There were a total of 1,033 fatalities reported due to heat waves, wildfires, and drought in the United States in 2024. In total, there were about 1,576 fatalities due to severe natural disasters in the United States that year.

The statistic shows the leading causes of deaths due to tropical cyclones in the United States from 1963 to 2012. Total 8 percent of victims died because of wind effects during tropical cyclones.

In 2024, there were a total of 81 severe natural disasters United States. In that year, approximately 60 percent of the catastrophes were severe convective storms. Furthermore, around 14 percent of the major disasters in the U.S. in 2024 were floods or flash floods.

This statistic shows the number of earthquakes in the United States from 2000 to 2012. 2,342 earthquakes were recorded in the United States in the year 2000.

Natural Hazards is a natural disaster dataset with sentiment labels, which contains nearly 50,00 Twitter data about different natural disasters in the United States (e.g., a tornado in 2011, a hurricane named Sandy in 2012, a series of floods in 2013, a hurricane named Matthew in 2016, a blizzard in 2016, a hurricane named Harvey in 2017, a hurricane named Michael in 2018, a series of wildfires in 2018, and a hurricane named Dorian in 2019).

OverviewThe multiple hazard index for the United States Counties was designed to map natural hazard relating to exposure to multiple natural disasters. The index was created to provide communities and public health officials with an overview of the risks that are prominent in their county, and to facilitate the comparison of hazard level between counties. Most existing hazard maps focus on a single disaster type. By creating a measure that aggregates the hazard from individual disasters, the increased hazard that results from exposure to multiple natural disasters can be better understood. The multiple hazard index represents the aggregate of hazard from eleven individual disasters. Layers displaying the hazard from each individual disaster are also included.

The hazard index is displayed visually as a choropleth map, with the color blue representing areas with less hazard and red representing areas with higher hazard. Users can click on each county to view its hazard index value, and the level of hazard for each individual disaster. Layers describing the relative level of hazard from each individual disaster are also available as choropleth maps with red areas representing high, orange representing medium, and yellow representing low levels of hazard.Methodology and Data CitationsMultiple Hazard Index

The multiple hazard index was created by coding the individual hazard classifications and summing the coded values for each United States County. Each individual hazard is weighted equally in the multiple hazard index. Alaska and Hawaii were excluded from analysis because one third of individual hazard datasets only describe the coterminous United States.

Avalanche Hazard

University of South Carolina Hazards and Vulnerability Research Institute. “Spatial Hazard Events and Losses Database”. United States Counties. “Avalanches United States 2001-2009”. < http://hvri.geog.sc.edu/SHELDUS/

Downloaded 06/2016.

Classification

Avalanche hazard was classified by dividing counties based upon the number of avalanches they experienced over the nine year period in the dataset. Avalanche hazard was not normalized by total county area because it caused an over-emphasis on small counties, and because avalanches are a highly local hazard.

None = 0 AvalanchesLow = 1 AvalancheMedium = 2-5 AvalanchesHigh = 6-10 Avalanches

Earthquake Hazard

United States Geological Survey. “Earthquake Hazard Maps”. 1:2,000,000. “Peak Ground Acceleration 2% in 50 Years”. < http://earthquake.usgs.gov/hazards/products/conterminous/

. Downloaded 07/2016.

Classification

Peak ground acceleration (% gravity) with a 2% likelihood in 50 years was averaged by United States County, and the earthquake hazard of counties was classified based upon this average.

Low = 0 - 14.25 % gravity peak ground accelerationMedium = 14.26 - 47.5 % gravity peak ground accelerationHigh = 47.5+ % gravity peak ground acceleration

Flood Hazard

United States Federal Emergency Management Administration. “National Flood Hazard Layer”. 1:10,000. “0.2 Percent Annual Flood Area”. < https://data.femadata.com/FIMA/Risk_MAP/NFHL/

. Downloaded 07/2016.

Classification

The National Flood Hazard Layer 0.2 Percent Annual Flood Area was spatially intersected with the United States Counties layer, splitting flood areas by county and adding county information to flood areas. Flood area was aggregated by county, expressed as a fraction of the total county land area, and flood hazard was classified based upon percentage of land that is susceptible to flooding. National Flood Hazard Layer does not cover the entire United States; coverage is focused on populated areas. Areas not included in National Flood Hazard Layer were assigned flood risk of Low in order to include these areas in further analysis.

Low = 0-.001% area susceptibleMedium = .00101 % - .005 % area susceptibleHigh = .00501+ % area susceptible

Heat Wave Hazard

United States Center for Disease Control and Prevention. “National Climate Assessment”. Contiguous United States Counties. “Extreme Heat Events: Heat Wave Days in May - September for years 1981-2010”. Downloaded 06/2016.

Classification

Heat wave was classified by dividing counties based upon the number of heat wave days they experienced over the 30 year time period described in the dataset.

Low = 126 - 171 Heat wave DaysMedium = 172 – 187 Heat wave DaysHigh = 188 – 255 Heat wave Days

Hurricane Hazard

National Oceanic and Atmospheric Administration. Coastal Services Center. “Historical North Atlantic Tropical Cyclone Tracks, 1851-2004”. 1: 2,000,000. < https://catalog.data.gov/dataset/historical-north-atlantic-tropical-cyclone-tracks-1851-2004-direct-download

. Downloaded 06/2016.

National Oceanic and Atmospheric Administration. Coastal Services Center. “Historical North Pacific Tropical Cyclone Tracks, 1851-2004”. 1: 2,000,000. < https://catalog.data.gov/dataset/historical-north-atlantic-tropical-cyclone-tracks-1851-2004-direct-download

. Downloaded 06/2016.

Classification

Atlantic and Pacific datasets were merged. Tropical storm and disturbance tracks were filtered out leaving hurricane tracks. Each hurricane track was assigned the value of the category number that describes that event. Weighting each event by intensity ensures that areas with higher intensity events are characterized as being more hazardous. Values describing each hurricane event were aggregated by United States County, normalized by total county area, and the hurricane hazard of counties was classified based upon the normalized value.

Landslide Hazard

United States Geological Survey. “Landslide Overview Map of the United States”. 1:4,000,000. “Landslide Incidence and Susceptibility in the Conterminous United States”. < https://catalog.data.gov/dataset/landslide-incidence-and-susceptibility-in-the-conterminous-united-states-direct-download

. Downloaded 07/2016.

Classification

The classifications of High, Moderate, and Low landslide susceptibility and incidence from the study were numerically coded, the average value was computed for each county, and the landslide hazard was classified based upon the average value.

Long-Term Drought Hazard

United States Drought Monitor, Drought Mitigation Center, United States Department of Agriculture, National Oceanic and Atmospheric Administration. “Drought Monitor Summary Map”. “Long-Term Drought Impact”. < http://droughtmonitor.unl.edu/MapsAndData/GISData.aspx >. Downloaded 06/2016.

Classification

Short-term drought areas were filtered from the data; leaving only long-term drought areas. United States Counties were assigned the average U.S. Drought Monitor Classification Scheme Drought Severity Classification value that characterizes the county area. County long-term drought hazard was classified based upon average Drought Severity Classification value.

Low = 1 – 1.75 average Drought Severity Classification valueMedium = 1.76 -3.0 average Drought Severity Classification valueHigh = 3.0+ average Drought Severity Classification value

Snowfall Hazard

United States National Oceanic and Atmospheric Administration. “1981-2010 U.S. Climate Normals”. 1: 2,000,000. “Annual Snow Normal”. < http://www1.ncdc.noaa.gov/pub/data/normals/1981-2010/products/precipitation/

. Downloaded 08/2016.

Classification

Average yearly snowfall was joined with point location of weather measurement stations, and stations without valid snowfall measurements were filtered out (leaving 6233 stations). Snowfall was interpolated using least squared distance interpolation to create a .05 degree raster describing an estimate of yearly snowfall for the United States. The average yearly snowfall raster was aggregated by county to yield the average yearly snowfall per United States County. The snowfall risk of counties was classified by average snowfall.

None = 0 inchesLow = .01- 10 inchesMedium = 10.01- 50 inchesHigh = 50.01+ inches

Tornado Hazard

United States National Oceanic and Atmospheric Administration Storm Prediction Center. “Severe Thunderstorm Database and Storm Data Publication”. 1: 2,000,000. “United States Tornado Touchdown Points 1950-2004”. < https://catalog.data.gov/dataset/united-states-tornado-touchdown-points-1950-2004-direct-download

. Downloaded 07/2016.

Classification

Each tornado touchdown point was assigned the value of the Fujita Scale that describes that event. Weighting each event by intensity ensures that areas with higher intensity events are characterized as more hazardous. Values describing each tornado event were aggregated by United States County, normalized by total county area, and the tornado hazard of counties was classified based upon the normalized value.

Volcano Hazard

Smithsonian Institution National Volcanism Program. “Volcanoes of the World”. “Holocene Volcanoes”. < http://volcano.si.edu/search_volcano.cfm

. Downloaded 07/2016.

Classification

Volcano coordinate locations from spreadsheet were mapped and aggregated by United States County. Volcano count was normalized by county area, and the volcano hazard of counties was classified based upon the number of volcanoes present per unit area.

None = 0 volcanoes/100 kilometersLow = 0.000915 - 0.007611 volcanoes / 100 kilometersMedium = 0.007612 - 0.018376 volcanoes / 100 kilometersHigh = 0.018377- 0.150538 volcanoes / 100 kilometers

Wildfire Hazard

United States Department of Agriculture, Forest Service, Fire, Fuel, and Smoke Science Program. “Classified 2014 Wildfire Hazard Potential”. 270 meters. < http://www.firelab.org/document/classified-2014-whp-gis-data-and-maps

. Downloaded 06/2016.

Classification

The classifications of Very High, High, Moderate, Low, Very Low, and Non-Burnable/Water wildfire hazard from the study were numerically coded, the average value was computed for each county, and the wildfire hazard was classified based upon the average value.

In 2021, severe thunderstorms in the United States caused economic losses of about 37.25 billion U.S. dollars. In total, natural disasters in the country caused about 169 billion U.S. dollars in economic losses in that year.

As climate change increases the frequency and severity of natural disasters like floods, wildfires and hurricanes, funding supports the growing need for emergency relief services. Providers rely on government funding, mainly from FEMA under the US Department of Homeland Security, which surged until 2024. Private donations from individuals, corporations and foundations account for over two-thirds of total funds and are crucial. Strong growth in disposable income and corporate profit has supported these donations. With this diverse funding, industry revenue is expected to climb at a 3.0% CAGR, reaching $16 billion in 2025. However, a 0.6% drop is expected in 2025 as government and corporate funds weaken. In addition to funding, FEMA collaborates with Voluntary Agency Liaisons (VALs), Voluntary Organizations Active in Disaster (VOADs) and state and local emergency management agencies to organize and coordinate NGOs and other groups' services. This partnership ensures a unified, efficient and effective response to address disaster survivors' needs. Disaster relief organizations establish themselves strategically where disasters are prevalent for maximum efficiency. A result of the geographical spread of these incidents, the concentration of disaster relief services remains generally low. However, larger organizations can leverage their size to reap economies of scale, reinvesting profit into enhanced tools and service provision. Well-established nonprofits like the Red Cross might operate locally but benefit from a more expansive infrastructure. In the future, migration and its impact on population density, a location's infrastructure, mitigation efforts and the strength of social support networks will influence the total cost of a disaster event. New technologies will aid in reducing costs and improving the efficiency of service providers. Drones, mobile applications and AI tools to improve disaster relief by delivering essential supplies, optimizing resource management, enhancing communication, assisting in preparedness and reducing labor costs. Large and small relief organizations can leverage these technologies, although larger organizations may gain more from scale efficiencies. Local and state government investments may mitigate the impact of natural disasters, reducing demand for relief services. Still, potential reorganization of FEMA and cuts to NOAA and FEMA can disrupt services. With declines in corporate profit growth, slower local and state government investment growth and uncertainty in federal funding, industry revenue growth will slow to a CAGR of 1.2%, reaching $17.0 billion in 2030 with a slight profit decline.

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).

Flash flooding is the top weather-related killer, responsible for an average of 140 deaths per year across the United States. Although precipitation forecasting and understanding of flash flood causes have improved in recent years, there are still many unknown factors that play into flash flooding. Despite having accurate and timely rainfall reports, some river basins simply do not respond to rainfall as meteorologists might expect. The Flash Flood Potential Index (FFPI) was developed in order to gain insight into these “problem basins”, giving National Weather Service (NWS) meteorologists insight into the intrinsic properties of a river basin and the potential for swift and copious rainfall runoff.The goal of the FFPI is to quantitatively describe a given sub-basin’s risk of flash flooding based on its inherent, static characteristics such as slope, land cover, land use and soil type/texture. It leverages both Geographic Information Systems (GIS) as well as datasets from various sources. By indexing a given sub-basin’s risk of flash flooding, the FFPI allows the user to see which subbasins are more predisposed to flash flooding than others. Thus, the FFPI can be added to the situational awareness tools which can be used to help assess flash flood risk.

Underserved communities, especially those in coastal areas in Puerto Rico, face significant threats from natural hazards such as hurricanes and rising sea levels. Limited funding hinders the investment in costly mitigation measures, increasing exposure to natural disasters. Providing coastal resources and data products through effective communication mechanisms is fundamental to improving the well-being of these underserved coastal communities. The overall objectives of the pilot effort to engage and connect with underrepresented coastal communities in Puerto Rico were the following: (1) compile a comprehensive database of the projects and resources relevant to natural hazards in Puerto Rico; (2) foster connections with Puerto Rican interested parties to better understand their priorities regarding coastal hazards and provide them with pertinent U.S. Geological Survey (USGS) resources; and (3) identify knowledge gaps to guide future USGS projects in Puerto Rico. As a result of thi ...

This statistic shows the ten natural disasters that resulted in the most fatalities in the United States from 1900 and 2016. In 2005, Hurricane Katrina (listed as storm) caused 1,833 fatalities in the United States.

The dataset presents the number of affected people and the number of fatalities caused by natural disasters in El Salvador, Guatemala, Honduras, and Nicaragua, showing the variation over the years, differentiated by disaster type. The data have been assessed based on information obtained from EM-DAT.

For more information contact GIS4Tech: info@gis4tech.com. You can also visit the PREDISAN platform https://predisan.gis4tech.com/ca4 for detailed, accurate information.

Internally displaced persons are defined according to the 1998 Guiding Principles as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.

"Internally displaced persons - IDPs" refers to the number of people living in displacement as of the end of each year.

"Internal displacements (New Displacements)" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.

Contains data from IDMC's Global Internal Displacement Database.

Most scientists agree that climate change is the largest existential threat of our time. Despite the magnitude of the threat, surprisingly few climate-related discussions take place on social media. What factors drive online discussions about climate change? In this study, we examined the occurrence of Reddit discussions around three types of climate-related events: natural disasters (e.g., hurricanes, wildfires), political events (i.e., 2016 United States Presidential election), and policy events (i.e., United States’ withdrawal from Paris Climate Agreement, release of IPCC report). The objective was to understand how different types of events influence collective action as measured by discussions of climate change. Six large US cities were selected based on the occurrence of at least one locally-relevant natural disaster since 2014. Posts (N = 4.4 million) from subreddits of the selected cities were collected to obtain a six-month period before and after local natural disasters as well as climate-related political and policy events (which applied equally to all cities). Climate change discussions increased significantly for all three types of events, with the highest discussion during the 2016 elections. Further, discussions returned to baseline levels within 2 months following natural disasters and policy events but continued at elevated rates for up to 4 months following the 2016 elections. The findings suggest that collective discussions on climate change are driven more by political leaders’ controversial positions than life-threatening local natural disasters themselves. Implications for collective action are discussed.

The National Risk Index Counties - Natural Hazard Frequency (October 2020) map service contains county-level Natural Hazard Frequency data.The National Risk Index (NRI) is an online tool to help illustrate the nation’s communities most at risk of natural hazards. It leverages authoritative nationwide datasets and multiplies values for exposure, hazard frequency, and historic loss ratios to derive Expected Annual Loss for 18 natural hazards; and it combines this metric with Social Vulnerability and Community Resilience data to generate a unitless, normalized Risk Index score for every census tract and county in the United States.The NRI incorporates data for the following natural hazards: Avalanche, Coastal Flooding, Cold Wave, Drought, Earthquake, Hail, Heat Wave, Hurricane, Ice Storm, Landslide, Lightning, Riverine Flooding, Strong Wind, Tornado, Tsunami, Volcanic Activity, Wildfire, and Winter Weather.Sources for Expected Annual Loss data include Arizona State University's Center for Emergency Management and Homeland Security, CoreLogic, Federal Emergency Management Agency (FEMA), Iowa State University, National Aeronautics and Space Administration (NASA), National Avalanche Center, National Oceanic and Atmospheric Administration (NOAA), NOAA National Hurricane Center (NHC), NOAA National Weather Service (NWS), NOAA Storm Prediction Center (SPC), NOAA / Vaisala National Lightning Detection Network (NLDN), Smithsonian Institution, State of Alaska, State of California, State of Hawaii, State of Oregon, State of Washington, United Nations Office for Disaster Risk Reduction, University of Nebraska-Lincoln, US Army Corps of Engineers (USACE), US Department of Agriculture (USDA), USDA Forest Service, and United States Geological Survey (USGS). Data for Social Vulnerability and Community Resilience is provided by University of South Carolina's Hazards & Vulnerability Research Institute (HVRI).Get the intended user experience at The National Risk Index application

Weather DescriptionThis feature service depicts the National Weather Service (NWS) watches, warnings, and advisories within the United States. Watches and warnings are classified into 43 categories.A warning is issued when a hazardous weather or hydrologic event is occurring, imminent or likely. A warning means weather conditions pose a threat to life or property. People in the path of the storm need to take protective action.A watch is used when the risk of a hazardous weather or hydrologic event has increased significantly, but its occurrence, location or timing is still uncertain. It is intended to provide enough lead time so those who need to set their plans in motion can do so. A watch means that hazardous weather is possible. People should have a plan of action in case a storm threatens, and they should listen for later information and possible warnings especially when planning travel or outdoor activities.An advisory is issued when a hazardous weather or hydrologic event is occurring, imminent or likely. Advisories are for less serious conditions than warnings, that cause significant inconvenience and if caution is not exercised, could lead to situations that may threaten life or property.SourceNational Weather Service RSS-CAP Warnings and Advisories: Public AlertsNational Weather Service Boundary Overlays: AWIPS Shapefile DatabaseUpdate FrequencyThe services is updated every 5 minutes using the Aggregated Live Feeds methodology.The overlay data is checked and updated daily from the official AWIPS Shapefile Database.Area CoveredUnited States and TerritoriesWhat can you do with this layer?Customize the display of each attribute by using the Change Style option for any layer.Query the layer to display only specific types of weather watches and warnings.Add to a map with other weather data layers to provide insight on hazardous weather events.Use ArcGIS Online analysis tools, such as Enrich Data, to determine the potential impact of weather events on populations.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.LayersUSA Weather Watches and Warnings - Public Forecast ZonesUSA Weather Watches and Warnings - Fire Forecast ZonesUSA Weather Watches and Warnings - US CountiesUSA Weather Watches and Warnings - US States and TerritoriesUSA Weather Watches and Warnings - Coastal and Offshore Marine ZonesUSA Weather Watches and Warnings - Events Ordered by Size and SeverityUSA Weather Watches and Warnings - Extreme EventsUSA Weather Watches and Warnings - Severe EventsUSA Weather Watches and Warnings - Moderate EventsUSA Weather Watches and Warnings - Minor EventsUSA Weather Watches and Warnings - Other EventsWSM (Night w/yellow boundaries)World HillshadeWorld Street Map Canvas (Night w/yellow boundaries)Flood DescriptionThis feature service depicts the National Weather Service (NWS) watches, warnings, and advisories within the United States. Watches and warnings are classified into 43 categories.A warning is issued when a hazardous weather or hydrologic event is occurring, imminent or likely. A warning means weather conditions pose a threat to life or property. People in the path of the storm need to take protective action.A watch is used when the risk of a hazardous weather or hydrologic event has increased significantly, but its occurrence, location or timing is still uncertain. It is intended to provide enough lead time so those who need to set their plans in motion can do so. A watch means that hazardous weather is possible. People should have a plan of action in case a storm threatens, and they should listen for later information and possible warnings especially when planning travel or outdoor activities.An advisory is issued when a hazardous weather or hydrologic event is occurring, imminent or likely. Advisories are for less serious conditions than warnings, that cause significant inconvenience and if caution is not exercised, could lead to situations that may threaten life or property.SourceNational Weather Service RSS-CAP Warnings and Advisories: Public AlertsNational Weather Service Boundary Overlays: AWIPS Shapefile DatabaseUpdate FrequencyThe services is updated every 5 minutes using the Aggregated Live Feeds methodology.The overlay data is checked and updated daily from the official AWIPS Shapefile Database.Area CoveredUnited States and TerritoriesWhat can you do with this layer?Customize the display of each attribute by using the Change Style option for any layer.Query the layer to display only specific types of weather watches and warnings.Add to a map with other weather data layers to provide insight on hazardous weather events.Use ArcGIS Online analysis tools, such as Enrich Data, to determine the potential impact of weather events on populations.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.LayersUSA Weather Watches and Warnings - Events Ordered by Size and SeverityTopographicWorld HillshadeWorld Street Map Canvas (Night w/yellow boundaries)Tornado DescriptionThis map contains continuously updated U.S. tornado reports, wind storm reports and hail storm reports. You can click on each to receive information about the specific location and read a short description about the issue.Each layer is updated 4 times hourly from data provided by NOAA’s National Weather Service Storm Prediction Center.A full archive of storm events can be accessed from the NOAA National Centers for Environmental Information.SourceNOAA Storm Prediction Center https://www.spc.noaa.gov/climo/reportsUpdate FrequencyThe service is updated every 15 minutes using the Aggregated Live Feeds MethodologyArea CoveredCONUS (Contiguous United States)What can you do with this layer?This map service is suitable for data discovery and visualization.Change the symbology of each layer using single or bi-variate smart mapping. For instance, use size or color to indicate the intensity of a tornado.You can click on each to receive information about the specific location and read a short description about the issue.Query the attributes to show only specific event types or locations.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.LayersUSA Storm Reports - NOAA TORNADO Storm Reports (24 hours)USA Storm Reports - NOAA WIND Storm Reports (24 hours)USA Storm Reports - NOAA TORNADO Storm Reports (past week)TopographicWorld HillshadeWorld Street Map Canvas (Night w/yellow boundaries)Wildfire DescriptionThis layer presents recent wildfire activity for the United States, featuring data from GeoMAC. Wildfire activity is downloaded from the GeoMAC Outgoing Datasets from the USGS. GeoMAC was designed to give fire managers near real-time information based on agency reports and fire perimeter data. GeoMAC is updated daily based upon input from incident intelligence sources, GPS data, and infrared (IR) imagery from fixed wing and satellite platforms.Fire Perimeter is a product of Geospatial Multi-Agency Coordination (GeoMAC). In order to give fire managers near real-time information, fire perimeter data is updated daily based upon input from incident intelligence sources, GPS data, infrared (IR) imagery from fixed wing and satellite platforms. We gather this data from the USGS feed (NIFC large fires, NIFC situation reports, perimeters). These shape files from the feed are parsed using the Aggregated Live Feeds methodology to take the returned information and serve the data through ArcGIS Server as a map service.See more information about GeoMAC.To find out more about the Esri Disaster Response Program, visit https://www.esri.com/services/disaster-response.From GeoMAC: Information presented on this website is a representation of the existing wildfire situation in the continental United States including Alaska. While every effort is made to provide accurate and complete information, proximity of fires to populated areas may not be accurately portrayed.Earthquake DescriptionIn addition to displaying earthquakes by magnitude, this service also provide earthquake impact details. Impact is measured by population as well as models for economic and fatality loss. For more details, see: PAGER Alerts.Events are updated as frequently as every 5 minutes and are available up to 30 days with the following exceptions:Events with a Magnitude LESS than 3.0 are retained for 3 daysEvents with a Magnitude LESS than 4.5 are retained for 7 daysIn addition to event points, ShakeMaps are also provided. These have been dissolved by Shake Intensity to reduce the Layer Complexity.The specific layers provided in this service have been Time Enabled and include:Events by Magnitude: The event’s seismic magnitude value.Contains PAGER Alert Level: USGS PAGER (Prompt Assessment of Global Earthquakes for Response) system provides an automated impact level assignment that estimates fatality and economic loss.Contains Significance Level: An event’s significance is determined by factors like magnitude, max MMI, ‘felt’ reports, and estimated impact.Shake Intensity: The Instrumental Intensity or Modified Mercalli Intensity (MMI) for available events.For field terms and technical details, see: ComCat DocumentationThis map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. Always refer to USGS source for official guidance.LayersRecent Earthquakes - Events by MagnitudeRecent Earthquakes - Shake IntensityTopographicWorld HillshadeWorld Street Map Canvas (Night w/yellow boundaries)Hurricane DescriptionHurricane tracks and positions provide information on where the storm has been, where it is currently located, and where it is predicted to go. Each storm location is depicted by the sustained wind speed, according to the Saffir-Simpson Scale. It should be noted that the Saffir-Simpson Scale only applies to hurricanes in the Atlantic and Eastern Pacific basins, however all storms are still symbolized

County Disaster Declaration detailed declaration records developed from FEMA Historic Disasters Declaration by County 1964 - 2013 for NSGIC resiliency project.NSGIC Data Citation:This project uses existing FEMA data resources that are the authoritative sources of information on this topic, including geospatial data files and open data APIs that were used to access available FEMA Federally-declared Natural Disaster data in the United States available from 1964 to 2014 (through 2013).To support our mapping needs, NSGIC downloaded a snapshot of FEMA data and published our own data Service Definitions and Feature Layers on NSGIC’s ArcGIS Online Mapping Platform to create the unfiltered Feature Layer Services we needed to support our mapping needs of the FEMA Federally Declared Disaster data.Note: These original data sources reflect a variety of inconsistencies and completeness is data collection, as well as changing definitions and priorities in FEMA’s disaster declaration information collection since record-keeping began in 1964. The original data was not modified.To publish the new Feature Layers on ArcGIS Online, NSGIC joined the FEMA Natural Disaster data with an Esri US County polygon shapefile with county population and demographic attributes from the U.S. Census Bureau’s American Community Survey. NSGIC added the 2010 and 2015 population estimates from the Census Bureau’s American Community Survey to relate the impacts of every declared natural disaster to current time frame.A significant portion of the available attribute data is not displayed in the NSGIC interactive maps, but is accessible through the site by experienced users.More recent data may be available from the original sourcesFEMA Data Citation:Data for this project was downloaded from FEMA in April 2016 and reflects the data available at that time using the available APIs.This product uses the Federal Emergency Management Agency’s API, but is not endorsed by FEMA.FEMA cannot verify the quality and/or timeliness of any data or any analysis derived therefrom after the data has been retrieved from FEMA.gov.NSGIC Data Citation:This project uses existing FEMA data resources that are the authoritative sources of information on this topic, including geospatial data files and open data APIs that were used to access available FEMA Federally-declared Natural Disaster data in the United States available from 1964 to 2014 (through 2013).To support our mapping needs, NSGIC downloaded a snapshot of FEMA data and published our own data Service Definitions and Feature Layers on NSGIC’s ArcGIS Online Mapping Platform to create the unfiltered Feature Layer Services we needed to support our mapping needs of the FEMA Federally Declared Disaster data.Note: These original data sources reflect a variety of inconsistencies and completeness is data collection, as well as changing definitions and priorities in FEMA’s disaster declaration information collection since record-keeping began in 1964. The original data was not modified.To publish the new Feature Layers on ArcGIS Online, NSGIC joined the FEMA Natural Disaster data with an Esri US County polygon shapefile and included the available county population and demographic attributes from the U.S. Census Bureau’s American Community Survey. A significant portion of the available attribute data is not displayed in the NSGIC interactive maps, but is accessible through the site by experienced users.More recent data may be available from the original sourcesFEMA Data Citation:Data for this project was downloaded from FEMA in April 2016 and reflects the data available at that time using the available APIs.This product uses the Federal Emergency Management Agency’s API, but is not endorsed by FEMA.FEMA cannot verify the quality and/or timeliness of any data or any analysis derived therefrom after the data has been retrieved from FEMA.gov.

Underserved communities, especially those in coastal areas in Puerto Rico, face significant threats from natural hazards such as hurricanes and rising sea levels. Limited funding hinders the investment in costly mitigation measures, increasing exposure to natural disasters. Providing coastal resources and data products through effective communication mechanisms is fundamental to improving the well-being of these underserved coastal communities. The overall objectives of the pilot effort to engage and connect with underrepresented coastal communities in Puerto Rico were the following: (1) compile a comprehensive database of the projects and resources relevant to natural hazards in Puerto Rico; (2) foster connections with Puerto Rican interested parties to better understand their priorities regarding coastal hazards and provide them with pertinent U.S. Geological Survey (USGS) resources; and (3) identify knowledge gaps to guide future USGS projects in Puerto Rico. To address these objectives, the research team held a virtual internal meeting amongst USGS colleagues (organized with a professional facilitator) to identify and gather information on existing USGS data, knowledge, and tools available for natural hazards and resources in Puerto Rico. The goals of the meeting were to: (1) exchange knowledge among colleagues, (2) broaden the network of participants, (3) foster potential collaborative relationships with researchers engaged in USGS hazards projects in Puerto Rico, and (4) document all the research taking place in Puerto Rico related to natural hazards and resources. The result was a database of USGS natural hazards projects being conducted or recently completed in Puerto Rico. For further information about this data, refer to the associated journal article (Torres-García and others, 2024).

County Disaster Declaration Summary Records developed from FEMA Historic Disasters Declaration by County 1964 - 2013 for NSGIC resiliency project.NSGIC Data Citation:This project uses existing FEMA data resources that are the authoritative sources of information on this topic, including geospatial data files and open data APIs that were used to access available FEMA Federally-declared Natural Disaster data in the United States available from 1964 to 2014 (through 2013).To support our mapping needs, NSGIC downloaded a snapshot of FEMA data and published our own data Service Definitions and Feature Layers on NSGIC’s ArcGIS Online Mapping Platform to create the unfiltered Feature Layer Services we needed to support our mapping needs of the FEMA Federally Declared Disaster data.Note: These original data sources reflect a variety of inconsistencies and completeness is data collection, as well as changing definitions and priorities in FEMA’s disaster declaration information collection since record-keeping began in 1964. The original data was not modified.To publish the new Feature Layers on ArcGIS Online, NSGIC joined the FEMA Natural Disaster data with an Esri US County polygon shapefile with county population and demographic attributes from the U.S. Census Bureau’s American Community Survey. NSGIC added the 2010 and 2015 population estimates from the Census Bureau’s American Community Survey to relate the impacts of every declared natural disaster to current time frame.A significant portion of the available attribute data is not displayed in the NSGIC interactive maps, but is accessible through the site by experienced users.More recent data may be available from the original sourcesFEMA Data Citation:Data for this project was downloaded from FEMA in April 2016 and reflects the data available at that time using the available APIs.This product uses the Federal Emergency Management Agency’s API, but is not endorsed by FEMA.FEMA cannot verify the quality and/or timeliness of any data or any analysis derived therefrom after the data has been retrieved from FEMA.gov.NSGIC Data Citation:This project uses existing FEMA data resources that are the authoritative sources of information on this topic, including geospatial data files and open data APIs that were used to access available FEMA Federally-declared Natural Disaster data in the United States available from 1964 to 2014 (through 2013).To support our mapping needs, NSGIC downloaded a snapshot of FEMA data and published our own data Service Definitions and Feature Layers on NSGIC’s ArcGIS Online Mapping Platform to create the unfiltered Feature Layer Services we needed to support our mapping needs of the FEMA Federally Declared Disaster data.Note: These original data sources reflect a variety of inconsistencies and completeness is data collection, as well as changing definitions and priorities in FEMA’s disaster declaration information collection since record-keeping began in 1964. The original data was not modified.To publish the new Feature Layers on ArcGIS Online, NSGIC joined the FEMA Natural Disaster data with an Esri US County polygon shapefile and included the available county population and demographic attributes from the U.S. Census Bureau’s American Community Survey. A significant portion of the available attribute data is not displayed in the NSGIC interactive maps, but is accessible through the site by experienced users.More recent data may be available from the original sourcesFEMA Data Citation:Data for this project was downloaded from FEMA in April 2016 and reflects the data available at that time using the available APIs.This product uses the Federal Emergency Management Agency’s API, but is not endorsed by FEMA.FEMA cannot verify the quality and/or timeliness of any data or any analysis derived therefrom after the data has been retrieved from FEMA.gov.