AndreaBozzo/ceres-open-data-index huggingface dataset:
Police Districts

There are seven police districts in Washington, DC, and each police district is divided into three sectors, which are groups of Police Service Areas (PSAs). Each police district has between seven and nine PSAs. Every resident lives in a PSA, and every PSA has a team of assigned police officers and officials. The Metropolitan Police Department (MPD) is fully committed to ensuring the safety and well-being of every person who lives, works, and visits the District. That commitment includes those members of our community who are served by MPD's Special Liaison Branch. The Department’s Special Liaison Branch (SLB) is a model for community policing in its work with historically underserved communities. Learn more about MPD patrol services at [mpdc.dc.gov/patrolservices] and special liaison units at [mpdc.dc.gov/slb].
National Weather Service Wind Gust Forecast

This map displays the forecasted wind gust over the next 72 hours across the Contiguous United States, Alaska, Guam, Hawaii, and Puerto Rico. [Wind Gust] is the maximum 3-second wind speed (in knots) forecast to occur within a 2-minute interval at a height of 10 meters [Above Ground Level (AGL)]. Wind gust forecasts are valid at the top of the indicated hour. Data are updated hourly from the [National Digital Forecast Database (NDFD)] produced by the National Weather Service. Where is the data coming from? [The National Digital Forecast Database (NDFD)] was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces gridded forecasts of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from [National Weather Service (NWS)] field offices working in collaboration with the [National Centers for Environmental Prediction (NCEP)]. All of these organizations are under the administration of the [National Oceanic and Atmospheric Administration (NOAA)]. Sources: * CONUS: [https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.wgust.bin] * ALASKA: [https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.alaska/VP.001-003/ds.wgust.bin] * HAWAII: [https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.hawaii/VP.001-003/ds.wgust.bin] * GUAM: [https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.guam/VP.001-003/ds.wgust.bin] * PUERTO RICO: [https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.puertori/VP.001-003/ds.wgust.bin] Where can I find other [NDFD] data? The Source data is downloaded and parsed using the [Aggregated Live Feeds methodology] to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise. What can you do with this layer? This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation. Revisions * Nov 24, 2025: Added data for Alaska, Guam, Hawaii, and Puerto Rico identified by ‘region’ field for filtering. Added Coded Value Domain for Beaufort wind scale on ‘force’ field. This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our [Live Feed Status] Page!
National Weather Service Wind Speed Forecast

This map displays the forecasted wind speeds over the next 72 hours across the contiguous United States, Alaska, Guam, Hawaii, and Puerto Rico. [Wind Speed] is the expected 10-meter [Above Ground Level (AGL)] sustained wind speed (in knots) for the indicated hour. Wind speed forecasts are valid at the top of the indicated hour. Data are updated hourly from the [National Digital Forecast Database] produced by the National Weather Service. Where is the data coming from? [The National Digital Forecast Database (NDFD)] was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces forecast data of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from [National Weather Service (NWS)] field offices working in collaboration with the [National Centers for Environmental Prediction (NCEP)]. All of these organizations are under the administration of the [National Oceanic and Atmospheric Administration (NOAA)]. Sources: * CONUS: [https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.wspd.bin] * ALASKA: [https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.alaska/VP.001-003/ds.wspd.bin] * HAWAII: [https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.hawaii/VP.001-003/ds.wspd.bin] * GUAM: [https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.guam/VP.001-003/ds.wspd.bin] * PUERTO RICO: [https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.puertori/VP.001-003/ds.wspd.bin] Where can I find other [NDFD] data? The Source data is downloaded and parsed using the [Aggregated Live Feeds methodology] to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise. What can you do with this layer? This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation. Revisions * Dec 29, 2025: Added data for Alaska, Guam, Hawaii, and Puerto Rico identified by ‘region’ field for filtering. Added Coded Value Domain for Beaufort wind scale on ‘force’ field. This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our [Live Feed Status] Page!
RISPP - Road Assets Exposed to Storm Surge & SLR by 2100

This layer was created by the Rhode Island Statewide Planning Program as part of the 2016 Municipal Transportation Assets Vulnerable to Sea Level Rise and Storm Surge Project. The layer depicts road centerline segments potentially exposed to storm surge inundation under sea level rise conditions before 2100, based on predictions of seven feet of sea level rise for the State of Rhode Island by the Rhode Island Coastal Resources Management Council (CRMC). The underlying road structure, and much of the attribute data, originates from the road network layer created by the Rhode Island Department of Transportation. The sea level rise scenarios of one, three, five, and seven feet of sea level rise originated with the STORMTOOLS data set created by CRMC. The modeling of storm surge and sea level rise inundation zones originated with the STORMTOOLS data set created by CRMC. Other data came from the Rhode Island Public Transportation Authority. This layer was created by the Rhode Island Statewide Planning Program as part of the 2016 Municipal Transportation Assets Vulnerable to Sea Level Rise and Storm Surge Project. The layer depicts road centerline segments potentially exposed to storm surge inundation under sea level rise conditions before 2100.
Intermodal Freight Facilities Marine Roll on Roll off

Intermodal Freight Facilities Marine Roll on Roll off This feature layer, utilizing data from the [Bureau of Transportation Statistics] (BTS), displays the major marine roll on-roll off Intermodal freight facilities within the U.S. Per [Investopedia], "Businesses use intermodal freight shipping both domestically and internationally because it lessens the amount of handling performed with the cargo during the trip and can reduce costs. Intermodal freight transportation is also a safe and secure method because it eliminates the handling of the freight itself during transportation, which reduces damage and loss, drivers can handle more loads in a shorter period of time, and additional security is provided at terminals, rail tracks, and ramps, which prevents theft." The term roll on/roll off (Ro/Ro) is generally reserved for much larger ocean going cargo vessels but can sometimes be used for smaller ships like ferries. These cargo ships are designed to carry wheeled cargo such as cars, trucks, semi-trailer trucks, trailers, and railroad cars, that are driven on and off the ships on their own wheels. This dataset is one of several layers in the Bureau of Transportation Statistics Intermodal Freight Facility Database. [Marine Roll on Roll off Intermodal Facilities] Intermodal Marine Roll on Roll off Facilities Data currency: This cached Esri service is checked weekly for updates from its federal source ([Intermodal Freight Facilities Marine Roll-on Roll-off]) Data modification(s): none For more information: [Intermodal Transportation Database] Support documentation: [Metadata] For feedback please contact: [ArcGIScomNationalMaps@esri.com] Thumbnail: Esri Basemaps (Imagery) Bureau of Transportation Statistics Per [BTS], "The Bureau of Transportation Statistics (BTS), part of the Department of Transportation (DOT) is the preeminent source of statistics on commercial aviation, multimodal freight activity, and transportation economics, and provides context to decision makers and the public for understanding statistics on transportation."
SACS NOAA ESI Shoreline US Virgin Islands

To characterize shoreline types across the study area for the purposes of identifying potential coastal storm risk management and risk reduction strategies, the SACS leveraged the NOAA Environmental Sensitivity Shoreline Index data which provided a consistent shoreline dataset across the study area. While the primary use of these data is to support oil spill contingency planning, the data can also be used to support a variety of coastal planning applications (NOAA 2017, NOAA 2000). Criteria used to characterize the shoreline included the shoreline setting, degree of exposure to wave and tidal energy, substrate composition, substrate permeability, slope, the presence of wetlands, development, coastal armor, and shoreline stabilization structures. The SACS Geospatial Appendix details specific NOAA ESI Code reclassifications.
MODIS True Color - Terra Surface Reflectance

This series of products from MODIS represents the only daily global composites available and is suitable for use at global and regional levels. This True Color band composition (Bands 1 4 3 | Red, Green, Blue) most accurately shows how we see the earth’s surface with our own eyes. It is a natural looking image that is useful for land surface, oceanic and atmospheric analysis. There are four True Color products in total. For each satellite (Aqua and Terra) there is a 250 meter corrected reflectance product and a 500 meter surface reflectance product. Although the resolution is coarser than other satellites, this allows for a global collection of imagery on a daily basis, which is made available in near real-time. In contrast, Landsat needs 16 days to collect a global composite. Besides the maximum resolution difference, the surface and corrected reflectance products also differ in the algorithm used for atmospheric correction. NASA Global Imagery Browse Services (GIBS) This image layer provides access to a subset of the NASA [Global Imagery Browse Services (GIBS)], which are a set of standard services to deliver global, full-resolution satellite imagery. The GIBS goal is to enable interactive exploration of NASA's Earth imagery for a broad range of users. The purpose of this image layer, and the other GIBS image services hosted by Esri, is to enable convenient access to this beautiful and useful satellite imagery for users of ArcGIS. The source data used by this image layer is a finished image; it is not recommended for quantitative analysis. Several full resolution, global imagery products are built and served by GIBS in near real-time (usually within 3.5 hours of observation). These products are built from NASA Earth Observing System satellites data courtesy of LANCE data providers and other sources. The MODIS instrument aboard Terra and Aqua satellites, the AIRS instrument aboard Aqua, and the OMI instrument aboard Aura are used as sources. Several of the MODIS global products are made available on this Esri hosted service. This image layer hosted by Esri provides direct access to one of the GIBS image products. The Esri servers do not store any of this data itself. Instead, for each received data request, multiple image tiles are retrieved from GIBS, which are then processed and assembled into the proper image for the response. This processing takes place on-the-fly, for each and every request. This ensures that any update to the GIBS data is immediately available in the Esri mosaic service. Note on Time: The image service supporting this layer is time enabled, but time has been disabled on this image layer so that the most recent imagery displays by default. If you would like to view imagery over time, you can update the layer properties to enable time animation and [configure time settings]. The results can be saved in a web map to use later or share with others.
Intermodal Freight Facilities Air-to-Truck

Intermodal Freight Facilities Air-to-Truck This feature layer, utilizing data from the Bureau of Transportation Statistics (BTS), displays Air-to-Truck Intermodal freight facilities within Puerto Rico and the U.S. This layer, per [BTS], "can be used to understand the intermodal connections for freight transfer and may be used for analysis, spatial mapping, and transportation modeling." It “includes air to truck intermodal freight facilities for the top 60 airports by total freight moved and is one of several layers in the Bureau of Transportation Statistics (BTS) Intermodal Freight Facility Database.” [USDOT BTS Intermodal Freight Facilities Air_to_Truck _ 800x400 _ screen capture] Minneapolis-St Paul International Airport Air to Truck Intermodal Facilities Data currency: This cached Esri service is checked monthly for updates from its federal source ([Intermodal Freight Facilities Air-to-Truck]). Data modification: none For more information: [Intermodal Transportation Database] For feedback, please contact: [ArcGIScomNationalMaps@esri.com] Thumbnail: Esri Basemaps (NAIP Imagery Hybrid) Bureau of Transportation Statistics Per [BTS], "The Bureau of Transportation Statistics (BTS), part of the Department of Transportation (DOT) is the preeminent source of statistics on commercial aviation, multimodal freight activity, and transportation economics, and provides context to decision makers and the public for understanding statistics on transportation."
Hailstorm Paths in the U.S.

Hailstorm Paths in the U.S. This feature layer, utilizing data from the National Oceanic and Atmospheric Administration (NOAA), displays hailstorm paths in the United States between 1955 and 2024. A hailstorm path shows the route of a hailstorm. Per [NOAA], "Hail is a form of precipitation consisting of solid ice that forms inside thunderstorm updrafts. Hail can damage aircraft, homes and cars, and can be deadly to livestock and people. Hailstones are formed when raindrops are carried upward by thunderstorm updrafts into extremely cold areas of the atmosphere and freeze. Hailstones then grow by colliding with liquid water drops that freeze onto the hailstone’s surface. Hail falls when it becomes heavy enough to overcome the strength of the thunderstorm updraft and is pulled toward the earth by gravity." [USDOC NOAA Hailstorm Paths in the U_S_ _ 800x400 _ screen capture] Super Hailstorm in Omaha, NE Data currency: December 30, 2024 Data source: [Storm Prediction Center] Data modifications: Added field Date_Calc For more information: [Severe Weather 101 - Hail]; [NSSL Research: Hail] Support documentation: [SPC Tornado, Hail, and Wind Database Format Specification] For feedback, please contact: [ArcGIScomNationalMaps@esri.com] Thumbnail source: Esri Basemaps National Oceanic and Atmospheric Administration Per [NOAA], its mission is "To understand and predict changes in climate, weather, ocean, and coasts, to share that knowledge and information with others, and to conserve and manage coastal and marine ecosystems and resources."
Landslides in New Jersey

This Landslides data contains point and other attributes for historic and recent landslide locations in New Jersey mapped by the New Jersey Geological Survey (NJGS). The landslides have occurred in many parts of the state and include slumps, debris flows, rockfalls and rockslides. Landslides in New Jersey are a geologic hazard in areas with steep to moderate slopes or geologic units prone to failure. They cause damage to utilities, property, and transportation routes. The average annual direct and indirect cost of New Jersey landslides is likely in the hundreds of thousands of dollars. New Jersey landslides have also caused fatalities and injuries. The landslides are caused by heavy rains, weathering, ocean waves, quarrying and construction activities.
Recent Earthquakes

In 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]. Consumption Best Practices: * As a service that is subject to very high usage, ensure peak performance and accessibility of your maps and apps by avoiding the use of non-cache-able relative Date/Time field filters. To accommodate filtering events by Date/Time, we suggest using the included "Age" fields that maintain the number of days or hours since a record was created or last modified, compared to the last service update. These queries fully support the ability to cache a response, allowing common query results to be efficiently provided to users in a high demand service environment. * When ingesting this service in your applications, avoid using [POST] requests whenever possible. These requests can compromise performance and scalability during periods of high usage because they too are not cache-able. Update Frequency: 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 4.5 are retained for 7 days * Events with a Significance value, "sig" field, of 600 or higher are retained for 90 days In 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 Documentation] Alternate Symbologies * Visit the [Classic USGS Feature Layer] item for a Rainbow view of Shakemap features. Revisions * Dec 22, 2025: Added ‘Hours Old’ field to Shake Intensity layer. * Sep 16, 2025: Exposed ‘UniqueId’ field in Shake Intensity Polygon layer. * Sep 14, 2025: Upgrade to Layer data update workflow, to improve reliability and scalability. * Aug 14, 2024: Added a default Minimum scale suppression of 1:6,000,000 on Shake Intensity layer. * Jul 11, 2024: Updated event popup, setting "Tsunami Warning" text to "Alert Possible" when flag is present. Also included hyperlink to tsunami warning center. * Feb 13, 2024: Updated feed logic to remove Superseded events This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. Always refer to [USGS] source for official guidance. If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our [Live Feed Status] Page!
Earthquake Faults and Folds in the USA

Earthquake Faults and Folds in the USA This feature layer, utilizing data from the U.S. Geological Survey"s (USGS) Earthquake Hazards Program (EHP), displays known faults and folds in the U.S. This layer, per [USGS], “contains information on faults and associated folds in the United States that demonstrate geological evidence of coseismic surface deformation in large earthquakes during the past 1.6 million years (Myr).” [NGDA Earthquake Faults and Folds in the USA _ 800x400 _ screen capture and popup] Central Virginia Fault Area Data downloaded: June 2026 Data source: [Faults] Data modification: none For more information: [Earthquake Hazards Program] For feedback please contact: [ArcGIScomNationalMaps@esri.com] Note: the map is designed to be displayed at a "States scale", in order to showcase the contents more efficiently. U.S. Geological Survey Per [USGS], "The USGS provides science about the natural hazards that threaten lives and livelihoods; the water, energy, minerals, and other natural resources we rely on; the health of our ecosystems and environment; and the impacts of climate and land-use change."
Hurricane Evacuation Routes (Archive)

This feature layer has been archived. It will no longer be updated or maintained. Hurricane Evacuation Routes This feature layer, utilizing data from the U.S. Government, displays the locations of hurricane evacuation routes in the United States. Per the [Mississippi Automated Resource Information System], "A hurricane evacuation route is a designated route used to direct traffic inland in case of a hurricane threat.“ [Hurricane Evacuation Routes Houston] Houston, Texas area hurricane evacuation routes Data currency: Caution should be exercised by the user of this feature layer. This data is over seventeen years old and has not been updated since creation. Data modification: None For feedback, please contact: [ArcGIScomNationalMaps@esri.com]
Tornado Tracks

Tornado Tracks This feature layer, utilizing data from the National Oceanic and Atmospheric Administration (NOAA), displays tornadoes in the United States, Puerto Rico and U.S. Virgin Islands between 1950 and 2025. A tornado track shows the route of a tornado. Per [NOAA], “A tornado is a narrow, violently rotating column of air that extends from a thunderstorm to the ground. Because wind is invisible, it is hard to see a tornado unless it forms a condensation funnel made up of water droplets, dust and debris. Tornadoes can be among the most violent phenomena of all atmospheric storms we experience. The most destructive tornadoes occur from supercells, which are rotating thunderstorms with a well-defined radar circulation called a mesocyclone. (Supercells can also produce damaging hail, severe non-tornadic winds, frequent lightning, and flash floods.)” [USDOC NOAA Tornado Tracks _ 800x400 _ screen capture] EF-5 Tornado Track (May 3, 1999) near Oklahoma City, Oklahoma Data currency: 2025 Data source: [Storm Prediction Center] Data modifications: Added field “Date_Calc” For more information: [Severe Weather 101 - Tornadoes]; [NSSL Research: Tornadoes] Support documentation: [SPC Tornado, Hail, and Wind Database Format Specification] For feedback, please contact: [ArcGIScomNationalMaps@esri.com] National Oceanic and Atmospheric Administration Per [NOAA], its mission is “To understand and predict changes in climate, weather, ocean, and coasts, to share that knowledge and information with others, and to conserve and manage coastal and marine ecosystems and resources.”