AndreaBozzo/ceres-open-data-index huggingface dataset:
Police Service Areas

Metropolitan Police Department (MPD) Police Service Areas (PSA). The dataset contains polygons representing of MPD PSA, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Police jurisdictions were initially created selecting street arcs from the planimetric street centerlines and street polygons, water polygons, real property boundaries and District of Columbia boundaries. 2019 Boundary Changes: Periodically, MPD conducts a comprehensive assessment of our patrol boundaries to ensure optimal operations. This effort considers current workload, anticipated population growth, development, and community needs. The overarching goals for the 2019 realignment effort included: optimal availability of police resources, officer safety and wellness, and efficient delivery of police services. These changes took effect on 01/10/2019. On 03/27/2019, this boundary was modified to adjust dispatching of North Capitol Street’s northwest access roads to be more operationally efficient.
National Flood Hazard Layer (NFHL) of New Jersey

This FEMA layer is used by NJDEP in an ArcGIS Online web mapping application. The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Datum of 1983.
Utilities Fire Threat Areas

In 2012, the CPUC ordered the development of a [statewide map] that is designed specifically for the purpose of identifying areas where there is an increased risk for utility associated wildfires. The development of the CPUC -sponsored fire-threat map, herein "CPUC Fire-Threat Map," started in [R.08-11-005] and continued in [R.15-05-006]. A multistep process was used to develop the statewide CPUC Fire-Threat Map. The first step was to develop Fire Map 1 (FM 1), an agnostic map which depicts areas of California where there is an elevated hazard for the ignition and rapid spread of powerline fires due to strong winds, abundant dry vegetation, and other environmental conditions. These are the environmental conditions associated with the catastrophic powerline fires that burned 334 square miles of Southern California in October 2007. FM 1 was developed by CAL FIRE and adopted by the CPUC in [Decision 16-05-036]. FM 1 served as the foundation for the development of the final CPUC Fire-Threat Map. The CPUC Fire-Threat Map delineates, in part, the boundaries of a new High Fire-Threat District (HFTD) where utility infrastructure and operations will be subject to stricter fire‑safety regulations. Importantly, the CPUC Fire-Threat Map (1) incorporates the fire hazards associated with historical powerline wildfires besides the October 2007 fires in Southern California (e.g., the Butte Fire that burned 71,000 acres in Amador and Calaveras Counties in September 2015), and (2) ranks fire-threat areas based on the risks that utility-associated wildfires pose to people and property. Primary responsibility for the development of the CPUC Fire-Threat Map was delegated to a group of utility mapping experts known as the Peer Development Panel (PDP), with oversight from a team of independent experts known as the Independent Review Team (IRT). The members of the IRT were selected by CAL FIRE and CAL FIRE served as the Chair of the IRT. The development of CPUC Fire-Threat Map includes input from many stakeholders, including investor-owned and publicly owned electric utilities, communications infrastructure providers, public interest groups, and local public safety agencies. The PDP served a draft statewide CPUC Fire-Threat Map on July 31, 2017, which was subsequently reviewed by the IRT. On October 2 and October 5, 2017, the PDP filed an Initial CPUC Fire-Threat Map that reflected the results of the IRT's review through September 25, 2017. The [final IRT-approved CPUC Fire-Threat Map] was filed on November 17, 2017. On November 21, 2017, SED filed on behalf of the IRT a [summary report detailing the production of the CPUC Fire-Threat Map](referenced at the time as Fire Map 2). Interested parties were provided opportunity to submit alternate maps, written comments on the IRT-approved map and alternate maps (if any), and motions for Evidentiary Hearings. No motions for Evidentiary Hearings or alternate map proposals were received. As such, on January 19, 2018 the CPUC adopted, via Safety and Enforcement Division's [(SED) disposition of a Tier 1 Advice Letter], the final CPUC Fire-Threat Map. Additional information can be found [here].
Plume Height (MISR) on 8/24/20 for the California Fires 2020

Date of Image: 8/24/2020 Date of Next Image: Unknown Summary: The Multi-angle Imaging SpectroRadiometer (MISR) team at NASA's Jet Propulsion Laboratory and the California Institute of Technology in Pasadena, California, provided this map of wildfire smoke plume heights for several wildfires in California, derived from data acquired by the MISR instrument, on board the NASA Terra satellite, on August 24, 2020. MISR carries nine fixed cameras, each of which views a scene from different angles over a period of about seven minutes. After accounting for true motion of the clouds due to wind, the angular parallax of the clouds between different views is used to derive the height of the smoke plumes. Suggested Use: These data contain plume height information for the CZU Lightning Complex, LNU Lightning Complex, and SCU Lightning Complex Fires as observed by MISR at approximately 12:10 pm local time on August 24, 2020. Plume height gives an indication of fire intensity and indicates whether the smoke is impacting air quality at ground-level. Observations of plume height are also important as an input to air quality models that predict where the smoke will go, and who it might affect downwind. The MISR plume heights in this map were produced using the MISR Interactive eXplorer (MINX) software. Satellite/Sensor: Terra/Multi-angle Imaging SpectroRadiometer Resolution: 1.1 kilometers horizontal resolution Credits: These data were captured during Terra orbit 110026. The smoke plume height calculation was performed using the MISR INteractive eXplorer (MINX) software tool, which is publicly available at [https://github.com/nasa/MINX]. MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, California, for NASA's Science Mission Directorate, Washington, D.C. The Terra spacecraft is managed by NASA's Goddard Space Flight Center, Greenbelt, Maryland. The MISR data were obtained from the NASA Langley Research Center Atmospheric Science Data Center, Hampton, Virginia. JPL is a division of the California Institute of Technology in Pasadena.
Exaggerated (5x) Plume Height (MISR) on 8/24/20 for the California Fires 2020

Date of Image: 8/24/2020 Date of Next Image: Unknown Summary: The Multi-angle Imaging SpectroRadiometer (MISR) team at NASA's Jet Propulsion Laboratory and the California Institute of Technology in Pasadena, California, provided this map of wildfire smoke plume heights for several wildfires in California, derived from data acquired by the MISR instrument, on board the NASA Terra satellite, on August 24, 2020. MISR carries nine fixed cameras, each of which views a scene from different angles over a period of about seven minutes. After accounting for true motion of the clouds due to wind, the angular parallax of the clouds between different views is used to derive the height of the smoke plumes. Suggested Use: These data contain plume height information for the CZU Lightning Complex, LNU Lightning Complex, and SCU Lightning Complex Fires as observed by MISR at approximately 12:10 pm local time on August 24, 2020. Plume height gives an indication of fire intensity and indicates whether the smoke is impacting air quality at ground-level. Observations of plume height are also important as an input to air quality models that predict where the smoke will go, and who it might affect downwind. The MISR plume heights in this map were produced using the MISR Interactive eXplorer (MINX) software. The plume point heights are exaggerated 5x to better show structure of the plumes. True height values are available in the attributes of each point. Satellite/Sensor: Terra/Multi-angle Imaging SpectroRadiometer Resolution: 1.1 kilometers horizontal resolution Credits: These data were captured during Terra orbit 110026. The smoke plume height calculation was performed using the MISR INteractive eXplorer (MINX) software tool, which is publicly available at [https://github.com/nasa/MINX]. MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, California, for NASA's Science Mission Directorate, Washington, D.C. The Terra spacecraft is managed by NASA's Goddard Space Flight Center, Greenbelt, Maryland. The MISR data were obtained from the NASA Langley Research Center Atmospheric Science Data Center, Hampton, Virginia. JPL is a division of the California Institute of Technology in Pasadena.
2020 Hurricane Hazus Modeled Damages

HAZUS wind loss estimates are presented for the 2020 Hurricane season, including Hurricane Delta, Hurricane Sally, Hurricane Laura and Hurricane Isaias. Results show modeled wind loss estimates based on predicted wind speed probabilities from NHC Advisorys. (see [NOAA NHC] for more information). The assessment considers only wind speeds greater than 50 mph. For more information about the Hazus program, please visit the [Hazus home page].
Puerto Rico Hospitals Impacted _ Maria 2017

This feature class/shapefile contains locations of Hospitals for 50 US states, Washington D.C., US territories of Puerto Rico, Guam, American Samoa, Northern Mariana Islands, Palau, and Virgin Islands. The dataset only includes hospital facilities based on data acquired from various state departments or federal sources which has been referenced in the SOURCE field. Hospital facilities which do not occur in these sources will be not present in the database. The source data was available in a variety of formats (pdfs, tables, webpages, etc.) which was cleaned and geocoded and then converted into a spatial database. The database does not contain nursing homes or health centers. Hospitals have been categorized into children, chronic disease, critical access, general acute care, long term care, military, psychiatric, rehabilitation, special, and women based on the range of the available values from the various sources after removing similarities. In this update 123 additional hospitals were added and 26 additional helipads were identified.
OpenStreetMap Buildings for North America

This feature layer provides access to OpenStreetMap (OSM) buildings data for North America, which is updated every 1 minute with the latest edits. This [hosted feature layer view] is referencing a hosted feature layer of OSM polygon (closed way) data in ArcGIS Online that is updated with minutely diffs from the OSM planet file. This feature layer view includes building features defined as a query against the hosted feature layer (i.e. building is not blank). In OSM, a building is a man-made structure with a roof, standing more or less permanently in one place. These features are identified with a [building tag]. There are thousands of different tag values for building used in the OSM database. In this feature layer, unique symbols are used for several of the most popular building types, while lesser used types are grouped in an "other" category. Zoom in to large scales (e.g. Streets level or 1:10k scale) to see the building features display. You can click on a feature to get the name of the building (if available). The name of the building will display by default at large scales (e.g. Street level of 1:5k scale). Labels can be turned off in your map if you prefer. Create New Layer If you would like to create a more focused version of this buildings layer displaying just one or two building types, you can do that easily! Just add the layer to a map, copy the layer in the content window, add a filter to the new layer (e.g. building is apartments), rename the layer as appropriate, and save layer. You can also change the layer symbols or popup if you like. Esri may publish a few such layers (e.g. parks) that are ready to use, but not for every type of building. Important Note: if you do create a new layer, it should be provided under the same Terms of Use and include the same Credits as this layer. You can copy and paste the Terms of Use and Credits info below in the new Item page as needed.
Active Fire Extents

Web service updating every 6 hours with the latest active fire perimeter from GeoMAC. Enriched with CoreLogic residential parcel counts and census demographics. Parcel data is processed before aggregation up to the active fire extents in order to best represent structure count using the following steps: * Residential parcels only (no commercial, agricultural, vacant, industrial parcels) * Water mask to remove parcels within open water (lakes, oceans, rivers) * Duplicate APN’s (Assessor’s Parcel Number) are removed. Sometimes there can be duplicate parcels over a single lot or structure with the same APN number, which skews the exposure count if not taken into account in processing. Data Sources [GeoMAC] [GeoMAC Wildfire Active Perimeters] CoreLogic National Parcel Dataset Access & Use Information Public: This dataset is intended for public access and use. Downloads & Resources [Map Service] [Feature Service]
Hurricane Frequency Hexbins

This feature service layer is a component of the Storm Surge Inundation Map application. Please [launch the main application] using this link: [https://www.epa.gov/crwu/coastal-storm-surge-scenarios-water-utilities]. This layer contains the total number of storm landfalls (strikes) and average return period for each category of hurricane, for each U.S. coastal county. The Storm Surge Inundation Map application presents a series of maps of projected storm variables as part of the EPA’s Creating Resilient Water Utilities (CRWU) initiative to illustrate Coastal Storm Surge Scenarios for water utilities. Point of contact: Steve Fries (fries.steve@epa.gov), EPA’s Creating Resilient Water Utilities
County_Hurr_Risk

The hurricane risk index is simply the product of the cumulative hurricane strikes per coastal county and the CDC Overall Social Vulnerability Index (SVI) for the given county. We normalize the hurricane strikes data to match the SVI data classification scheme (i.e., max value at 1); however, using the raw or normalized values of hurricane strikes has no impact on the spatial pattern of the risk index. Therefore, a risk index of value 1 indicates the county has the highest hurricane strikes of all the counties and is the most vulnerable county in the nation according to the SVI index. Because the analysis is over multiple states, we use the ‘United States’ SVI dataset at the county level. Values of the index are unevenly distributed so we classify intervals using the Jenks method and the first break at 0.08 is roughly equal to the median index value. For counties north of North Carolina, the low hurricane risk is most dependent on the low number of hurricane strikes. The vast majority of the counties fall in the lowest risk category and any in the second lowest category are there because of high social vulnerability.
Feeding_America_Food_Banks_View1

NOTE: Due to resource constraints, Team Rubicon is no longer updating operational status of Food Banks. The [Feeding America nationwide network of food banks] secures and distributes 4.3 billion meals each year through food pantries and meal programs throughout the United States and leads the nation to engage in the fight against hunger. What is a food bank? A food bank is a non-profit organization that collects and distributes food to hunger-relief charities. Food banks act as food storage and distribution depots for smaller front line agencies; and usually do not themselves give out food directly to people struggling with hunger. Food banks in the U.S. are very diverse – from small operations serving people spread out across large rural areas to very large facilities that store and distribute many millions of pounds of food each year, and everything in between. A variety of factors impact how food banks work, from the size of the facility to the number of staff members. But, one thing all food banks have in common is that they rely on donors and volunteers to carry out their day-to-day operations. Data Source: [https://www.feedingamerica.org/find-your-local-foodbank]
Weather Warnings (Fire related, National Weather Service)

This is a saved copy of the NWS Weather Watches and Warning layer, filtered just for wildfire related warnings. Details from the orginal item:[https://www.arcgis.com/home/item.html?id=a6134ae01aad44c499d12feec782b386] This 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. Source * National Weather Service RSS-CAP Warnings and Advisories: [Public Alerts] * National Weather Service Boundary Overlays: [AWIPS Shapefile Database] Update Frequency * The 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 Covered * United States and Territories What 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.
Wildfire Hazard Potential

The [wildland fire potential layer] provides information on the relative potential for wildfire that would be difficult for fire crews to contain. Areas with higher wildland fire potential values represent fuels with a higher likelihood of experiencing high-intensity fire with torching, crowning, and other forms of extreme fire behavior. Dataset Summary This layer provides access to a 270m cell size raster derived from the Large Fire Simulation System (LFSim) produced as part of the Fire Program Analysis System by the USDA Forest Service’s [Fire Modeling Institute]. The data covers the contiguous U.S. The layer is useful for analyses of wildfire risk, hazardous fuels prioritization and strategic planning across large landscapes (hundreds of square miles) up through regional and national scales. When paired with spatial data depicting highly valued resources, land managers can use these data to create value-specific risk maps. Examples of published research using these data include: * [Integrated national-scale assessment of wildfire risk to human and ecological values] * [A simulation of probabilistic wildfire risk components for the continental United States] This layer is derived from the [USA Wildland Fire Potential] service produced by the US Forest Service.
Open Pharmacies - Rx Open

[Rx Open] helps patients find nearby open pharmacies in areas impacted by disaster. Combining multiple data feeds from the pharmaceutical industry, Rx Open displays the precise location of open pharmacies, closed pharmacies, and those whose status is unknown. This critical information assists government officials in assessing an emergency's impact on public health in a disaster area. Healthcare Ready provides Rx Open to the public at no cost during a disaster through the generous support of our [leadership] and from the NCPDP Foundation, who provides grant support and the dataQ® pharmacy data file. To enroll your pharmacy email [ContactUs@HealthcareReady.org]. Participation in Rx Open is free. If the status of your pharmacy is not consistent with what is shown on the Rx Open maps, please contact us at [ContactUs@HealthcareReady.org].
Landslide Risk

This dataset depicts low, medium, and high landslide hazard zones for the island of Tutuila, American Samoa. The data was digitized from a mosaic of scanned paper maps produced in conjunction with a Landslide Mitigation Study for Tutuila Island by the U.S. Department of Agriculture/Soil Conservation Service (USDA/SCS) for the American Samoa Coastal Management Program on October 30, 1990.
Major Earthquakes

Most intense, most fatal and most damaging global earthquakes from 2150 BCE to present. This layer represents earthquakes with at least one of the following criteria: * Magnitude 8.5 or greater * Modified Mercalli Intensity XI or XII * 1,001 or more fatalities * $25 million or more in damage Data source: National Geophysical Data Center / World Data Service (NGDC/WDS): [Significant Earthquake Database]. National Geophysical Data Center, NOAA. [doi:10.7289/V5TD9V7K]