33 datasets found
  1. BioA Management Recommendations Story Map Webmap

    • usfs.hub.arcgis.com
    Updated Jul 28, 2020
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    U.S. Forest Service (2020). BioA Management Recommendations Story Map Webmap [Dataset]. https://usfs.hub.arcgis.com/maps/373d8b89a6514ba5af3f65d6715f0d1d
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    Dataset updated
    Jul 28, 2020
    Dataset provided by
    U.S. Department of Agriculture Forest Servicehttp://fs.fed.us/
    Authors
    U.S. Forest Service
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    The layers present in this web map represent a subset of the maps found in the original chapter 2 of the USDA Forest Service Bioregional Assessment of Northwest Forests. Data layers from the following maps are present:Restoration need map found on page 33 of the original documentFigure 2-6: BioA forests rated by urgency to address a lack of resiliency (page 39)Figure 2-7: Northern Spotted Owl range and critical habitat (page 39)

  2. m

    MassGIS Data: MassDEP Water Utility Resilience Program Mapping Project

    • mass.gov
    Updated Mar 15, 2025
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    MassGIS (Bureau of Geographic Information) (2025). MassGIS Data: MassDEP Water Utility Resilience Program Mapping Project [Dataset]. https://www.mass.gov/info-details/massgis-data-massdep-water-utility-resilience-program-mapping-project
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    Dataset updated
    Mar 15, 2025
    Dataset authored and provided by
    MassGIS (Bureau of Geographic Information)
    Area covered
    Massachusetts
    Description

    March 2025

  3. a

    Climate Mapping For Resilience and Adaptation Assessment Tool

    • keep-cool-global-community.hub.arcgis.com
    Updated Jan 23, 2024
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    National Climate Resilience (2024). Climate Mapping For Resilience and Adaptation Assessment Tool [Dataset]. https://keep-cool-global-community.hub.arcgis.com/items/ca0d59f9645149e5bfe85f68e1cfed27
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    Dataset updated
    Jan 23, 2024
    Dataset authored and provided by
    National Climate Resilience
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The CMRA Portal provides resources for multiple types of users, whether you're a local resilience planner, a program analyst, or just interested in climate impacts in the United States. At the heart of CMRA is the Assessment Tool - an interactive application that provides statistics, maps, and reports that can help people document their climate exposure, now and in the future.CMRA also offers links to federal funding sources, a rich collection of open data, and other applications for visualizing information. The information on this page is intended to orient you to how these different resources can be used most effectively. Watch a tutorial video on how to use CMRA and the Assessment tool.

  4. d

    Resilience Indicator Summaries and Resilience Scores CNMI Excel database

    • datadiscoverystudio.org
    Updated Jan 1, 2012
    + more versions
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    USGS - Pacific Islands Climate Science Center (2012). Resilience Indicator Summaries and Resilience Scores CNMI Excel database [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/c6e2bca8c5d04b9bbb9c5ae4fb5921a2/html
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    Dataset updated
    Jan 1, 2012
    Dataset provided by
    USGS - Pacific Islands Climate Science Center
    Area covered
    Description

    Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

  5. c

    Relative Sea Level Rise in the Chesapeake Bay

    • data.chesapeakebay.net
    • gsat-chesbay.hub.arcgis.com
    • +1more
    Updated Feb 17, 2020
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    Chesapeake Geoplatform (2020). Relative Sea Level Rise in the Chesapeake Bay [Dataset]. https://data.chesapeakebay.net/datasets/relative-sea-level-rise-in-the-chesapeake-bay/explore
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    Dataset updated
    Feb 17, 2020
    Dataset authored and provided by
    Chesapeake Geoplatform
    Area covered
    Description

    This data resource is a layer in a map service. To download it, please go to the "Layers" section of this page and click the name of the dataset. This will open a new page that features a download button. Open the Map Service: https://gis.chesapeakebay.net/ags/rest/services/ChesapeakeProgress/cpClimate_SeaLevel/MapServer This Chesapeake Bay Program indicator of progress toward the Climate Monitoring and Assessment Outcome shows change in relative sea level at seven long-term tide gauge stations on the Chesapeake Bay and its tributaries.

  6. H

    Extracted Data From: Climate Resilience Evaluation and Awareness Tool

    • dataverse.harvard.edu
    Updated Feb 19, 2025
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    Environmental Protection Agency (2025). Extracted Data From: Climate Resilience Evaluation and Awareness Tool [Dataset]. http://doi.org/10.7910/DVN/Z7J2EA
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Harvard Dataverse
    Authors
    Environmental Protection Agency
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2035
    Description

    This submission includes publicly available data extracted in its original form. Please reference the Related Publication listed here for source and citation information If you have questions about the source data, please contact the EPA Creating Resilient Water Utilities (CRWU) (CRWUhelp@epa.gov). If you have questions about metadata, please contact CAFE (climatecafe@bu.edu) "EPA's Creating Resilient Water Utilities (CRWU) initiative provides drinking water, wastewater, and stormwater (water sector) utilities with practical tools, training, and technical assistance needed to increase resilience to climate change. CRWU’s Climate Resilience Evaluation and Awareness Tool (CREAT) and interactive maps (Storm Surge Inundation Map, CREAT Climate Scenarios Projection Map, and the Streamflow Projections Map), provide utilities with pre-processed data to aid in climate-based decision-making. To increase accessibility for geospatial users, CRWU provided these datasets in a zipped file geodatabase format. The data provided here are projected changes in climate conditions. These data and additional projections associated with the same scenarios are available in CREAT. The scenarios used to present the range of model projections for each grid cell on the map were: 'Hot/Dry' scenario based on the average of the five climate models that project hotter and drier conditions compared to the other model projections; ‘Central’ scenario based on the average of the five climate models that project changes in the middle of the distribution of projections; and 'Warm/Wet’ scenario based on the average of the five climate models that project less warming but increased precipitation relative to other models. Changes in annual temperature, annual precipitation, and 100-year storm intensity are provided as increases (positive values) or decreases (negative values) relative to a baseline of observed climate at the same location from 1981-2010. Each projection includes changes in temperature and precipitation averaged over two 20-year time periods: '2035 period' from 2026-2045 and '2060 period' from 2051-2070. The number of hot days associated with each climate station are reported as the number of days per year that have temperatures over 100 °F following the temperature increases projected by the same models. Climate station data were built upon the dataset of the Global Historical Climatology Network (GHCN)-Daily. The dataset is being maintained at the National Oceanic and Atmospheric Administration’s National Climatic Data Centre (NCDC). Additional information on the selection of scenarios and the sources of data used can be found in the CREAT 3.1 Methodology Guide. Models used were drawn from the Coupled Model Intercomparison Project Phase 5 (CMIP5) dataset. To explore data for a location or to download data from this map, please visit the CRWU Data Access page." [Quote from: https://epa.maps.arcgis.com/apps/MapSeries/index.html?appid=3805293158d54846a29f750d63c6890e]

  7. National Weather Service Precipitation Forecast

    • resilience-fema.hub.arcgis.com
    • disasterpartners.org
    • +18more
    Updated Aug 16, 2022
    + more versions
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    Esri (2022). National Weather Service Precipitation Forecast [Dataset]. https://resilience-fema.hub.arcgis.com/datasets/esri2::national-weather-service-precipitation-forecast
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map displays the Quantitative Precipitation Forecast (QPF) for the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative precipitation data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the "Amount by Time" (incremental) layer or the "Accumulation by Time" (cumulative) layer to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.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).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.qpf.binWhere 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.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!

  8. c

    Drought and Moisture Surplus for the Conterminous United States, Annual Data...

    • resilience.climate.gov
    • colorado-river-portal.usgs.gov
    • +12more
    Updated Oct 17, 2019
    + more versions
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    U.S. Forest Service (2019). Drought and Moisture Surplus for the Conterminous United States, Annual Data 1-Year Windows (Image Service) [Dataset]. https://resilience.climate.gov/datasets/209708ebfc0c45baa21a70b503d6fb7f
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    Dataset updated
    Oct 17, 2019
    Dataset authored and provided by
    U.S. Forest Service
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Description

    Note: To download this raster dataset, go to ArcGIS Open Data Set and click the download button, and under additional resources select raster download option; the data can also be downloaded directly from the FSGeodata Clearinghouse. To summarize this dataset by U.S. Forest Service Lands, see the Drought Summary Tool. You can also explore cumulative drought and moisture changes from this StoryMap; additional drought products from the Office of Sustainability and Climate are available in our Climate Gallery and the OSC Drought page.The Moisture Deficit and Surplus map uses moisture difference z-score datasets developed by scientists Frank Koch, John Coulston, and William Smith of the Forest Service Southern Research Station. A z-score is a statistical method for assessing how different a value is from the mean (average). Mean moisture values were derived from historical data on precipitation and potential evapotranspiration, from 1900 to 2023. The greater the z-value, the larger the departure from average conditions, indicating larger moisture deficits or surpluses. Thus, the dark red areas on this map indicate a one-year period with extremely dry conditions, relative to the average conditions over the past century. For further reading on the methodology used to build these maps, see the publication here: https://www.fs.usda.gov/treesearch/pubs/43361

  9. a

    Total Score Quantile

    • noaa.hub.arcgis.com
    Updated Oct 4, 2021
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    NOAA GeoPlatform (2021). Total Score Quantile [Dataset]. https://noaa.hub.arcgis.com/maps/64d9b63a6122491eaecfb80dab9ec996
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    Dataset updated
    Oct 4, 2021
    Dataset authored and provided by
    NOAA GeoPlatform
    Area covered
    Description

    This web map was created to support the Salt Marsh Resilience to Sea Level Rise app. The map highlights the overall resilience score. Resilience scores range from 1 (red) for least resilient to 10 (green) for most resilient.Links to data resources: data page, metadata, map service.

  10. a

    National Weather Service Smoke Forecast

    • resilience-fema.hub.arcgis.com
    • disasterpartners.org
    • +17more
    Updated Aug 16, 2022
    + more versions
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    Esri (2022). National Weather Service Smoke Forecast [Dataset]. https://resilience-fema.hub.arcgis.com/datasets/a98fd08751a5480c898b7cebe38807f4
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esri
    Area covered
    Description

    This map displays projected visible surface smoke across the contiguous United States for the next 48 hours in 1 hour increments. It is updated every 24 hours by NWS. Concentrations are reported in micrograms per cubic meter.Where is the data coming from?The National Digital Guidance Database (NDGD) is a sister to the National Digital Forecast Database (NDFD). Information in NDGD may be used by NWS forecasters as guidance in preparing official NWS forecasts in NDFD. The experimental/guidance NDGD data is not an official NWS forecast product.Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndgd/GT.aq/AR.conus/ds.smokes01.binSource data archive can be found here: https://www.ncei.noaa.gov/products/weather-climate-models/national-digital-guidance-database look for 'LXQ...' files by date. These are the Binary GRIB2 files that can be decoded via DeGRIB tool.Where can I find other NDGD 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.RevisionsJuly 11, 2022: Feed updated to leverage forecast model change by NOAA, whereby the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) forecast model system was replaced with the Rapid Refresh (RAP) forecast model system. Key differences: higher accuracy with RAP now concentrated at 0-8 meter detail vs HYSPLIT at 0-100 meter; earlier data delivery by 6 hrs; forecast output extended to 51 hrs.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!

  11. Recent Hurricanes, Cyclones and Typhoons

    • resilience-fema.hub.arcgis.com
    • climate.esri.ca
    • +27more
    Updated Jun 11, 2019
    + more versions
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    Esri (2019). Recent Hurricanes, Cyclones and Typhoons [Dataset]. https://resilience-fema.hub.arcgis.com/datasets/esri2::recent-hurricanes-cyclones-and-typhoons
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    Dataset updated
    Jun 11, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Earth
    Description

    This layer features tropical storm (hurricanes, typhoons, cyclones) tracks, positions, and observed wind swaths from the past hurricane season for the Atlantic, Pacific, and Indian Basins. These are products from the National Hurricane Center (NHC) and Joint Typhoon Warning Center (JTWC). They are part of an archive of tropical storm data maintained in the International Best Track Archive for Climate Stewardship (IBTrACS) database by the NOAA National Centers for Environmental Information.Data SourceNOAA National Hurricane Center tropical cyclone best track archive.Update FrequencyWe automatically check these products for updates every 15 minutes from the NHC GIS Data page.The NHC shapefiles are parsed using the Aggregated Live Feeds methodology to take the returned information and serve the data through ArcGIS Server as a map service.Area CoveredWorldWhat can you do with this layer?Customize the display of each attribute by using the ‘Change Style’ option for any layer.Run a filter to query the layer and display only specific types of storms or areas.Add to your map with other weather data layers to provide insight on hazardous weather events.Use ArcGIS Online analysis tools like ‘Enrich Data’ on the Observed Wind Swath layer to determine the impact of cyclone events on populations.Visualize data in ArcGIS Insights or Operations Dashboards.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. Always refer to NOAA or JTWC sources 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!

  12. National Weather Service 3-Day Min/Max Temperature Forecast

    • resilience.climate.gov
    • heat.gov
    • +6more
    Updated Aug 16, 2022
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    Esri (2022). National Weather Service 3-Day Min/Max Temperature Forecast [Dataset]. https://resilience.climate.gov/maps/0ae7cf18df0a4b4d9e7eea665f00500d
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map displays the minimum and maximum air temperature forecast over the next 3 days across the Contiguous United States, Alaska, Guam, Hawaii, and Puerto Rico in daily increments. Minimum temperatures are typically at night, while maximum temperatures are typically afternoon. The original raster data has been processed into 1-degree contours and both Layers include a Time Series set to a 24-hour time interval.The minimum and maximum temperatures are the forecasted ambient air temperature in °F.See sister data product for Apparent and Expected Hourly TemperaturesRevisionsApr 21, 2022: Added Forecast Period Number 'Interval' field for an alternate query method to the Timeline of data.Apr 22, 2022: Set 'Min Temperature' layer visibility to False by default, so only Max temperature is visible when initially viewed.Sep 1, 2022: Updated renderer Arcade logic on layers to correctly symbolize on values greater than 120 and less than -60 degrees.DetailService Data update interval is: HourlyWhere 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).Overnight Minimum Temperature Source:CONUS: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.mint.binALASKA: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.alaska/VP.001-003/ds.mint.binHAWAII: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.hawaii/VP.001-003/ds.mint.binGUAM: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.guam/VP.001-003/ds.mint.binPUERTO RICO: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.puertori/VP.001-003/ds.mint.binDaytime Maximum Temperature Source:CONUS: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.maxt.binALASKA: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.alaska/VP.001-003/ds.maxt.binHAWAII: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.hawaii/VP.001-003/ds.maxt.binGUAM: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.guam/VP.001-003/ds.maxt.binPUERTO RICO: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.puertori/VP.001-003/ds.maxt.binWhere 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 feature 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.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.

  13. ACS Internet Access by Age and Race Variables - Boundaries

    • resilience.climate.gov
    • coronavirus-resources.esri.com
    • +6more
    Updated Dec 7, 2018
    + more versions
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    Esri (2018). ACS Internet Access by Age and Race Variables - Boundaries [Dataset]. https://resilience.climate.gov/maps/5a1b51d3c6374c3cbb7c9ff7acdba16b
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    Dataset updated
    Dec 7, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows computer ownership and internet access by age and race. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent of population age 18 to 64 in households with no computer. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B28005, B28003, B28009B, B28009C, B28009D, B28009E, B28009F, B28009G, B28009H, B28009I Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  14. a

    Rate of vegetation and mineralization of surfaces

    • catalogue.arctic-sdi.org
    • open.canada.ca
    • +1more
    Updated Jun 8, 2022
    + more versions
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    (2022). Rate of vegetation and mineralization of surfaces [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/search?keyword=Resilience
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    Dataset updated
    Jun 8, 2022
    Description

    Rate of mineralization and vegetation of surfaces in the territory of the agglomeration of Montreal represented by polygons and based on the data Mineral and vegetable surfaces of 2016 from the Geomatics Division of the City of Montreal. The data was calculated at the district level and at the level of the distribution islands of Statistics Canada. The data can also be consulted on the interactive climate change vulnerability map.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

  15. USA Current Wildfires

    • resilience.climate.gov
    • atlas.eia.gov
    • +18more
    Updated Aug 16, 2022
    + more versions
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    Esri (2022). USA Current Wildfires [Dataset]. https://resilience.climate.gov/maps/d957997ccee7408287a963600a77f61f
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer presents the best-known point and perimeter locations of wildfire occurrences within the United States over the past 7 days. Points mark a location within the wildfire area and provide current information about that wildfire. Perimeters are the line surrounding land that has been impacted by a wildfire.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-cacheable 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 cacheable.Source:  Wildfire points are sourced from Integrated Reporting of Wildland-Fire Information (IRWIN) and perimeters from National Interagency Fire Center (NIFC). Current Incidents: This layer provides a near real-time view of the data being shared through the Integrated Reporting of Wildland-Fire Information (IRWIN) service. IRWIN provides data exchange capabilities between participating wildfire systems, including federal, state and local agencies. Data is synchronized across participating organizations to make sure the most current information is available. The display of the points are based on the NWCG Fire Size Classification applied to the daily acres attribute.Current Perimeters: This layer displays fire perimeters posted to the National Incident Feature Service. It is updated from operational data and may not reflect current conditions on the ground. For a better understanding of the workflows involved in mapping and sharing fire perimeter data, see the National Wildfire Coordinating Group Standards for Geospatial Operations.Update Frequency:  Every 15 minutes using the Aggregated Live Feed Methodology based on the following filters:Events modified in the last 7 daysEvents that are not given a Fire Out DateIncident Type Kind: FiresIncident Type Category: Prescribed Fire, Wildfire, and Incident Complex

    Area Covered: United StatesWhat can I do with this layer? The data includes basic wildfire information, such as location, size, environmental conditions, and resource summaries. Features can be filtered by incident name, size, or date keeping in mind that not all perimeters are fully attributed.Attribute InformationThis is a list of attributes that benefit from additional explanation. Not all attributes are listed.Incident Type Category: This is a breakdown of events into more specific categories.Wildfire (WF) -A wildland fire originating from an unplanned ignition, such as lightning, volcanos, unauthorized and accidental human caused fires, and prescribed fires that are declared wildfires.Prescribed Fire (RX) - A wildland fire originating from a planned ignition in accordance with applicable laws, policies, and regulations to meet specific objectives.Incident Complex (CX) - An incident complex is two or more individual incidents in the same general proximity that are managed together under one Incident Management Team. This allows resources to be used across the complex rather than on individual incidents uniting operational activities.IrwinID: Unique identifier assigned to each incident record in both point and perimeter layers.

    Acres: these typically refer to the number of acres within the current perimeter of a specific, individual incident, including unburned and unburnable islands.Discovery: An estimate of acres burning upon the discovery of the fire.Calculated or GIS:  A measure of acres calculated (i.e., infrared) from a geospatial perimeter of a fire.Daily: A measure of acres reported for a fire.Final: The measure of acres within the final perimeter of a fire. More specifically, the number of acres within the final fire perimeter of a specific, individual incident, including unburned and unburnable islands.

    Dates: the various systems contribute date information differently so not all fields will be populated for every fire.FireDiscovery: The date and time a fire was reported as discovered or confirmed to exist. May also be the start date for reporting purposes.

    Containment: The date and time a wildfire was declared contained. Control: The date and time a wildfire was declared under control.ICS209Report: The date and time of the latest approved ICS-209 report.Current: The date and time a perimeter is last known to be updated.FireOut: The date and time when a fire is declared out.ModifiedOnAge: (Integer) Computed days since event last modified.DiscoveryAge: (Integer) Computed days since event's fire discovery date.CurrentDateAge: (Integer) Computed days since perimeter last modified.CreateDateAge: (Integer) Computed days since perimeter entry created.

    GACC: A code that identifies one of the wildland fire geographic area coordination centers. A geographic area coordination center is a facility that is used for the coordination of agency or jurisdictional resources in support of one or more incidents within a geographic coordination area.Fire Mgmt Complexity: The highest management level utilized to manage a wildland fire event.Incident Management Organization: The incident management organization for the incident, which may be a Type 1, 2, or 3 Incident Management Team (IMT), a Unified Command, a Unified Command with an IMT, National Incident Management Organization (NIMO), etc. This field is null if no team is assigned.Unique Fire Identifier: Unique identifier assigned to each wildland fire. yyyy = calendar year, SSUUUU = Point Of Origin (POO) protecting unit identifier (5 or 6 characters), xxxxxx = local incident identifier (6 to 10 characters)RevisionsJan 4, 2021: Added Integer fields 'Days Since...' to Current_Incidents point layer and Current_Perimeters polygon layer. These fields are computed when the data is updated, reflecting the current number of days since each record was last updated. This will aid in making 'age' related, cache friendly queries.Mar 12, 2021: Added second set of 'Age' fields for Event and Perimeter record creation, reflecting age in Days since service data update.Apr 21, 2021: Current_Perimeters polygon layer is now being populated by NIFC's newest data source. A new field was added, 'IncidentTypeCategory' to better distinguish Incident types for Perimeters and now includes type 'CX' or Complex Fires. Five fields were not transferrable, and as a result 'Comments', 'Label', 'ComplexName', 'ComplexID', and 'IMTName' fields will be Null moving forward.Apr 26, 2021: Updated Incident Layer Symbology to better clarify events, reduce download size and overhead of symbols. Updated Perimeter Layer Symbology to better distingish between Wildfires and Prescribed Fires.May 5, 2021: Slight modification to Arcade logic for Symbology, refining Age comparison to Zero for fires in past 24-hours.Aug 16, 2021: Enabled Time Series capability on Layers (off by default) using 'Fire Discovery Date' for Incidents and 'Creation Date' for Perimeters.This layer 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!

  16. ACS Race and Hispanic Origin Variables - Boundaries

    • resilience.climate.gov
    • visionzero.geohub.lacity.org
    • +9more
    Updated Oct 22, 2018
    + more versions
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    Esri (2018). ACS Race and Hispanic Origin Variables - Boundaries [Dataset]. https://resilience.climate.gov/maps/23ab8028f1784de4b0810104cd5d1c8f
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    Dataset updated
    Oct 22, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows population broken down by race and Hispanic origin. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the predominant race living within an area. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B03002Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  17. a

    Youth Risk & Resiliency (YRRS) Trends in New Mexico, 2003-2011

    • chi-phi-nmcdc.opendata.arcgis.com
    • hub.arcgis.com
    Updated Feb 17, 2014
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    New Mexico Community Data Collaborative (2014). Youth Risk & Resiliency (YRRS) Trends in New Mexico, 2003-2011 [Dataset]. https://chi-phi-nmcdc.opendata.arcgis.com/datasets/youth-risk-resiliency-yrrs-trends-in-new-mexico-2003-2011
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    Dataset updated
    Feb 17, 2014
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    Description

    This map was updated in 2021. See the archived version of this map with YRRS data from 2003-2011 here: https://nmcdc.maps.arcgis.com/home/item.html?id=e882a9314cd94c0ca88113ba623cd39dData Dictionary available on Feature Layer details page: https://nmcdc.maps.arcgis.com/home/item.html?id=3f2889801e0d4e7bab806b778a19ca5dSource: NM Department of Health, Epidemiology and Response Division, Youth Risk and Resiliency Survey: https://www.youthrisk.org/Questionnaires: https://www.youthrisk.org/surveybooklets/NOTE (May 2016) - older feature service will be deleted when all layers or replaced. New Feature Service - https://nmcdc.maps.arcgis.com/home/item.html?id=db4acb0bef404f14b08a3ba4b9649aea

  18. USA Weather Watches and Warnings

    • resilience-fema.hub.arcgis.com
    • resilience.climate.gov
    • +14more
    Updated Aug 16, 2022
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    Esri (2022). USA Weather Watches and Warnings [Dataset]. https://resilience-fema.hub.arcgis.com/datasets/esri2::usa-weather-watches-and-warnings
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    United States,
    Description

    This feature service depicts the National Weather Service (NWS) watches, warnings, and advisories within the United States. Watches and warnings are classified into well over 100 categories. See event descriptions for full details. 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 DatabaseSample DataSee Sample Layer Item for sample data during Weather inactivity!Update 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.Revisions:Feb 25, 2021: Revised service data upate workflow, improving stability and update interval.Process now checks for data updates every 5 minutes!Mar 3, 2021: Revised data processing to leverage VTEC parameter details to better align Event 'effective' dates with reported dates on Alert pages.Apr 17, 2023: Turned off popups for boundary Layers by default.Feb 1, 2024: Revised to leverage CAP v1.2 source endpoint. Update event link to use alert search.Feb 16, 2024: Revised event link to accomodate change in alert search endpoint.Jan 19, 2025: Added event 'Description' and 'Instructions', updated Pop-up.Jan 22, 2025: Exposed 'Hours Old' fields supporting last 'Updated', 'Effective', and 'Expiration' as +- age values for events.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!

  19. c

    Apparent

    • resilience.climate.gov
    • hub.arcgis.com
    • +3more
    Updated Aug 16, 2022
    + more versions
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    Esri (2022). Apparent [Dataset]. https://resilience.climate.gov/maps/esri2::apparent
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esri
    Area covered
    Description

    This map displays the Apparent and Expected Air Temperature forecast over the next 72 hours across the Contiguous United States, Alaska, Guam, Hawaii, and Puerto Rico in 3 hour increments. The original raster data has been processed into 1-degree contours.Two layers are included: apparent and expected temperature, both include a Time Series set to a 3-hour time interval. The apparent temperature is the perceived (or feels like) temperature derived from either a combination of temperature and wind (wind chill) or temperature and humidity (heat index) for the indicated hour. When the temperature at a particular grid point falls to 50 °F or less, wind chill will be used for that point for the apparent temperature. When the temperature at a grid point rises above 80 °F, the heat index will be used for apparent temperature.
    Between 51 and 80 °F, the apparent temperature will be the ambient air temperature.The expected temperature is the forecasted ambient air temperature in °F.See sister data product for Min and Max Daily TemperaturesRevisionsApr 21, 2022: Added Forecast Period Number 'Interval' field for an alternate query method to the Timeline of data. Disabled Time Series by default to improve initial Map Viewer exprience and added a Filter for 'interval = 1' to display initial forecast time data (current time period).Apr 22, 2022: Set 'Apparent Temperature' layer visibility to True by default, so content is visible when initially viewed.Sep 1, 2022: Updated renderer Arcade logic on layers to correctly symbolize on values greater than 120 and less than -60 degrees.DetailService Data update interval is: HourlyWhere 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).Apparent Temperature Source:CONUS: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.apt.binALASKA: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.alaska/VP.001-003/ds.apt.binHAWAII: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.hawaii/VP.001-003/ds.apt.binGUAM: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.guam/VP.001-003/ds.apt.binPUERTO RICO: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.puertori/VP.001-003/ds.apt.binExpected Temperature Source:CONUS: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.temp.binALASKA: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.alaska/VP.001-003/ds.temp.binHAWAII: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.hawaii/VP.001-003/ds.temp.binGUAM: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.guam/VP.001-003/ds.temp.binPUERTO RICO: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.puertori/VP.001-003/ds.temp.binWhere 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 feature 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 or add a Filter using the 'Forecast Period Number'.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.

  20. a

    Youth Risk & Resiliency Trends, 2003-2011- ARCHIVED VERSION

    • chi-phi-nmcdc.opendata.arcgis.com
    Updated Apr 27, 2022
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    New Mexico Community Data Collaborative (2022). Youth Risk & Resiliency Trends, 2003-2011- ARCHIVED VERSION [Dataset]. https://chi-phi-nmcdc.opendata.arcgis.com/maps/e882a9314cd94c0ca88113ba623cd39d
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    Dataset updated
    Apr 27, 2022
    Dataset authored and provided by
    New Mexico Community Data Collaborative
    Area covered
    Description

    THIS WEBMAP WAS UPDATED IN 2021. THIS IS THE ARCHIVED VERSION. VIEW THE NEW MAP HERE: https://nmcdc.maps.arcgis.com/home/item.html?id=1ccf65320fdd4a36a21d0c846af89d86Data Dictionary available on Feature Layer details page: https://nmcdc.maps.arcgis.com/home/item.html?id=3f2889801e0d4e7bab806b778a19ca5d Source: NM Department of Health, Epidemiology and Response Division, Youth Risk and Resiliency Survey: https://www.youthrisk.org/Questionnaires: https://www.youthrisk.org/surveybooklets/NOTE (May 2016) - older feature service will be deleted when all layers or replaced. New Feature Service - https://nmcdc.maps.arcgis.com/home/item.html?id=db4acb0bef404f14b08a3ba4b9649aea

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U.S. Forest Service (2020). BioA Management Recommendations Story Map Webmap [Dataset]. https://usfs.hub.arcgis.com/maps/373d8b89a6514ba5af3f65d6715f0d1d
Organization logo

BioA Management Recommendations Story Map Webmap

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Dataset updated
Jul 28, 2020
Dataset provided by
U.S. Department of Agriculture Forest Servicehttp://fs.fed.us/
Authors
U.S. Forest Service
License

MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically

Area covered
Description

The layers present in this web map represent a subset of the maps found in the original chapter 2 of the USDA Forest Service Bioregional Assessment of Northwest Forests. Data layers from the following maps are present:Restoration need map found on page 33 of the original documentFigure 2-6: BioA forests rated by urgency to address a lack of resiliency (page 39)Figure 2-7: Northern Spotted Owl range and critical habitat (page 39)

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