According to a survey that was conducted in Japan in August 2024, ** percent of respondents reported spending between one and less than *** thousand Japanese yen on natural disaster preparedness in the past year. ** percent indicated spending between *** thousand and less than ** thousand yen.

STATA Code for the analysis in "Disaster preparedness and disaster response: Evidence from sales of emergency supplies before and after hurricanes" is included. The data are proprietary and not provided.

In 2017, ***** percent of Indonesian households had natural disaster simulation and training. Natural disasters are common across Indonesia as the archipelago lies on the Pacific Ring of Fire, where tectonic plates meet. However, the disaster preparedness for emergency response in Indonesia is low and not integrated into the school system yet.

Disaster preparedness and climate change adaptation and vulnerability

The Ministry of Economic Affairs' Water Resources Agency's Disaster Emergency Response Team, utilizing long-term disaster response experience, further combines real-time data such as rainfall, water levels, and reservoir levels, through computer technology to provide water level alerts to the public and relevant units. This helps people understand the risk of home flooding, prepare early, and reduce the occurrence of disasters. This dataset is linked to a Keyhole Markup Language (KML) file list, which is a markup language based on the eXtensible Markup Language (XML) syntax standard, developed and maintained by Google's Keyhole company for expressing geospatial annotations. Documents written in the KML language are referred to as KML files and are used in Google Earth-related software (Google Earth, Google Map, Google Maps for mobile, etc.) for displaying geospatial data. Many GIS-related systems now also use this format for geospatial data exchange, and the KML of this data uses UTF-8 encoding.

The EM-DAT Public Table is a flat representation of EM-DAT data in a single downloadable table. Most impact variables are part of the public table (see Impact Variables). The public table provides a flat view of the general structure in which each record (row) corresponds to a disaster impacting a country.

I used pivot tables in combination with a heat map to quickly show the severity (by deaths) of each type of disaster, by region as a drop down, each year. https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F21036995%2F9a85181a2764627469832038bdbac6da%2FEM_Data.png?generation=1723575827178988&alt=media" alt="">

Data Dictionary https://doc.emdat.be/docs/data-structure-and-content/emdat-public-table/

License information: UCLouvain 2023

This Database License Agreement (the Agreement) is made between yourself (the Licensee) and Université catholique de Louvain (UCLouvain), a Belgian University with its registered office located at Place de l’Université, 1, B-1348 Louvain-la-Neuve, Belgium, acting through its Research Group “Center for Research on the Epidemiology of Disasters” or CRED (the Licensor).

WHEREAS the Licensor has developed the EM-DAT database (hereinafter the Database) made available on the internet subject to its conditions of use;

WHEREAS the Database aims at providing an objective basis for impact and vulnerability assessment and rational decision-making in disaster situations by collecting, organizing, and giving access to validated data on the human impact of disasters (such as the number of people killed, injured, or affected), and the disaster-related economic damage estimates;

The Licensor wishes to lay down the conditions enabling the Licensee to use the Database for Commercial Purposes.

The data found on this page comes from the Hazard Mitigation Planning Program's Mitigation Planning Portal (MPP). The MPP is an online platform for tracking and reporting on mitigation plans and related data elements across all ten Federal Emergency Management Agency (FEMA) Regions. MPP data provides insight into which jurisdictions are participating in mitigation plans across the country and what the status of those plans are. Additionally, MPP data provides dates to support tracking of when plans are approved and when they are set to expire which FEMA uses to monitor and support disaster preparedness and resilience.rnHazard mitigation planning reduces loss of life and property by minimizing the impact of disasters. It begins with state, tribal, territorial and local governments identifying natural disaster risks and vulnerabilities that are common in their area. After identifying these risks, they develop long-term strategies for protecting people and property from similar events. Mitigation plans are key to breaking the cycle of disaster damage and reconstruction. When applying for certain types of non-emergency disaster assistance, FEMA requires a hazard mitigation plan. These requirements are part of the laws, regulations and policy surrounding hazard mitigation planning. For more information, visit Hazard Mitigation Planning (https://www.fema.gov/emergency-managers/risk-management/hazard-mitigation-planning)rnrnHazard mitigation plans enable state, tribal, territorial, and local governments to: rnulli Increase education and awareness around threats, hazards, risk, and vulnerabilities/liliBuild partnerships for risk reduction with governments, organizations, businesses, and the public/liliIdentify long-term strategies that seek to reduce risk/liliAlign risk reduction with other state, tribal, territorial or local objectives/liliIdentify implementation actions to focus resources on the greatest risks and vulnerabilities/liliConnect priorities to potential funding sources/liliIncrease investment in mitigation actions/li/ulrnrnA FEMA-approved hazard mitigation plan is needed to receive certain types of non-emergency disaster assistance.rnrnrnPlease note that jurisdictions may participate in multiple plans. This is raw, unedited data that is dependent on Regional entry, as such it is subject to human error and delayed entry of plan information. The data is updated from authoritative sources and has a minimum 24 hour delay.rnCitation: The Agency's preferred citation for datasets (API usage or file downloads) can be found on the OpenFEMA Terms and Conditions page, Citing Data section: https://www.fema.gov/about/openfema/terms-conditions. rnPlace name may differ from official naming standard referenced in update organization documents (i.e. Tribal name under BIA list or other authoritative source Village of, City of, etc.).rnrnIf you have media inquiries about this dataset, please email the FEMA News Desk FEMA-News-Desk@dhs.gov or call (202) 646-3272. For inquiries about FEMA's data and Open government program please contact the OpenFEMA team via email OpenFEMA@fema.dhs.gov.

This data is from a survey of Local Government Units (LGUs) Disaster Risk Reduction and Management (DRRM) Office in the Philippines. The survey conducted in 2016-2017 was intended to assess the disaster risk reduction and mitigation programs and policies employed by the local government on types of disaster due to natural hazards. The survey data covers 47 provinces (including Metro Manila) with 193 municipalities and cities. The sampling design followed a multi-stage probability scheme taking into account the high-risk and low-risk disaster areas. This data article describes the framework and design of the survey and highlights the creation of indices and other outcome variables based on the survey. It also provides information on the field operations including data cleaning and processing that may be useful to those undertaking similar surveys. The dataset is in comma-separated values file (.csv) with accompanying data dictionary (.txt). The questionnaire is also included in the data supplementary appendix. This data article is an adjunct to the research articles, “Localized Disaster Risk Management Index for the Philippines: Is Your Municipality Ready for the Next Disaster?,” Ravago, et al., 2020 and “Coping with disasters due to natural hazards: Evidence from the Philippines,” Ravago, et al., 2018, where data interpretation and analysis can be found.

Household Risk Scorecards for Disaster Prep Market Outlook

According to our latest research, the Household Risk Scorecards for Disaster Prep market size reached USD 2.1 billion in 2024 globally, with a robust CAGR of 12.7% projected from 2025 to 2033. By 2033, the market is forecasted to achieve a value of USD 6.2 billion, driven by heightened awareness of disaster preparedness, increasing frequency of extreme weather events, and a growing emphasis on risk mitigation at the household level. This growth is further supported by technological advancements in risk assessment tools and the integration of AI and data analytics in disaster preparedness solutions.

The primary growth factor for the Household Risk Scorecards for Disaster Prep market is the escalating frequency and severity of natural disasters globally. Climate change has intensified the occurrence of floods, hurricanes, wildfires, and earthquakes, compelling households and communities to adopt proactive risk management strategies. As a result, there is a surging demand for sophisticated risk scorecard solutions that provide tailored recommendations, real-time alerts, and actionable insights. The integration of geographic information systems (GIS), remote sensing, and predictive analytics into these scorecards enables more accurate and granular risk assessment, empowering individuals and organizations to make informed decisions regarding disaster preparedness. Furthermore, government initiatives promoting disaster readiness and the inclusion of risk scorecards in insurance underwriting processes are further catalyzing market expansion.

Another significant driver is the increasing digitalization of risk management practices. The proliferation of smart home devices, IoT sensors, and cloud-based platforms has revolutionized the way households monitor and manage disaster risks. Modern risk scorecards leverage vast datasets, machine learning algorithms, and real-time environmental data to deliver personalized risk profiles and mitigation plans. This digital transformation not only enhances the accuracy and timeliness of risk assessments but also facilitates seamless integration with emergency response systems and community alert networks. The growing adoption of mobile applications and online platforms for disaster preparedness is expanding the market’s reach, particularly among tech-savvy consumers and urban populations.

The market is also benefiting from increased collaboration between public and private stakeholders. Insurance providers, government agencies, technology firms, and community organizations are working together to develop comprehensive risk assessment frameworks and promote the adoption of household risk scorecards. Public awareness campaigns, educational programs, and financial incentives are encouraging more households to invest in disaster preparedness tools. Moreover, advancements in data sharing and interoperability standards are enabling seamless exchange of risk information across platforms, enhancing the overall effectiveness of disaster risk reduction efforts. These collaborative initiatives are expected to sustain market growth and foster innovation in the development of next-generation risk scorecard solutions.

Regionally, North America dominates the Household Risk Scorecards for Disaster Prep market, accounting for the largest share due to its advanced technological infrastructure, high awareness levels, and robust regulatory frameworks. Europe follows closely, driven by stringent disaster management policies and strong government support. The Asia Pacific region is witnessing the fastest growth, fueled by rapid urbanization, increasing disaster vulnerability, and rising investments in smart city initiatives. Latin America and the Middle East & Africa are also emerging as significant markets, supported by growing disaster risk reduction programs and international aid efforts. Each region presents unique challenges and opportunities, shaping the competitive landscape and influencing market dynamics.

Component Analysis

This plan provides for the establishment of national arrangements for the FSM government for responding to emergency and disaster events within the country, published in 2017.

The Global Disaster Preparedness Systems Market Size Was Worth USD 176.10 Billion in 2023 and Is Expected To Reach USD 363.93 Billion by 2032, CAGR of 8.40%.

AI in Disaster Management Market Outlook

According to our latest research, the AI in Disaster Management market size reached USD 2.1 billion in 2024, reflecting the rapid adoption of artificial intelligence technologies in emergency preparedness and response worldwide. The market is projected to expand at a robust CAGR of 23.6% from 2025 to 2033, culminating in a forecasted market value of approximately USD 17.1 billion by 2033. This significant growth is primarily driven by the increasing frequency and severity of natural disasters, the need for real-time situational awareness, and the integration of AI-powered predictive analytics in disaster management systems.

The exponential growth of the AI in Disaster Management market is underpinned by the escalating impact of climate change, which has led to a notable surge in natural calamities such as floods, hurricanes, wildfires, and earthquakes across the globe. Governments and organizations are increasingly recognizing the critical importance of leveraging AI to enhance disaster preparedness, response, and recovery. AI-driven solutions offer advanced capabilities in risk assessment, early warning, and resource optimization, enabling authorities to make data-driven decisions swiftly and efficiently. The integration of machine learning models with geospatial data, satellite imagery, and IoT sensors has transformed traditional disaster management approaches, making them more proactive and effective in mitigating risks and minimizing losses.

Another key growth factor is the rising investment in smart infrastructure and digital transformation initiatives by both public and private sectors. As urban populations continue to swell and cities become more complex, the need for resilient disaster management frameworks has intensified. AI-powered platforms facilitate seamless coordination among emergency services, optimize resource allocation, and ensure timely dissemination of critical information to affected communities. Furthermore, advancements in natural language processing and computer vision have empowered emergency response teams to analyze vast amounts of unstructured data, such as social media feeds and surveillance footage, to gain real-time insights during disasters. This has significantly improved situational awareness and accelerated the deployment of relief efforts.

The proliferation of cloud computing and the advent of edge AI have further accelerated the adoption of AI in disaster management. Cloud-based solutions offer scalability, flexibility, and cost-efficiency, enabling organizations to deploy sophisticated AI models without substantial upfront investments in hardware. Edge AI, on the other hand, allows for real-time data processing at the site of disaster, reducing latency and ensuring immediate response. These technological advancements, coupled with the growing ecosystem of AI startups and solution providers, have democratized access to cutting-edge disaster management tools globally. The increasing collaboration between technology companies, humanitarian organizations, and government agencies is also fostering innovation and driving market expansion.

Regionally, North America continues to dominate the AI in Disaster Management market, accounting for the largest revenue share in 2024, followed by Europe and Asia Pacific. The United States, in particular, has been at the forefront of adopting AI-driven disaster response solutions, supported by substantial government funding and a strong presence of leading technology vendors. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by the rising vulnerability to natural disasters, rapid urbanization, and increasing investments in smart city initiatives. Europe also presents significant growth opportunities, driven by stringent regulatory frameworks and a strong emphasis on disaster risk reduction strategies.

Component Analysis

The Component segment in the AI in Disaster Management market is categorized into Software, Hardware, and Services, each playing a pivotal role in the overall ecosystem. AI-powered software solutions form the backbone of modern disaster management systems, encompassing advanced analytics platforms, machine learning models, and decision support tools. These software applications enable authorities to analyze vast datasets, predict disaster risks, and automate response protocols with high accuracy. The demand for customizable and interoperable sof

Flooding is one of the most devastating natural disasters, causing significant loss of life, property, and economic stability worldwide. Understanding flood patterns, impacts, and potential future events is crucial for effective disaster management and mitigation strategies. The dataset was inspired by the increasing frequency and severity of flood events globally, coupled with the need for more robust data to inform disaster preparedness and response. By making this data publicly available.

According to a survey among natural disaster prevention industry-related businesses, more than **** of all respondents answered that government support was needed in securing low-interest funding above all other areas in 2023. The second-most popular answer was support for connecting with other companies.

The global emergency and disaster response market is a rapidly expanding sector, projected to reach a substantial size driven by increasing frequency and severity of natural disasters, coupled with growing urbanization and infrastructure development. The market's Compound Annual Growth Rate (CAGR) of 6.58% from 2019-2033 signifies consistent growth potential. Key drivers include heightened government spending on preparedness and response capabilities, technological advancements in early warning systems and communication technologies, and an increasing awareness of the need for effective disaster management strategies. The market is segmented by equipment types encompassing threat detection systems, personal protective gear, medical equipment, temporary shelters, mountaineering gear, firefighting equipment, and other specialized tools, along with vehicle platforms categorized as land, marine, and airborne. North America and Europe currently hold significant market shares, owing to robust economies, established infrastructure, and advanced technological adoption. However, the Asia-Pacific region is expected to witness substantial growth due to rapid urbanization, rising population density, and increasing vulnerability to natural disasters. Major players such as Textron Inc., Magirus GmbH, Honeywell International Inc., and others are actively shaping the market through continuous product innovation and strategic partnerships. The competitive landscape is characterized by both established industry leaders and emerging technology providers. Future growth will likely be influenced by factors such as the integration of artificial intelligence and machine learning for improved predictive analytics and response coordination, the development of sustainable and resilient infrastructure, and increased collaboration between public and private sectors in disaster preparedness. The ongoing evolution of disaster response technologies and strategies suggests a consistently expanding market ripe for further investment and innovation, particularly in regions facing high vulnerability to extreme weather events and other catastrophic scenarios. This report provides a detailed analysis of the global Emergency and Disaster Response industry, projecting robust growth to reach multi-billion dollar valuations by 2033. The study covers the historical period (2019-2024), the base year (2025), and forecasts the market's trajectory through to 2033. This in-depth research utilizes rigorous data analysis to provide crucial insights for stakeholders including manufacturers, government agencies, and investors seeking to capitalize on this rapidly evolving market. Key areas of focus include market segmentation by equipment (threat detection, personal protection gear, medical equipment, temporary shelter, mountaineering equipment, firefighting equipment, and other equipment), vehicle platforms (land, marine, and airborne), and leading industry players. Key drivers for this market are: , Increasing Number Of Air Passengers; Use Of Portable Electronic Devices. Potential restraints include: , High Cost Of Connectivity Equipments. Notable trends are: Land Segment to Register the Highest CAGR during the Forecast Period.

Indonesia is an area belonging to the Ring Of Fire line, fascinating the beauty of the panoramic, so attract much foreign tourists to come and see its beauty. Furthermore Indonesia is a country that often experience natural disasters, Indonesia Located in a geographical location that is prone to disaster. Disasters can be caused by both natural and behavioral factors for utilizing and managing natural resources. In some areas of Indonesia, disasters examples that hit the country. So far, there are available disaster management regulation tools, which provides disaster management framework, Pre-disaster comprehend, emergency response, and post-disaster. Although the law has outlined comprehensive disaster management provisions, so far is still focused on the emergency response period. Further actions such as mitigation, rehabilitation and reconstruction appear not to be a top priority of disaster management activities. Other issues that are still scattered are coordination, rescue aid, appropriateness of assistance, and logistic distribution.

Disaster Management Market Outlook

According to our latest research, the global disaster management market size reached USD 178.4 billion in 2024, driven by escalating natural and man-made disasters worldwide. The sector is demonstrating robust momentum, with a compound annual growth rate (CAGR) of 7.2% anticipated from 2025 through 2033. By the end of this forecast period, the disaster management market is projected to achieve a value of USD 332.9 billion by 2033. The increasing frequency and severity of disasters, coupled with the growing integration of advanced technologies, are key growth catalysts shaping the global landscape of disaster management solutions and services.

The primary growth driver for the disaster management market is the rising incidence of both natural and anthropogenic disasters. Over recent years, climate change has led to more frequent and severe weather events such as hurricanes, floods, wildfires, and earthquakes, necessitating robust disaster management infrastructure. Additionally, urbanization and population growth in high-risk zones have heightened vulnerability, compelling governments and private entities to invest in comprehensive disaster preparedness and response systems. The need for timely and effective emergency response, coupled with increasing public awareness and regulatory mandates, is further propelling market demand for advanced solutions such as geospatial technologies, real-time surveillance systems, and emergency notification platforms.

Another significant factor fueling market expansion is the rapid technological advancement and digitization of disaster management processes. The integration of artificial intelligence, IoT, cloud computing, and big data analytics has revolutionized disaster risk assessment, early warning systems, and post-disaster recovery operations. These innovations enable real-time data collection, predictive analytics, and automated response mechanisms, which significantly enhance the efficiency and accuracy of disaster management efforts. Furthermore, the proliferation of mobile devices and high-speed internet connectivity has made it easier to disseminate critical information to affected populations and coordinate multi-agency responses, contributing to the overall growth of the disaster management market.

The increasing collaboration between public and private sectors has also played a pivotal role in market development. Governments are partnering with technology providers, consulting firms, and non-governmental organizations to build resilient infrastructure and streamline disaster response protocols. International aid and funding from organizations like the United Nations, World Bank, and regional development banks are supporting the deployment of sophisticated disaster management solutions in both developed and emerging economies. This collaborative ecosystem not only accelerates the adoption of cutting-edge technologies but also fosters innovation and knowledge sharing, thereby strengthening the global disaster management framework.

From a regional perspective, North America currently dominates the disaster management market due to its advanced technological infrastructure, stringent regulatory frameworks, and high disaster risk profile. However, Asia Pacific is expected to witness the fastest growth during the forecast period, driven by increasing investments in disaster preparedness, rising urbanization, and frequent natural calamities in countries such as China, India, Japan, and Indonesia. Europe, Latin America, and the Middle East & Africa are also experiencing steady market growth, supported by government initiatives, cross-border collaborations, and the growing adoption of digital disaster management solutions. The regional dynamics are shaped by unique risk profiles, economic capabilities, and policy environments, which collectively influence market opportunities and challenges across the globe.

Solution Analysis

The disaster management market is segmented by solution into su

Recovery efforts from natural disasters can be more efficient with data-driven information on current needs and future risks. We aim to advance open-source software infrastructure to support scientific investigation and data-driven decision making with a prototype system using a water quality assessment developed to investigate post-Hurricane Maria drinking water contamination in Puerto Rico. The widespread disruption of water treatment processes and uncertain drinking water quality within distribution systems in Puerto Rico poses risk to human health. However, there is no existing digital infrastructure to scientifically determine the impacts of the hurricane. After every natural disaster, it is difficult to answer elementary questions on how to provide high quality water supplies and health services. This project will archive and make accessible data on environmental variables unique to Puerto Rico, damage caused by Hurricane Maria, and will begin to address time sensitive needs of citizens. The initial focus is to work directly with public utilities to collect and archive samples of biological and inorganic drinking water quality. Our goal is to advance understanding of how the severity of a hazard to human health (e.g., no access to safe culinary water) is related to the sophistication, connectivity, and operations of the physical and related digital infrastructure systems. By rapidly collecting data in the early stages of recovery, we will test the design of an integrated cyberinfrastructure system to for usability of environmental and health data to understand the impacts from natural disasters. We will test and stress the CUAHSI HydroShare data publication mechanisms and capabilities to (1) assess the spatial and temporal presence of waterborne pathogens in public water systems impacted by a natural disaster, (2) demonstrate usability of HydroShare as a clearinghouse to centralize selected datasets related to Hurricane Maria, and (3) develop a prototype cyberinfrastructure to assess environmental conditions and public health impacted by natural disasters. The project thus serves to not only document post-disaster conditions, but develops a process to track the impact of recovery over time, as monitored through health, power availability and water quality.

PLAIN LANGUAGE SUMMARY There is an urgent need to understand the impacts of infrastructure damage on public health after natural disasters. One limitation to effective disaster response is easy and rapid access to diverse information about available resources and maps of community resource needs and risks. We aim to expand access to diverse datasets useful for understanding disaster related environmental conditions, with a focus on drinking water quality information. The research products will be made publicly available using a collaborative, online sharing platform – HydroShare. Curating a central repository of assembled data has the potential to greatly facilitate coordinated disaster responses of all types, with opportunities to improve the monitoring of the recovery process. We will prototype this system with an assessment of drinking water, environmental, and public health concerns unique to Puerto Rico in the aftermath of Hurricane Maria. By working directly with public water utilities, we intend to characterize and map the severity of impaired water resources and distribution systems in Puerto Rico. Developing cyber and social infrastructure to understand the dynamics of drinking water contamination after natural disasters will improve disaster preparedness and response, and contribute to efforts across the nation and the world to build for a resilient future.

Poster presented at AGU Fall Meeting New Orleans Ernest N. Morial Convention Center Session: NH23E Late-Breaking Research Related to the 2017 Hurricane Season in the Americas (Harvey, Irma, Jose, Maria): Poster Contributions Program: Natural Hazards Day: Tuesday, 12 December 2017

The Canadian Disaster Database is a publicly accessible web-based repository of historical information about natural and man-made disasters that have taken place since 1900 in Canada or abroad that have directly affected Canadians. The database contains information on over 1000 events and can be used to support research, academic activities and decision-making across a breadth of fields including earth sciences, agriculture, climate change, biology and epidemiology, land use planning, insurance, investment, and the anthropological and sociological aspects of community resilience, among many others. Canada endeavours to provide the best information possible; however, the information contained in the Canadian Disaster Database (CDD) is based on information that is sourced from outside parties and may not be accurate. Canada makes no representations, warranties, or guarantees, express or implied, that the data contained in the CDD may be relied upon for any use whatsoever. Canada accepts no responsibility or liability for inaccuracies, errors or omissions in the data and any loss, damage or costs incurred as a result of using or relying on the data in any way. The CDD may contain material that is subject to licensing requirements or copyright restrictions and may not be reproduced, published, distributed or transferred in whole or in part without the consent of the author. The CDD shares information on events that have fully concluded to ensure that the data reflects the event appropriately (i.e., insurance and disaster recovery payment information is available). For this reason, events for which the costs and/or other impacts have not fully recorded contributes to a delay in making them available through the CDD. If you have technical questions about accessing or using the data in the CDD, please write to us at ps.cdd-bdc.sp@ps-sp.gc.ca.

The Artificial Intelligence in Disaster Response and Emergency Management market is an evolving landscape, leveraging cutting-edge technologies to enhance the effectiveness and efficiency of disaster preparedness, response, and recovery. With the increasing frequency and severity of natural disasters, governments an