptation needs, initiatives, opportunities, and so on. The findings imply that climate change is one of the critical reasons for the occurrence of drought disasters in the study area and the state as a whole; drought and climate change have severely impacted water resources. To conclude, the study emphasises the emerging need for research, policy, and action to mitigate the impact of climate change on water resources and related areas. [ABSTRACT FROM AUTHOR]

In Monsoon Asia, home to more than half of the world’s population, extreme climatic events are expected to become more frequent and intense due to climate change. Modern disaster management to date has focused on assessing the risks of natural hazards based on historical data, responding to disasters through prevention and mitigation techniques, and information campaigns, instead of vernacular knowledge cultivated in the local environment. This has led the public to a dangerous complacency about the power of technology over nature, and neglecting the possibility of “unforeseen” events. Climate change has not only made it more difficult to assess the risks of natural hazards, but has also diminished local resilience to them. However, since the adoption of the Hyogo Framework for Action in 2005, Monsoon Asia has begun multi-sectoral efforts to build local resilience to natural hazards by integrating vernacular knowledge into modern disaster management. Whereas in the past, experts and government agencies regarded the public as mere recipients of their services, they have now become acutely aware of the need to build partnerships with local communities to compensate for current technological limitations in disaster management, and to imaginatively prepare for the increasing risks of climatic contingencies. To achieve these goals, vernacular knowledge can be a useful resource, and a number of efforts have been initiated in the region to preserve such knowledge in imaginative forms to pass it on to future generations.

There has been an unsettling rise in the intensity and frequency of natural disasters due to climate change and anthropogenic activities. Artificial intelligence (AI) models have shown remarkable success and superiority to handle huge and nonlinear data owing to their higher accuracy and efficiency, making them perfect tools for disaster monitoring and management. Accordingly, natural disaster management (NDM) with the usage of AI models has received increasing attention in recent years, but there has been no systematic review so far. This paper presents a systematic review on how AI models are applied in different NDM stages based on 278 studies retrieved from Elsevier Science, Springer LINK and Web of Science. The review: (1) enables increased visibility into various disaster types in different NDM stages from the methodological and content perspective, (2) obtains many general results including the practicality and gaps of extant studies and (3) provides several recommendations to develop innovative AI models and improve the quality of modeling. Overall, a comprehensive assessment and evaluation for the reviewed studies are performed, which tracked all stages of NDM research with the applications of AI models. [ABSTRACT FROM AUTHOR]

The paper presents research on the development of an ontology-based evaluation tool for the assessment of the utility of natural disaster management (NDM) websites and potential standards and guidelines for their development and evaluation. It analyzes ratings and feedback on the development of the ontology for NDM website elements from stakeholders including experts managing NDM websites and potential users of the websites and evaluates such ratings using relative and absolute utility theory. It suggests evidence that NDM websites show a lack of readiness.

Natural disasters, such as earthquakes, tsunamis, and hurricanes cause enormous harm during each year. To reduce casualties and economic losses in the response phase, rescue units must be allocated and scheduled efficiently, such that it is a key issues in emergency response. In this paper, a multi-objective mix integer nonlinear programming model (MOMINLP) is proposed to minimize sum of weighted completion times of relief operations as first objective function and makespan as second objective with considering time-window for incidents. The rescue units also have different capability and each incident just can be allocated to a rescue unit that has the ability to do it. By assuming the incidents and rescue units as jobs and machine, respectively, the research problem can be formulated as a parallel-machine scheduling problem with unrelated machines. Multi-Choice Goal programming (MCGP) is applied to solve research problem as single objective problem. The experimental results shows the superiority of the proposed approach to allocate and schedule the rescue units in the natural disasters.

The application potential of Visual Analytics (VA), with its supporting interactive 2D and 3D visualization techniques, in the environmental domain is unparalleled. Such advanced systems may enable an in-depth interactive exploration of multifaceted geospatial and temporal changes in very large and complex datasets. This is facilitated by a unique synergy of modules for simulation, analysis, and visualization, offering instantaneous visual feedback of transformative changes in the underlying data. However, even if the resulting knowledge holds great potential for supporting decision-making in the environmental domain, the consideration of such techniques still have to find their way to daily practice. To advance these developments, we demonstrate four case studies that portray different opportunities in data visualization and VA in the context of climate research and natural disaster management. Firstly, we focus on 2D data visualization and explorative analysis for climate change detection and urban microclimate development through a comprehensive time series analysis. Secondly, we focus on the combination of 2D and 3D representations and investigations for flood and storm water management through comprehensive flood and heavy rain simulations. These examples are by no means exhaustive, but serve to demonstrate how a VA framework may apply to practical research.

During each year, natural disasters like floods, hurricanes, tornadoes, earthquakes, and mass movements cause enormous damages to the people and infrastructure. Designing an effective decision support model to allocate and schedule of the rescue units can reduce economic losses and casualties in the natural disasters. By assuming the incidents as jobs and rescue units as machines, we can formulate the research problem as an unrelated parallel machine scheduling problem. In this paper, a mixed integer linear programming model is proposed to minimize the sum of the weighted completion times and delays at the start of relief operations. After relieving several incidents, rescuers will become tired and then need more time to relieve the remaining incidents which were assigned to them; therefore, we consider this phenomenon as fatigue effect in this research. The rescue units also have different capabilities, and each incident just can be allocated to a rescue unit that is able to do it. Due to NP-hardness of the research problem, three metaheuristic algorithms, namely simulated annealing (SA) algorithm, particle swarm optimization (PSO) algorithm, and a method based on hybrid SA and PSO (SA-PSO), are developed to solve the research problem. Finally, the developed metaheuristic algorithms are ranked by applying the technique for order of preference by similarity to ideal solution. The experimental results illustrate that the SA algorithm and the hybrid SA-PSO are better than others in terms of CPU time and solution quality, respectively. [ABSTRACT FROM AUTHOR]

Sri Lanka, being a small island in the Indian Ocean, is prone to natural disasters such as floods, landslides, droughts, cyclones, lightning strikes, coastal erosion, and tsunamis, which kill a number of people and destroy properties each year. Information and communication technologies (ICTs) play a significant role in natural disaster management in many countries; however, the Sri Lankan ICT development index was 3.77 in 2016, a low record in comparison to other countries. In this context, we need to probe into why ICTs have not been successfully used for natural disaster management and how ICTs can be effectively used in natural disaster management in Sri Lanka? Therefore, this study examines the use of ICT in natural disaster management in Sri Lanka. The specific objectives are to identify the role of ICT in natural disaster management and issues and implications involving the use of ICT in natural disaster management. Mixed methods will be used to achieve the aim and objectives of the research. Data will be randomly collected using 200 questionnaires. Questionnaires will be distributed among the respondents in Matara Divisional Secretariat division of Sri Lanka, which is affected by many natural disasters each year. In-depth interviews will be conducted with experts in natural disaster management and administrative officers in responsible authorities in Sri Lanka. The analysis will be done qualitatively and quantitatively. [ABSTRACT FROM AUTHOR]

In recent years, a growing number of stakeholders have been taking part in the generation and delivery of geospatial information and services to reduce the impact of severe natural disasters on the communities. This is mainly due to a huge demand for accurate, current and relevant knowledge about the impacted areas for a wide range of applications in risk-informed decision makings. The aim of this paper is to identify users’ requirements for emergency mapping team (EMT) operations in the Dominican Republic (DR). An online survey was applied to collect data from key users involved in the Inter-Institutional Geospatial Information Team in DR. Our findings suggest a set of users’ requirements for EMT operations: (1) standardization; (2) establishing and maintaining a spatial data infrastructure; (3) partnership; (4) effective communication among stakeholders; and (5) capacity building. A better understanding of the users’ requirements and the associated information workflows will lead to a superior level of readiness for EMT operations in DR. This knowledge will support future studies/practices at the local and national levels in the Caribbean region, which share similar challenges in terms of natural hazards and development issues.

The impact of flash floods that occurred in the city of Manado a few years ago resulted in significant material losses and casualties. The Manado City Government through the National Disaster Management Agency (BNPB) has an effort to deal with disaster problems, particularly floods, including involving the Air Force of the Sam Ratulangi Air Base. However, it must be admitted that there are still obstacles to optimize the Indonesian Army Force in supporting natural disaster management in the North Sulawesi region. The further studies are needed related to the synergy of the Sam Ratulangi Air Force Base and the Regional Government in response to natural flood disasters in Manado, North Sulawesi. In this paper, the theories or concepts of disaster management, synergy, civil-military relations, and national security are used. The method used is qualitative with a case study approach. The results of the study show the main differences in disaster management efforts among regional governments and related to perceptions of flood mitigation, sector introspection regarding flood mitigation, motivation for flood mitigation, and disaster management implementation plans. The planning approach is highly dependent on the political interests of the regional government. Furthermore, based on the analysis of the three pillars of synergy between civil-military in efforts to mitigate floods in the city of Manado, the problems identified are (1) related to the improvement and capacity and capability of each sector; (2) equating perceptions and frameworks at the level of regional leadership elements; (3) preparation of SOPs/operational guidelines and/or technical guidelines; and (4) performance improvement based on evaluation of disaster management. [ABSTRACT FROM AUTHOR]

Abstract Examining the efficacy of natural disaster management readiness and response activities is challenging due to the involvement of many random and uncertain components. These uncertainties can be captured by stochastic models. The analysis of these models is carried out using Monte Carlo simulations to judge the effectiveness of natural disaster management solutions. However, this approach uses static estimators, which generally rely on sampled number of events taken from the random space. The safety-critical nature of disaster management requires a more quantifiable analysis. In order to overcome this challenge, we propose to use statistical model checking for relief supply location and distribution in natural disaster management. For illustration purposes, we use the PRISM model checker to model and analyze a real-world scenario of relief supply location and distribution while considering some key factors, like demand of medical supplies at hospitals, predestined routes from warehouses to hospitals, capacity of warehouses and transportation plans. [ABSTRACT FROM AUTHOR]

This study aimed to analyze the main geo-environmental aspects of the municipality of São José dos Campos/SP, which can be considered impediments to the effective implementation of the land use regularization process in Special Areas of Social Interest (ZEIS) that have environmental characteristics of high susceptibility to landslide occurrence. For this, some geological and geotechnical data were collected and analyzed, as well as technical and legal standards related to theme and anthropogenic factors that maximize landslide occurrence. It was found that: some ZEIS are situated on lands characterized as areas with risk of landslides; most landslides have occurred in areas classified as ZEIS; both the absence of urban infrastructure systems and the non-application of the technical and legal standards of land use planning contribute considerably to the occurrence of landslides; there is a need to implement natural disaster management devices present in the current legislation on the land regularization process of ZEIS in the municipality. [ABSTRACT FROM AUTHOR]

Providing emergency relief to the victims of natural disasters is a hugely complex process fraught with many challenging aspects: multiple uncertainties, little reliable information, scarcity of resources, a variety of involved entities, and so on. Nowadays there is a lot of information that could be used to improve decision-making in disaster management, but usually it is not available at the right moment, in the right way, or it is partially known or vague. In this article we analyze the decision-making process for disaster management from the general view of intelligent decision-making to the specific characteristics of this context. This specificity deals with a new kind of logistics, and it is shown how this humanitarian logistics, specifically designed with the aim of alleviating suffering of vulnerable people, is a growing new research area to develop new decision aid models for disaster management, identifying new and relevant differences with other types of logistics. To illustrate these claims, two models are introduced, one for assessment of consequences in the earlier stage after a disaster (focused on the unknown, one of the main characteristics in disaster management), and another one for last mile distribution of humanitarian aid (focused on the multicriteria nature of decision-making on disaster management). [ABSTRACT FROM PUBLISHER]

Using mail survey data, we analyze the types of vulnerabilities Florida’s county officials rate as critical when planning for (a) a natural disaster and (b) a deliberate (terrorist) human-made attack. The research identifies the degree to which these officials provide similar assessments (commonality) of their community’s vulnerabilities across these two types of disasters. Overall, vulnerability assessment commonality is more pervasive for basic needs—water, power, transportation, emergency health care, communication, and financial assets. County management personnel and first responders are more likely to perceive greater overlap across types of hazards than finance, human services, or infrastructure officials, especially in Metropolitan Statistical Areas. [ABSTRACT FROM PUBLISHER]

The application potential of Visual Analytics (VA), with its supporting interactive 2D and 3D visualization techniques, in the environmental domain is unparalleled. Such advanced systems may enable an in-depth interactive exploration of multifaceted geospatial and temporal changes in very large and complex datasets. This is facilitated by a unique synergy of modules for simulation, analysis, and visualization, offering instantaneous visual feedback of transformative changes in the underlying data. However, even if the resulting knowledge holds great potential for supporting decision-making in the environmental domain, the consideration of such techniques still have to find their way to daily practice. To advance these developments, we demonstrate four case studies that portray different opportunities in data visualization and VA in the context of climate research and natural disaster management. Firstly, we focus on 2D data visualization and explorative analysis for climate change detection and urban microclimate development through a comprehensive time series analysis. Secondly, we focus on the combination of 2D and 3D representations and investigations for flood and storm water management through comprehensive flood and heavy rain simulations. These examples are by no means exhaustive, but serve to demonstrate how a VA framework may apply to practical research. [ABSTRACT FROM AUTHOR]

In 2004, the Government Accountability Office reported that in the context of homeland security and disaster management, regional organization is an effective way to improve intergovernmental cooperation and preparedness at the local level. In 2006, the Department of Homeland Security began including risk (vulnerability) calculations in its funding formulas and adopted a regional approach to the distribution of funds to major metropolitan areas. Despite regionalism's theoretical appeal and its popularity as an organizational structure, what makes regionalism work in the context of emergency management/homeland security has not been methodically examined at the first responder level. Our study of local governments in Florida empirically tests the relationship between perceived vulnerabilities (risks) and the effectiveness of regional emergency management organizational structures. We find that certain types of local vulnerabilities, such as population attributes and infrastructure, are more powerful promoters of proregionalism sentiments than others, most notably financial condition. [ABSTRACT FROM AUTHOR]

This paper reviews, compares, and analyzes the legal and institutional frameworks of the Disaster Management (DM) systems in India and Nigeria. This research aims to study the effectiveness and efficacy of the DM systems in both countries to identify the strengths and weaknesses and make recommendations for enhancing the current systems. The study initially provides a comprehensive introduction of Indian and Nigerian DM systems, including the countries' disaster profiles and the current DM policies and institutional frameworks, then compares them from various perspectives to identify the similarities, differences, common challenges, and lessons learned. An intense documentary survey of relevant literature is applied in this study to obtain data and information. The study finds that India, by developing better legal and institutional frameworks, creates a more effective DM system than Nigeria in terms of the integration and prioritization of Disaster Risk Reduction (DRR) efforts, community participation and coordination, and collaboration mechanisms. The research also discovers that both nations struggle to mobilize, manage, and utilize DM funds due to a lack of transparency in funding sources, particularly at the state and local/district levels. The findings also show that both countries' DM systems are mainly focused on natural disasters, with little emphasis provided on effective preventative and regulatory measures to deal with the risks and consequences of man-made hazards. The paper concludes that due to administrative and financial issues, none of the two countries achieved total success in capacity building activities. [ABSTRACT FROM AUTHOR]

In recent years, a growing number of stakeholders have been taking part in the generation and delivery of geospatial information and services to reduce the impact of severe natural disasters on the communities. This is mainly due to a huge demand for accurate, current and relevant knowledge about the impacted areas for a wide range of applications in risk-informed decision makings. The aim of this paper is to identify users' requirements for emergency mapping team (EMT) operations in the Dominican Republic (DR). An online survey was applied to collect data from key users involved in the Inter-Institutional Geospatial Information Team in DR. Our findings suggest a set of users' requirements for EMT operations: (1) standardization; (2) establishing and maintaining a spatial data infrastructure; (3) partnership; (4) effective communication among stakeholders; and (5) capacity building. A better understanding of the users' requirements and the associated information workflows will lead to a superior level of readiness for EMT operations in DR. This knowledge will support future studies/practices at the local and national levels in the Caribbean region, which share similar challenges in terms of natural hazards and development issues. [ABSTRACT FROM AUTHOR]

Climatic change and its related impact are among the most challenging threats facing the world at present. Most developing countries are particularly vulnerable to the impact of climate change due to their economic circumstances. As such, they are often less able to implement adaptation strategies to reduce climate-related impact. Based on this, this study deals with the risk, vulnerability and adaptive measures in the case of sudden disasters (i.e. heavy floods and tsunami) by applying the disaster vulnerability approach, using a case study in Malaysia. This study applies three basic indicators of climatic disasters' impact and issues – (i) flood disaster vulnerability (Ω); (ii) flood disaster magnitude (Π); and (iii) integration of adaptive flood risk management (§) using public risk perception of climate disasters and flood prevention strategies. Following the findings, this study proposes procedural and theoretical frameworks which are comparatively new to the research of climate threats (climate change, variability and disasters). Additionally, it offers decision makers' valuable insights which may assist in promoting greater awareness of flood risk management, in both Malaysia and other communities facing similar climate threats and disaster trends. [ABSTRACT FROM AUTHOR]