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.

Source: The Emergency Events Database (EM-DAT) , Centre for Research on the Epidemiology of Disasters (CRED) / Université catholique de Louvain (UCLouvain), Brussels, Belgium – www.emdat.be.Category: Climate and WeatherData series: Climate related disasters frequency, Number of Disasters: TOTAL  Climate related disasters frequency, Number of Disasters: Drought  Climate related disasters frequency, Number of Disasters: Extreme temperature  Climate related disasters frequency, Number of Disasters: Flood  Climate related disasters frequency, Number of Disasters: Landslide  Climate related disasters frequency, Number of Disasters: Storm  Climate related disasters frequency, Number of Disasters: Wildfire Climate related disasters frequency, People Affected: Drought  Climate related disasters frequency, People Affected: Extreme temperature  Climate related disasters frequency, People Affected: Flood  Climate related disasters frequency, People Affected: Landslide  Climate related disasters frequency, People Affected: Storm  Climate related disasters frequency, People Affected: Wildfire Climate related disasters frequency, People Affected: TOTAL  Disaster IntensityMetadata:EM-DAT: The International Disasters Database - Centre for Research on the Epidemiology of Disasters (CRED), part of the University of Louvain (UCLouvain) www.emdat.be, Brussels, Belgium. Only climate related disasters (Wildfire, Storm, Landslide, Flood, Extreme Temperature, and Drought) are covered. See the CID Glossary for the definitions. EM-DAT records country level human and economic losses for disasters with at least one of the following criteria: i.          Killed ten (10) or more people  ii.         Affected hundred (100) or more people  iii.        Led to declaration of a state of emergency iv.        Led to call for international assistance   The reported total number of deaths “Total Deaths” includes confirmed fatalities directly imputed to the disaster plus missing people whose whereabouts since the disaster are unknown and so they are presumed dead based on official figures. “People Affected” is the total of injured, affected, and homeless people. Injured includes the number of people with physical injuries, trauma, or illness requiring immediate medical assistance due to the disaster. Affected includes the number of people requiring immediate assistance due to the disaster. Homeless includes the number of people requiring shelter due to their house being destroyed or heavily damaged during the disaster. Disaster intensity is calculated by summing “Total Deaths” and 30% of the “People Affected”, and then dividing the result by the total population. For each disaster and its corresponding sources, the population referred to in these statistics and the apportionment between injured, affected, homeless, and the total is checked by CRED staff members. Nonetheless, it is important to note that these are estimates based on certain assumptions, which have their limitations. For details on the criteria and underlying assumptions, please visit https://doc.emdat.be/docs/data-structure-and-content/impact-variables/human/. Methodology:Global climate related disasters are stacked to show the trends in climate related physical risk factors.

The International Disaster Database is a global database that systematically records information on natural and technological disasters, including their occurrence, effects, and impacts. It was established in 1988 by the Centre for Research on the Epidemiology of Disasters (CRED) and contains data on over 26,000 disasters from 1900 to the present day. The database is compiled from various sources, including UN agencies, non-governmental organizations, reinsurance companies, research institutes, and press agencies. CRED distributes the data in open access for non-commercial use. EM-DAT supports humanitarian action, disaster preparedness, risk reduction strategies, and vulnerability assessments at both national and international levels. The data included in Data360 is a subset of the data available from the source. Please refer to the source for complete data and methodology details. This collection includes only a subset of indicators from the source dataset.

In the last century, Portugal was affected by several natural disasters of hydrogeomorphologic origin that often caused high levels of destruction. However, data on past events related to floods and landslides were scattered. The DISASTER project created a consistent and validated hydro-geomorphologic database for Portugal, by creating, disseminating and exploiting a GIS database on disastrous floods and landslides for the period 1865–2010, further updated until 2020.

Data collection was steered by the concept of disaster used within the DISASTER project. Therefore, any hydro-geomorphological case is stored in the database if the occurrence led to fatalities or injuries, and missing, evacuated or displaced people, independently of the number of people affected.

The sources of information are 16 national, regional and local newspapers that implied the analysis of 145,344 individual newspapers. The hydro-geomorphologic occurrences were stored in a database containing two major parts: the characteristics of the hydro-geomorphologic case and the corresponding damages. We provide the main results of the DISASTER database for the public.

Further details about the data collection and exploitation can be found in the following paper:

Zêzere, J.L., Pereira, S., Tavares, A.O. et al. DISASTER: a GIS database on hydro-geomorphologic disasters in Portugal. Natural Hazards 72, 503–532 (2014). https://doi.org/10.1007/s11069-013-1018-y

We provide a shapefile with the location of the hydro-geomorphological hazard for the period 1865-2020 for mainland Portugal and additional details about the hydrogeomorphological hazard type and subtype, date of occcurrence, year, month, day, hour, georeferencing quality, source, source date, source type, page in the source, number of human damages (fatalities, injured, evaciated, displaced and missing people), district, municipality and parish.

Also, we provide a word document with the database codes description.

The Geocoded Disasters (GDIS) Dataset is a geocoded extension of a selection of natural disasters from the Centre for Research on the Epidemiology of Disasters' (CRED) Emergency Events Database (EM-DAT). The data set encompasses 39,953 locations for 9,924 disasters that occurred worldwide in the years 1960 to 2018. All floods, storms (typhoons, monsoons etc.), earthquakes, landslides, droughts, volcanic activity and extreme temperatures that were recorded in EM-DAT during these 58 years and could be geocoded are included in the data set. The highest spatial resolution in the data set corresponds to administrative level 3 (usually district/commune/village) in the Global Administrative Areas database (GADM, 2018). The vast majority of the locations are administrative level 1 (typically state/province/region).

This dataset provides data on the occurrence and impacts of mass disasters in Vietnam from 1900 to 2024. This includes both natural (biological, climatological, extra-terrestrial, geophysical, hydrological, meteorological), and technological (industrial accident) disasters. Data was extracted from The International Disaster Database, Centre for Research on the Epidemiology of Disasters.

The NOAA National Centers for Environmental Information ceased providing support for this product in May 2025 in response to an initiative to implement reductions within the U.S. federal government. This dataset contains U.S. disaster cost assessments of the total, direct losses ($) inflicted by: tropical cyclones, inland floods, drought & heat waves, severe local storms (i.e., tornado, hail, straight-line wind damage), wildfires, crop freeze events and winter storms. These assessments require input from a variety of public and private data sources including: the Insurance Services Office (ISO) Property Claim Services (PCS), Federal Emergency Management Agency (FEMA) National Flood Insurance Program (NFIP) and Presidential Disaster Declaration (PDD) assistance, and the United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) & Risk Management Agency (RMA), the National Interagency Fire Center (NIFC) and state agency reporting, among others. Each of these data sources provides unique information as part of the overall disaster loss assessment.

Tracking the occurrence of natural disasters can save lives by helping countries prepare for future ones.

In our work on natural disasters, we visualize data from EM-DAT, the most comprehensive international disaster database. Make a chart of the number of recorded disaster events over time — like the one above — and it looks like the number of disasters rose alarmingly from the 1970s to the millennium. This has led to many media outlets and organizations claiming that the number of disasters has quadrupled over the last 50 years.

However, as EM-DAT itself makes clear, most of this is due to improvements in recording. The Centre for Research on the Epidemiology of Disasters, which builds this database, was not established until 1973, and didn’t start publishing EM-DAT until 1988.

The number of recorded disasters increased due to more focused efforts to obtain globally comprehensive data and improvements in communication technologies, which allowed more events to be included, even in the planet's most remote areas.

EM-DAT suggests that only data from 2000 onwards is relatively complete and comparable. The number of events before 2000 is likely to be underestimated. Note that this data does not tell us anything about the intensity of disasters.

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.

Note: this map service is being replaced by a new set of feature layers, please use these instead:Historical Tsunami EventsTsunami ObservationsSignificant EarthquakesSignificant Volcanic EventsVolcano LocationsCurrent DARTs and Retrospective BPR DeploymentsHistorical MarigramsTsunami-Capable Tide StationsPlate BoundariesNatural hazards such as earthquakes, tsunamis, and volcanoes affect both coastal and inland areas. Long-term data from these events can be used to establish the past record of natural hazard event occurrences, which is important for planning, response, and mitigation of future events. NOAA's National Centers for Environmental Information (NCEI) plays a major role in post-event data collection. The data in this archive is gathered from scientific and scholarly sources, regional and worldwide catalogs, tide gauge reports, individual event reports, and unpublished works. For more information, please see: https://www.ncei.noaa.gov/products/natural-hazardsTo view this service in an interactive mapping application, please see the Global Natural Hazards Data Viewer (NOAA GeoPlatform entry).

Early event detection and response can significantly reduce the societal impact of floods. Currently, early warning systems rely on gauges, radar data, models and informal local sources. However, the scope and reliability of these systems are limited. Recently, the use of social media for detecting disasters has shown promising results, especially for earthquakes. Here, we present a new database for detecting floods in real time on a global scale using Twitter. The method was developed using 125 million tweets, from which we derived over 10.000 flood events in countries or their first administrative subdivisions across 176 countries in 12 languages in just over four years. Using strict parameters, validation shows that approximately 83% of the events were correctly detected. In countries where the first official language is included, our algorithm detected 70% of events in NatCatSERVICE disaster database at admin 1 level. Moreover, a large number of flood events not included in NatCatSERVICE are detected. All results are publicly available on www.globalfloodmonitor.org.

"The Canadian Disaster Database (CDD) contains detailed disaster information on more than 1000 natural, technological and conflict events (excluding war) that have happened since 1900 at home or abroad and that have directly affected Canadians. The CDD tracks ""significant disaster events"" which conform to the Emergency Management Framework for Canada definition of a ""disaster"" and meet one or more of the following criteria: •10 or more people killed •100 or more people affected/injured/infected/evacuated or homeless •an appeal for national/international assistance •historical significance •significant damage/interruption of normal processes such that the community affected cannot recover on its own The database describes where and when a disaster occurred, the number of injuries, evacuations, and fatalities, as well as a rough estimate of the costs. As much as possible, the CDD contains primary data that is valid, current and supported by reliable and traceable sources, including federal institutions, provincial/territorial governments, non-governmental organizations and media sources. Data is updated and reviewed on a semi-annual basis"

This entry does not contain data itself, it is for the website, the NASA Disasters Mapping Portal: https://maps.disasters.nasa.gov The Disasters Mapping Portal contains numerous datasets that can be streamed from the Portal into GIS software. The Disasters Applications area promotes the use of Earth observations to improve prediction of, preparation for, response to, and recovery from natural and technological disasters. Disaster applications and applied research on natural hazards support emergency mitigation approaches, such as early warning systems, and providing information and maps to disaster response and recovery teams. NOTE: Removed "2017 - Present" from "Temporal Applicability" since it's not valid NOTE: Removed "Event-Specific and Near-Real Time Products" from "Update Frequency" since it's not valid

Open Data for Resilience Initiative (OpenDRI) applies the concepts of the global open data movement to the challenges of reducing vulnerability to natural hazards and the impacts of climate change. OpenDRI supports World Bank Regional Disaster Risk Management Teams to build capacity and long-term ownership of open data projects with client countries that are tailored to meet specific needs and goals of stakeholders around three main areas of Sharing Data, Collecting Data, Using Data. All data is published under an open license. Projects include Open Cities Africa, with national projects in: Niger (flood hostpots and mitigation), Uganda (drought risk information and disaster risk financing), Zanzibar (vunlerability to natural disasters), Pacific Islands (Natural Disasters and Climate Change), Sri Lanka (evidence based methods for natural disaster response), Afghanistan (disaster risk decisionmaking), St Vincent and the Grenadines (hydroclimatic disasters), Saint Lucia (post disaster rehabilitation), Jamaica (storm even impact), Serbia (disaster preparedness), Indonesia (disaster management especially flooding), Seychelles (site specific risks of floods, earthquakes, cyclones, storm surge and tsunamis), Muaritius (under development), Madagascar (under development), Vietnam (natural hazards especially flood risks and climate change impacts), Bangladesh (under development), Pakistan (earthquakes and monsoon floods), Nepal (Seismic risk), Haiti (storms, flooding, landslides, environmental degradation), Guyana (under development), Grenada (under development), Dominica (extreme weather events), Colombia (flooding, landslides, increased vulnerability due to insufficient urban planning), Antigua and Barbuda (cyclones, fires and flooding), Belize (storm, flood and tsunami risks), Bolivia (natural hazards and climate change), Kyrgyz Republic (risk data on meteorological, geological, geophyical and boilogical hazards), Philippines (typhoones and monsoon floods recovery data), Tanzania (flood maps), Mozambique (flood, cyclone and windstorms), Comoros (flood, storm, volcanic eruption), Malawi (information to develop schools, healthcare and agriculture against floods and droughts), Armenia (earthquakes, drought, hailstorms, landslides)

Solomon Islands SB: Droughts, Floods, Extreme Temperatures: Average 1990-2009: % of Population data was reported at 0.090 % in 2009. Solomon Islands SB: Droughts, Floods, Extreme Temperatures: Average 1990-2009: % of Population data is updated yearly, averaging 0.090 % from Dec 2009 (Median) to 2009, with 1 observations. Solomon Islands SB: Droughts, Floods, Extreme Temperatures: Average 1990-2009: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Solomon Islands – Table SB.World Bank.WDI: Land Use, Protected Areas and National Wealth. Droughts, floods and extreme temperatures is the annual average percentage of the population that is affected by natural disasters classified as either droughts, floods, or extreme temperature events. A drought is an extended period of time characterized by a deficiency in a region's water supply that is the result of constantly below average precipitation. A drought can lead to losses to agriculture, affect inland navigation and hydropower plants, and cause a lack of drinking water and famine. A flood is a significant rise of water level in a stream, lake, reservoir or coastal region. Extreme temperature events are either cold waves or heat waves. A cold wave can be both a prolonged period of excessively cold weather and the sudden invasion of very cold air over a large area. Along with frost it can cause damage to agriculture, infrastructure, and property. A heat wave is a prolonged period of excessively hot and sometimes also humid weather relative to normal climate patterns of a certain region. Population affected is the number of people injured, left homeless or requiring immediate assistance during a period of emergency resulting from a natural disaster; it can also include displaced or evacuated people. Average percentage of population affected is calculated by dividing the sum of total affected for the period stated by the sum of the annual population figures for the period stated.; ; EM-DAT: The OFDA/CRED International Disaster Database: www.emdat.be, Université Catholique de Louvain, Brussels (Belgium), World Bank.; ;

Data for the visualization published on the OD Mekong Disasters and emergency response page (https://opendevelopmentmekong.net/topics/disasters-and-emergency-response/). It shows the number of total deaths recorded by natural disaster classification. Source: EM-DAT: The OFDA/CRED International Disaster Database – www.emdat.be – Université Catholique de Louvain – Brussels – Belgium

FFEM-DB (Database of Flood Fatalities from the Euro-Mediterranean region) is a database which contains 2.875 cases of flood fatalities that occurred throughout 41 years (1980–2020) in 12 study areas in Euro-Mediterranean area (Cyprus; Czech Republic; Germany; Greece; Israel; Italy; Portugal; Turkey; United Kingdom; the Spanish regions of Balearic Islands and Catalonia, and the Mediterranean regions of South France). FFEM-DB provides not only the number of fatalities, but also detailed information about the profile of victims and the circumstances of the accidents. Flood fatality cases are georeferenced using NUTS 3 level (Nomenclature of Territorial Units for Statistics), allowing analyses of fatality distribution in respect to geographic and demographic data.

(UNCLASSIFIED) Liberia’s infrastructure has been in shambles for decades, mostly due to two recent civil wars and regional instability. Vital services including disaster relief and an operating health care system are nonfunctioning, causing natural disasters and epidemics to be even more dangerous. Intense summer rains often lead to flooding, mostly around the capital of Monrovia. Flooding in this region often destroys homes leaving many displaced. In addition, the healthcare system is highly dependent on foreign aid and assistance with Agencies and NGOs providing 90% of health services. Attribute Table Field DescriptionsISO3 - International Organization for Standardization 3-digit country code ADM0_NAME - Administration level zero identification / name AREA_AFF - Location of disaster event TYPE_1 - Primary classification in geodatabase TYPE_2 - Secondary classification in geodatabase START_DT - Start date of disaster event END_DT - Date disaster event ended TL_AFFECT - Total number affected by disaster event FATALITY - Number of deaths caused by disaster event COMMENTS - Additional comments SOURCE_DT - Source one creation date SOURCE - Source one SOURCE2_DT - Source two creation date SOURCE2 - Source two CollectionThis HGIS dataset was created through information provided by EM-DAT The International Disaster Database and Relief Web. Additional information regarding significant events was sourced through other sources and news articles. The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe is not responsible for the accuracy and completeness of data compiled from outside sources.Sources (HGIS)EM-DAT. The International Disaster Database, “Advanced Search”. Last modified September 2014. Accessed September 2014. http://www.emdat.be.ReliefWeb, “Liberia”. Last modified May 2014. Accessed September 2014. http://reliefweb.int.Sources (Metadata)IRIN Humanitarian News and Analysis, “Liberia: Floods displace hundreds in Monrovia.” Last modified August 2007. Accessed September 2014. http://www.irinnews.org.World Health Organization, “Liberia: Health Sector Needs Assessment.” Last modified January 2006. Accessed September 2014. http://www.who.int/en

This dataset was built from search criteria on the EM-DAT database to find the number of floods, storms, droughts and earthquakes per years int he five Lower Mekong countries. Source: EM-DAT: The OFDA/CRED International Disaster Database – www.emdat.be – Université Catholique de Louvain – Brussels – Belgium.

SBA Disaster Loan Data provides verified loss and approved loan amount totals for both home and business disaster loans, segmented by city, county, zip code and state.