The "Map Imager Layer - Administrative Boundaries" is a Map Image Layer of Administrative Boundaries. It has been designed specifically for use in ArcGIS Online (and will not directly work in ArcMap or ArcPro). This data has been modified from the original source data to serve a specific business purpose. This data is for cartographic purposes only.The Administrative Boundaries Data Group contains the following layers: Populated Places (USGS)US Census Urbanized Areas and Urban Clusters (USCB)US Census Minor Civil Divisions (USCB)PLSS Townships (MnDNR, MnGeo)Counties (USCB)American Indian, Alaska Native, Native Hawaiian (AIANNH) Areas (USCB)States (USCB)Countries (MPCA)These datasets have not been optimized for fast display (but rather they maintain their original shape/precision), therefore it is recommend that filtering is used to show only the features of interest. For more information about using filters please see "Work with map layers: Apply Filters": https://doc.arcgis.com/en/arcgis-online/create-maps/apply-filters.htmFor additional information about the Administrative Boundary Dataset please see:United States Census Bureau TIGER/Line Shapefiles and TIGER/Line Files Technical Documentation: https://www.census.gov/programs-surveys/geography/technical-documentation/complete-technical-documentation/tiger-geo-line.htmlUnited States Census Bureau Census Mapping Files: https://www.census.gov/geographies/mapping-files.htmlUnited States Census Bureau TIGER/Line Shapefiles: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html and https://www.census.gov/cgi-bin/geo/shapefiles/index.php

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990-1999 and 2000-2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990-1999 and 2000-2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000-2009 than during 1990-1999; and that inland water levels were generally lower during 2000-2009 than during 1990-1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990-1999. Mean October water levels during 2000-2009 were generally higher than during 1990-1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses. For more information on the NHDPlus dataset see the NHDPlus v2 User Guide.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territories not including Alaska.Geographic Extent: The United States not including Alaska, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaProjection: Web Mercator Auxiliary Sphere Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Source: EPA and USGSUpdate Frequency: There is new new data since this 2019 version, so no updates planned in the futurePublication Date: March 13, 2019Prior to publication, the NHDPlus network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the NHDPlus Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, On or Off Network (flowlines only), Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original NHDPlus dataset. No data values -9999 and -9998 were converted to Null values for many of the flowline fields.What can you do with this layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute. Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map. Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

Click here to open the ArcGIS Online 3D Map Viewer and work through the examples shown belowTo add 3D data to ArcGIS Online you will need a login for an ArcGIS Online account. We would recommend that you use a free schools subscription (full functionality) or the free public account (reduced functionality).Login to ArcGIS OnlineSearch for layers in ArcGIS Online:

Soil map units are the basic geographic unit of the Soil Survey Geographic Database (SSURGO). The SSURGO dataset is a compilation of soils information collected over the last century by the Natural Resources Conservation Service (NRCS). Map units delineate the extent of different soils. Data for each map unit contains descriptions of the soil’s components, productivity, unique properties, and suitability interpretations.Each soil type has a unique combination of physical, chemical, nutrient and moisture properties. Soil type has ramifications for engineering and construction activities, natural hazards such as landslides, agricultural productivity, the distribution of native plant and animal life and hydrologic and other physical processes. Soil types in the context of climate and terrain can be used as a general indicator of engineering constraints, agriculture suitability, biological productivity and the natural distribution of plants and animals. Data from the gSSURGO databasewas used to create this layer. To download ready-to-use project packages of useful soil data derived from the SSURGO dataset, please visit the USA SSURGO Downloader app. Dataset SummaryPhenomenon Mapped: Soils of the United States and associated territoriesGeographic Extent: The 50 United States, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaCoordinate System: Web Mercator Auxiliary SphereVisible Scale: 1:144,000 to 1:1,000Source: USDA Natural Resources Conservation ServiceUpdate Frequency: AnnualPublication Date: December 2024 What can you do with this layer?ArcGIS OnlineFeature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro.Below are just a few of the things you can do with a feature service in Online and Pro.Add this layer to a map in the map viewer. The layer is limited to scales of approximately 1:144,000 or larger but avector tile layercreated from the same data can be used at smaller scales to produce awebmapthat displays across the full scale range. The layer or a map containing it can be used in an application.Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections and apply filters. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Change the layer’s style and filter the data. For example, you could set a filter forFarmland Class= "All areas are prime farmland" to create a map of only prime farmland.Add labels and set their propertiesCustomize the pop-up ArcGIS ProAdd this layer to a 2d or 3d map. The same scale limit as Online applies in ProUse as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of theLiving Atlas of the Worldthat provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics. Data DictionaryAttributesKey fields from nine commonly used SSURGO tables were compiled to create the 173 attribute fields in this layer. Some fields were joined directly to the SSURGO Map Unit polygon feature class while others required summarization and other processing to create a 1:1 relationship between the attributes and polygons prior to joining the tables. Attributes of this layer are listed below in their order of occurrence in the attribute table and are organized by the SSURGO table they originated from and the processing methods used on them. Map Unit Polygon Feature Class Attribute TableThe fields in this table are from the attribute table of the Map Unit polygon feature class which provides the geographic extent of the map units.Area SymbolSpatial VersionMap Unit Symbol Map Unit TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the table using the Map Unit Key field.Map Unit NameMap Unit KindFarmland ClassInterpretive FocusIntensity of MappingIowa Corn Suitability Rating Legend TableThis table has 1:1 relationship with the Map Unit table and was joined using the Legend Key field.Project Scale Survey Area Catalog TableThe fields in this table have a 1:1 relationship with the polygons and were joined to the Map Unit table using the Survey Area Catalog Key and Legend Key fields.Survey Area VersionTabular Version Map Unit Aggregated Attribute TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the Map Unit attribute table using the Map Unit Key field. Slope Gradient - Dominant ComponentSlope Gradient - Weighted AverageBedrock Depth - MinimumWater Table Depth - Annual MinimumWater Table Depth - April to June MinimumFlooding Frequency - Dominant ConditionFlooding Frequency - MaximumPonding Frequency - PresenceAvailable Water Storage 0-25 cm - Weighted AverageAvailable Water Storage 0-50 cm - Weighted AverageAvailable Water Storage 0-100 cm - Weighted AverageAvailable Water Storage 0-150 cm - Weighted AverageDrainage Class - Dominant ConditionDrainage Class - WettestHydrologic Group - Dominant ConditionIrrigated Capability Class - Dominant ConditionIrrigated Capability Class - Proportion of Mapunit with Dominant ConditionNon-Irrigated Capability Class - Dominant ConditionNon-Irrigated Capability Class - Proportion of Mapunit with Dominant ConditionRating for Buildings without Basements - Dominant ConditionRating for Buildings with Basements - Dominant ConditionRating for Buildings with Basements - Least LimitingRating for Buildings with Basements - Most LimitingRating for Septic Tank Absorption Fields - Dominant ConditionRating for Septic Tank Absorption Fields - Least LimitingRating for Septic Tank Absorption Fields - Most LimitingRating for Sewage Lagoons - Dominant ConditionRating for Sewage Lagoons - Dominant ComponentRating for Roads and Streets - Dominant ConditionRating for Sand Source - Dominant ConditionRating for Sand Source - Most ProbableRating for Paths and Trails - Dominant ConditionRating for Paths and Trails - Weighted AverageErosion Hazard of Forest Roads and Trails - Dominant ComponentHydric Classification - PresenceRating for Manure and Food Processing Waste - Weighted Average Component Table – Dominant ComponentMap units have one or more components. To create a 1:1 join component data must be summarized by map unit. For these fields a custom script was used to select the component with the highest value for the Component Percentage Representative Value field (comppct_r). Ties were broken with the Slope Representative Value field (slope_r). Components with lower average slope were selected as dominant. If both soil order and slope were tied, the first value in the table was selected. Component Percentage - Low ValueComponent Percentage - Representative ValueComponent Percentage - High ValueComponent NameComponent KindOther Criteria Used to Identify ComponentsCriteria Used to Identify Components at the Local LevelRunoff ClassSoil loss tolerance factorWind Erodibility IndexWind Erodibility GroupErosion ClassEarth Cover 1Earth Cover 2Hydric ConditionHydric RatingAspect Range - Counter Clockwise LimitAspect - Representative ValueAspect Range - Clockwise LimitGeomorphic DescriptionNon-Irrigated Capability SubclassNon-Irrigated Unit Capability ClassIrrigated Capability SubclassIrrigated Unit Capability ClassConservation Tree Shrub GroupGrain Wildlife HabitatGrass Wildlife HabitatHerbaceous Wildlife HabitatShrub Wildlife HabitatConifer Wildlife HabitatHardwood Wildlife HabitatWetland Wildlife HabitatShallow Water Wildlife HabitatRangeland Wildlife HabitatOpenland Wildlife HabitatWoodland Wildlife HabitatWetland Wildlife HabitatSoil Slip PotentialSusceptibility to Frost HeavingConcrete CorrosionSteel CorrosionTaxonomic ClassTaxonomic OrderTaxonomic SuborderGreat GroupSubgroupParticle SizeParticle Size ModCation Exchange Activity ClassCarbonate ReactionTemperature ClassMoist SubclassSoil Temperature RegimeEdition of Keys to Soil Taxonomy Used to Classify SoilCalifornia Storie IndexComponent Key Component Table – Weighted AverageMap units may have one or more soil components. To create a 1:1 join, data from the Component table must be summarized by map unit. For these fields a custom script was used to calculate an average value for each map unit weighted by the Component Percentage Representative Value field (comppct_r).Slope Gradient - Low ValueSlope Gradient - Representative ValueSlope Gradient - High ValueSlope Length USLE - Low ValueSlope Length USLE - Representative ValueSlope Length USLE - High ValueElevation - Low ValueElevation - Representative ValueElevation - High ValueAlbedo - Low ValueAlbedo - Representative ValueAlbedo - High ValueMean Annual Air Temperature - Low ValueMean Annual Air Temperature - Representative ValueMean Annual Air Temperature - High ValueMean Annual Precipitation - Low ValueMean Annual Precipitation - Representative ValueMean Annual Precipitation - High ValueRelative Effective Annual Precipitation - Low ValueRelative Effective Annual Precipitation - Representative ValueRelative Effective Annual Precipitation - High ValueDays between Last and First Frost - Low ValueDays between Last and First Frost - Representative ValueDays between Last and First Frost - High ValueRange Forage Annual Potential Production - Low ValueRange Forage Annual Potential Production - Representative ValueRange Forage Annual Potential Production - High ValueInitial Subsidence - Low ValueInitial Subsidence - Representative ValueInitial Subsidence -

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We converted the photointerpreted data into a format usable in a geographic information system (GIS) by employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM), Zone 16, using the North American Datum of 1983 (NAD83). Orthorectify: We orthorectified the interpreted overlays by using OrthoMapper, a softcopy photogrammetric software for GIS. One function of OrthoMapper is to create orthorectified imagery from scanned and unrectified imagery (Image Processing Software, Inc., 2002). The software features a method of visual orientation involving a point-and-click operation that uses existing orthorectified horizontal and vertical base maps. Of primary importance to us, OrthoMapper also has the capability to orthorectify the photointerpreted overlays of each photograph based on the reference information provided. Digitize: To produce a polygon vector layer for use in ArcGIS (Environmental Systems Research Institute [ESRI], Redlands, California), we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format by using ArcGIS. In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map-attribute codes (both map-class codes and physiognomic modifier codes) to the polygons and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer. Geodatabase: At this stage, the map layer has only map-attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map-class names, physiognomic definitions, links to NVCS types), we produced a feature-class table, along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature-class layers produced from this project, including vegetation sample plots, accuracy assessment (AA) sites, aerial photo locations, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.

The way to access Layers Quickly.

Quick Layers is an Add-In for ArcMap 10.6+ that allows rapid access to the DNR's Geospatial Data Resource Site (GDRS). The GDRS is a data structure that serves core geospatial dataset and applications for not only DNR, but many state agencies, and supports the Minnesota Geospatial Commons. Data added from Quick Layers is pre-symbolized, helping to standardize visualization and map production. Current version: 1.164

To use Quick Layers with the GDRS, there's no need to download QuickLayers from this location. Instead, download a full copy or a custom subset of the public GDRS (including Quick Layers) using GDRS Manager.

Quick Layers also allows users to save and share their own pre-symbolized layers, thus increasing efficiency and consistency across the enterprise.

Installation:

After using GDRS Manager to create a GDRS, including Quick Layers, add the path to the Quick Layers addin to the list of shared folders:
1. Open ArcMap
2. Customize -> Add-In Manager… -> Options
3. Click add folder, and enter the location of the Quick Layers app. For example, if your GDRS is mapped to the V drive, the path would be V:\gdrs\apps\pub\us_mn_state_dnr\quick_layers
4. After you do this, the Quick Layers toolbar will be available. To add it, go to Customize -> Toolbars and select DNR Quick Layers 10

The link below is only for those who are using Quick Layers without a GDRS. To get the most functionality out of Quick Layers, don't install it separately, but instead download it as part of a GDRS build using GDRS Manager.

This data set contains high-resolution QuickBird imagery and geospatial data for the entire Barrow QuickBird image area (156.15° W - 157.07° W, 71.15° N - 71.41° N) and Barrow B4 Quadrangle (156.29° W - 156.89° W, 71.25° N - 71.40° N), for use in Geographic Information Systems (GIS) and remote sensing software. The original QuickBird data sets were acquired by DigitalGlobe from 1 to 2 August 2002, and consist of orthorectified satellite imagery. Federal Geographic Data Committee (FGDC)-compliant metadata for all value-added data sets are provided in text, HTML, and XML formats. Accessory layers include: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); an index map for the 62 QuickBird tiles (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow QuickBird image area and the Barrow B4 quadrangle area (ESRI Shapefile format). Unmodified QuickBird data comprise 62 data tiles in Universal Transverse Mercator (UTM) Zone 4 in GeoTIFF format. Standard release files describing the QuickBird data are included, along with the DigitalGlobe license agreement and product handbooks. The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are provided on four DVDs. This product is available only to investigators funded specifically from the National Science Foundation (NSF), Office of Polar Programs (OPP), Arctic Sciences Section. An NSF OPP award number must be provided when ordering this data.

This data set contains small-scale base GIS data layers compiled by the National Park Service Servicewide Inventory and Monitoring Program and Water Resources Division for use in a Baseline Water Quality Data Inventory and Analysis Report that was prepared for the park. The report presents the results of surface water quality data retrievals for the park from six of the United States Environmental Protection Agency's (EPA) national databases: (1) Storage and Retrieval (STORET) water quality database management system; (2) River Reach File (RF3) Hydrography; (3) Industrial Facilities Discharges; (4) Drinking Water Supplies; (5) Water Gages; and (6) Water Impoundments. The small-scale GIS data layers were used to prepare the maps included in the report that depict the locations of water quality monitoring stations, industrial discharges, drinking intakes, water gages, and water impoundments. The data layers included in the maps (and this dataset) vary depending on availability, but generally include roads, hydrography, political boundaries, USGS 7.5' minute quadrangle outlines, hydrologic units, trails, and others as appropriate. The scales of each layer vary depending on data source but are generally 1:100,000.

This National Geographic Style Map (World Edition) web map provides a reference map for the world that includes administrative boundaries, cities, protected areas, highways, roads, railways, water features, buildings, and landmarks, overlaid on shaded relief and a colorized physical ecosystems base for added context to conservation and biodiversity topics. Alignment of boundaries is a presentation of the feature provided by our data vendors and does not imply endorsement by Esri, National Geographic or any governing authority.This basemap, included in the ArcGIS Living Atlas of the World, uses the National Geographic Style vector tile layer and the National Geographic Style Base and World Hillshade raster tile layers.The vector tile layer in this web map is built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layers referenced in this map.

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Point Conception map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Point Conception map area data layers. Data layers are symbolized as shown on the associated map sheets.

The Mid-Century Map (World Edition) web map provides a customized world basemap symbolized with a unique "Mid-Century" style. It takes its inspiration from the art and advertising of the 1950's with unique fonts. The symbols for cities and capitals have an atomic slant to them. The map data includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, building footprints, and administrative boundaries.This basemap, included in the ArcGIS Living Atlas of the World, uses the Mid-Century vector tile layer.The vector tile layer in this web map is built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layer referenced in this map.

The way to access Layers Quickly.

Quick Layers is an Add-In for ArcGIS Pro 3 that allows rapid access to the DNR's Geospatial Data Resource Site (GDRS). The GDRS is a data structure that serves core geospatial dataset and applications for not only DNR, but many state agencies, and supports the Minnesota Geospatial Commons. Data added from Quick Layers is pre-symbolized, helping to standardize visualization and map production. Current version: 3.11

To use Quick Layers with the GDRS, there's no need to download QuickLayers from this location. Instead, download a full copy or a custom subset of the public GDRS (including Quick Layers for ArcGIS Pro 3) using GDRS Manager.

Quick Layers also allows users to save and share their own pre-symbolized layers, thus increasing efficiency and consistency across the enterprise.

Installation:

After using GDRS Manager to create a GDRS, including Quick Layers, add the path to the Quick Layers addin to the list of shared folders:
1. Open ArcGIS Pro
2. Project -> Add-In Manager -> Options
3. Click add folder, and enter the location of the Quick Layers Pro app. For example, if your GDRS is mapped to the V drive, the path would be V:\gdrs\apps\pub\us_mn_state_dnr\quick_layers_pro3
4. After you do this, the Quick Layers ribbon will be available. To also add Quick Layers to the Quick Access Toolbar at the top, right click Quick Layers, and select Add to Quick Access Toolbar

The link below is only for those who are using Quick Layers without a GDRS. To get the most functionality out of Quick Layers, don't install it separately, but instead download it as part of a GDRS build using GDRS Manager.

Note: The schema changed in February 2025 - please see below. We will post a roadmap of upcoming changes, but service URLs and schema are now stable. For deployment status of new services beginning in February 2025, see https://gis.data.ca.gov/pages/city-and-county-boundary-data-status. Additional roadmap and status links at the bottom of this metadata.This dataset is regularly updated as the source data from CDTFA is updated, as often as many times a month. If you require unchanging point-in-time data, export a copy for your own use rather than using the service directly in your applications. PurposeCounty boundaries along with third party identifiers used to join in external data. Boundaries are from the California Department of Tax and Fee Administration (CDTFA). These boundaries are the best available statewide data source in that CDTFA receives changes in incorporation and boundary lines from the Board of Equalization, who receives them from local jurisdictions for tax purposes. Boundary accuracy is not guaranteed, and though CDTFA works to align boundaries based on historical records and local changes, errors will exist. If you require a legal assessment of boundary location, contact a licensed surveyor.This dataset joins in multiple attributes and identifiers from the US Census Bureau and Board on Geographic Names to facilitate adding additional third party data sources. In addition, we attach attributes of our own to ease and reduce common processing needs and questions. Finally, coastal buffers are separated into separate polygons, leaving the land-based portions of jurisdictions and coastal buffers in adjacent polygons. This feature layer is for public use. Related LayersThis dataset is part of a grouping of many datasets:Cities: Only the city boundaries and attributes, without any unincorporated areasWith Coastal BuffersWithout Coastal BuffersCounties: Full county boundaries and attributes, including all cities within as a single polygonWith Coastal Buffers (this dataset)Without Coastal BuffersCities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.With Coastal BuffersWithout Coastal BuffersCity and County AbbreviationsUnincorporated Areas (Coming Soon)Census Designated PlacesCartographic CoastlinePolygonLine source (Coming Soon)State BoundaryWith Bay CutsWithout Bay Cuts Working with Coastal Buffers The dataset you are currently viewing includes the coastal buffers for cities and counties that have them in the source data from CDTFA. In the versions where they are included, they remain as a second polygon on cities or counties that have them, with all the same identifiers, and a value in the COASTAL field indicating if it"s an ocean or a bay buffer. If you wish to have a single polygon per jurisdiction that includes the coastal buffers, you can run a Dissolve on the version that has the coastal buffers on all the fields except OFFSHORE and AREA_SQMI to get a version with the correct identifiers. Point of ContactCalifornia Department of Technology, Office of Digital Services, gis@state.ca.gov Field and Abbreviation DefinitionsCDTFA_COUNTY: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.CDTFA_COPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering system. The boundary data originate with CDTFA's teams managing tax rate information, so this field is preserved and flows into this dataset.CENSUS_GEOID: numeric geographic identifiers from the US Census BureauCENSUS_PLACE_TYPE: City, County, or Town, stripped off the census name for identification purpose.GNIS_PLACE_NAME: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information SystemGNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.CDT_COUNTY_ABBR: Abbreviations of county names - originally derived from CalTrans Division of Local Assistance and now managed by CDT. Abbreviations are 3 characters.CDT_NAME_SHORT: The name of the jurisdiction (city or county) with the word "City" or "County" stripped off the end. Some changes may come to how we process this value to make it more consistent.AREA_SQMI: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.OFFSHORE: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".PRIMARY_DOMAIN: Currently empty/null for all records. Placeholder field for official URL of the city or countyCENSUS_POPULATION: Currently null for all records. In the future, it will include the most recent US Census population estimate for the jurisdiction.GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead. Boundary AccuracyCounty boundaries were originally derived from a 1:24,000 accuracy dataset, with improvements made in some places to boundary alignments based on research into historical records and boundary changes as CDTFA learns of them. City boundary data are derived from pre-GIS tax maps, digitized at BOE and CDTFA, with adjustments made directly in GIS for new annexations, detachments, and corrections.Boundary accuracy within the dataset varies. While CDTFA strives to correctly include or exclude parcels from jurisdictions for accurate tax assessment, this dataset does not guarantee that a parcel is placed in the correct jurisdiction. When a parcel is in the correct jurisdiction, this dataset cannot guarantee accurate placement of boundary lines within or between parcels or rights of way. This dataset also provides no information on parcel boundaries. For exact jurisdictional or parcel boundary locations, please consult the county assessor's office and a licensed surveyor. CDTFA's data is used as the best available source because BOE and CDTFA receive information about changes in jurisdictions which otherwise need to be collected independently by an agency or company to compile into usable map boundaries. CDTFA maintains the best available statewide boundary information. CDTFA's source data notes the following about accuracy: City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. Boundary ProcessingThese data make a structural change from the source data. While the full boundaries provided by CDTFA include coastal buffers of varying sizes, many users need boundaries to end at the shoreline of the ocean or a bay. As a result, after examining existing city and county boundary layers, these datasets provide a coastline cut generally along the ocean facing coastline. For county boundaries in northern California, the cut runs near the Golden Gate Bridge, while for cities, we cut along the bay shoreline and into the edge of the Delta at the boundaries of Solano, Contra Costa, and Sacramento counties. In the services linked above, the versions that include the coastal buffers contain them as a second (or third) polygon for the city or county, with the value in the COASTAL field set to whether it"s a bay or ocean polygon. These can be processed back into a single polygon by dissolving on all the fields you wish to keep, since the attributes, other than the COASTAL field and geometry attributes (like areas) remain the same between the polygons for this purpose. SliversIn cases where a city or county"s boundary ends near a coastline, our coastline data may cross back and forth many times while roughly paralleling the jurisdiction"s boundary, resulting in many polygon slivers. We post-process the data to remove these slivers using a city/county boundary priority algorithm. That is, when the data run parallel to each other, we discard the coastline cut and keep the CDTFA-provided boundary, even if it extends into the ocean a small amount. This processing supports consistent boundaries for Fort Bragg, Point Arena, San Francisco, Pacifica, Half Moon Bay, and Capitola, in addition to others. More information on this algorithm will be provided soon. Coastline CaveatsSome cities have buffers extending into water bodies that we do not cut at the shoreline. These include South Lake Tahoe and Folsom, which extend into neighboring lakes, and San Diego and surrounding cities that extend into San Diego Bay, which our shoreline encloses. If you have feedback on the exclusion of these

This web map created by the Colorado Governor's Office of Information Technology GIS team, serves as a basemap specific to the state of Colorado. The basemap includes general layers such as counties, municipalities, roads, waterbodies, state parks, national forests, national wilderness areas, and trails.Layers:Layer descriptions and sources can be found below. Layers have been modified to only represent features within Colorado and are not up to date. Layers last updated February 23, 2023. Colorado State Extent: Description: “This layer provides generalized boundaries for the 50 States and the District of Columbia.” Notes: This layer was filtered to only include the State of ColoradoSource: Esri Living Atlas USA States Generalized Boundaries Feature LayerState Wildlife Areas:Description: “This data was created by the CPW GIS Unit. Property boundaries are created by dissolving CDOWParcels by the property name, and property type and appending State Park boundaries designated as having public access. All parcel data correspond to legal transactions made by the CPW Real Estate Unit. The boundaries of the CDOW Parcels were digitized using metes and bounds, BLM's GCDB dataset, the PLSS dataset (where the GCDB dataset was unavailable) and using existing digital data on the boundaries.” Notes: The state wildlife areas layer in this basemap is filtered from the CPW Managed Properties (public access only) layer from this feature layer hosted in ArcGIS Online Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerMunicipal Boundaries:Description: "Boundaries data from the State Demography Office of Colorado Municipalities provided by the Department of Local Affairs (DOLA)"Source: Colorado Information Marketplace Municipal Boundaries in ColoradoCounties:Description: “This layer presents the USA 2020 Census County (or County Equivalent) boundaries of the United States in the 50 states and the District of Columbia. It is updated annually as County (or County Equivalent) boundaries change. The geography is sources from US Census Bureau 2020 TIGER FGDB (National Sub-State) and edited using TIGER Hydrology to add a detailed coastline for cartographic purposes. Geography last updated May 2022.” Notes: This layer was filtered to only include counties in the State of ColoradoSource: Esri USA Census Counties Feature LayerInterstates:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: Interstates are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointU.S. Highways:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: U.S. Highways are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointState Highways:Description: Authoritative data from the Colorado Department of Transportation representing Highways Notes: State Highways are filtered by route sign from this CDOT Highways layer Source: Colorado Department of Transportation Highways REST EndpointMajor Roads:Description: Authoritative data from the Colorado Department of Transportation representing major roads Source: Colorado Department of Transportation Major Roads REST EndpointLocal Roads:Description: Authoritative data from the Colorado Department of Transportation representing local roads Source: Colorado Department of Transportation Local Roads REST EndpointRail Lines:Description: Authoritative data from the Colorado Department of Transportation representing rail lines Source: Colorado Department of Transportation Rail Lines REST EndpointCOTREX Trails:Description: “The Colorado Trail System, now titled the Colorado Trail Explorer (COTREX), endeavors to map every trail in the state of Colorado. Currently their are nearly 40,000 miles of trails mapped. Trails come from a variety of sources (USFS, BLM, local parks & recreation departments, local governments). Responsibility for accuracy of the data rests with the source.These data were last updated on 2/5/2019” Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerNHD Waterbodies:Description: “The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.”Notes: This layer was filtered to only include waterbodies in the State of ColoradoSource: National Hydrography Dataset Plus Version 2.1 Feature LayerNHD Flowlines:Description: “The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.”Notes: This layer was filtered to only include flowline features in the State of ColoradoSource: National Hydrography Dataset Plus Version 2.1 Feature LayerState Parks:Description: “This data was created by the CPW GIS Unit. Property boundaries are created by dissolving CDOWParcels by the property name, and property type and appending State Park boundaries designated as having public access. All parcel data correspond to legal transactions made by the CPW Real Estate Unit. The boundaries of the CDOW Parcels were digitized using metes and bounds, BLM's GCDB dataset, the PLSS dataset (where the GCDB dataset was unavailable) and using existing digital data on the boundaries.” Notes: The state parks layer in this basemap is filtered from the CPW Managed Properties (public access only) layer from this feature layer Source: Colorado Parks and Wildlife CPW Admin Data Feature LayerDenver Parks:Description: "This dataset should be used as a reference to locate parks, golf courses, and recreation centers managed by the Department of Parks and Recreation in the City and County of Denver. Data is based on parcel ownership and does not include other areas maintained by the department such as medians and parkways. The data should be used for planning and design purposes and cartographic purposes only."Source: City and County of Denver Parks REST EndpointNational Wilderness Areas:Description: “A parcel of Forest Service land congressionally designated as wilderness such as National Wilderness Area.”Notes: This layer was filtered to only include National Wilderness Areas in the State of ColoradoSource: United States Department of Agriculture National Wilderness Areas REST EndpointNational Forests: Description: “A depiction of the boundaries encompassing the National Forest System (NFS) lands within the original proclaimed National Forests, along with subsequent Executive Orders, Proclamations, Public Laws, Public Land Orders, Secretary of Agriculture Orders, and Secretary of Interior Orders creating modifications thereto, along with lands added to the NFS which have taken on the status of 'reserved from the public domain' under the General Exchange Act. The following area types are included: National Forest, Experimental Area, Experimental Forest, Experimental Range, Land Utilization Project, National Grassland, Purchase Unit, and Special Management Area.”Notes: This layer was filtered to only include National Forests in the State of ColoradoSource: United States Department of Agriculture Original Proclaimed National Forests REST Endpoint

This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups include: new/revised datasets (paleo-geothermal features, geochemistry, geophysics, heat flow, slip and dilation, potential structures, geothermal power plants, positive and negative test sites), machine learning model input grids, machine learning models (Artificial Neural Network (ANN), Extreme Learning Machine (ELM), Bayesian Neural Network (BNN), Principal Component Analysis (PCA/PCAk), Non-negative Matrix Factorization (NMF/NMFk) - supervised and unsupervised), original NV Play Fairway data and models, and NV cultural/reference data.

See layer descriptions for additional metadata. Smaller GIS resource packages (by category) can be found in the related datasets section of this submission. A submission linking the full codebase for generating machine learning output models is available through the "Related Datasets" link on this page, and contains results beyond the top picks present in this compilation.

The Federal Emergency Management Agency (FEMA) produces Flood Insurance Rate maps and identifies Special Flood Hazard Areas as part of the National Flood Insurance Program's floodplain management. Special Flood Hazard Areas have regulations that include the mandatory purchase of flood insurance for holders of federally regulated mortgages. In addition, this layer can help planners and firms avoid areas of flood risk and also avoid additional cost to carry insurance for certain planned activities. Dataset SummaryPhenomenon Mapped: Flood Hazard AreasGeographic Extent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Northern Mariana Islands and American Samoa.Projection: Web Mercator Auxiliary SphereData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Northern Mariana Islands, and American Samoa)Cell Sizes: 10 meters (default), 30 meters, and 90 metersUnits: NoneSource Type: ThematicPixel Type: Unsigned integerSource: Federal Emergency Management Agency (FEMA)Update Frequency: AnnualPublication Date: May 7, 2025 This layer is derived from the May 7, 2025 version Flood Insurance Rate Map feature class S_FLD_HAZ_AR. The vector data were then flagged with an index of 94 classes, representing a unique combination of values displayed by three renderers. (In three resolutions the three renderers make nine processing templates.) Repair Geometry was run on the set of features, then the features were rasterized using the 94 class index at a resolutions of 10, 30, and 90 meters, using the Polygon to Raster tool and the "MAXIMUM_COMBINED_AREA" option. Not every part of the United States is covered by flood rate maps. This layer compiles all the flood insurance maps available at the time of publication. To make analysis easier, areas that were NOT mapped by FEMA for flood insurance rates no longer are served as NODATA but are filled in with a value of 250, representing any unmapped areas which appear in the US Census boundary of the USA states and territories. The attribute table corresponding to value 250 will indicate that the area was not mapped.What can you do with this layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application. Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "flood hazard areas" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "flood hazard areas" in the search box, browse to the layer then click OK. In ArcGIS Pro you can use the built-in raster functions to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro. The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one. Processing TemplatesCartographic Renderer - The default. These are meaningful classes grouped by FEMA which group its own Flood Zone Type and Subtype fields. This renderer uses FEMA's own cartographic interpretations of its flood zone and zone subtype fields to help you identify and assess risk. Flood Zone Type Renderer - Specifically renders FEMA FLD_ZONE (flood zone) attribute, which distinguishes the original, broadest categories of flood zones. This renderer displays high level categories of flood zones, and is less nuanced than the Cartographic Renderer. For example, a fld_zone value of X can either have moderate or low risk depending on location. This renderer will simply render fld_zone X as its own color without identifying "500 year" flood zones within that category.Flood Insurance Requirement Renderer - Shows Special Flood Hazard Area (SFHA) true-false status. This may be helpful if you want to show just the places where flood insurance is required. A value of True means flood insurance is mandatory in a majority of the area covered by each 10m pixel. Each of these three renderers have templates at three different raster resolutions depending on your analysis needs. To include the layer in web maps to serve maps and queries, the 10 meter renderers are the preferred option. These are served with overviews and render at all resolutions. However, when doing analysis of larger areas, we now offer two coarser resolutions of 30 and 90 meters in processing templates for added convenience and time savings.Data DictionaryMaking a copy of your area of interest using copyraster in arcgis pro will copy the layer's attribute table to your network alongside the local output raster. The raster attribute table in the copied raster will contain the flood zone, zone subtype, and special flood hazard area true/false flag which corresponds to each value in the layer for your area of interest. For your convienence, we also included a table in CSV format in the box below as a data dictionary you can use as an index to every value in the layer. Value,FLD_ZONE,ZONE_SUBTY,SFHA_TF 2,A,, 3,A,,F 4,A,,T 5,A,,T 6,A,,T 7,A,1 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN CHANNEL,T 8,A,1 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN STRUCTURE,T 9,A,ADMINISTRATIVE FLOODWAY,T 10,A,COASTAL FLOODPLAIN,T 11,A,FLOWAGE EASEMENT AREA,T 12,A99,,T 13,A99,AREA WITH REDUCED FLOOD RISK DUE TO LEVEE,T 14,AE,,F 15,AE,,T 16,AE,,T 17,AE,,T 18,AE,1 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN CHANNEL,T 19,AE,1 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN STRUCTURE,T 20,AE,"1 PCT CONTAINED IN STRUCTURE, COMMUNITY ENCROACHMENT",T 21,AE,"1 PCT CONTAINED IN STRUCTURE, FLOODWAY",T 22,AE,ADMINISTRATIVE FLOODWAY,T 23,AE,AREA OF SPECIAL CONSIDERATION,T 24,AE,COASTAL FLOODPLAIN,T 25,AE,COLORADO RIVER FLOODWAY,T 26,AE,COMBINED RIVERINE AND COASTAL FLOODPLAIN,T 27,AE,COMMUNITY ENCROACHMENT,T 28,AE,COMMUNITY ENCROACHMENT AREA,T 29,AE,DENSITY FRINGE AREA,T 30,AE,FLOODWAY,T 31,AE,FLOODWAY CONTAINED IN CHANNEL,T 32,AE,FLOODWAY CONTAINED IN STRUCTURE,T 33,AE,FLOWAGE EASEMENT AREA,T 34,AE,RIVERINE FLOODWAY IN COMBINED RIVERINE AND COASTAL ZONE,T 35,AE,RIVERINE FLOODWAY SHOWN IN COASTAL ZONE,T 36,AE,STATE ENCROACHMENT AREA,T 37,AH,,T 38,AH,,T 39,AH,FLOODWAY,T 40,AO,,T 41,AO,COASTAL FLOODPLAIN,T 42,AO,FLOODWAY,T 43,AREA NOT INCLUDED,,F 44,AREA NOT INCLUDED,,T 45,AREA NOT INCLUDED,,U 46,D,,F 47,D,,T 48,D,AREA WITH FLOOD RISK DUE TO LEVEE,F 49,OPEN WATER,,F 50,OPEN WATER,,T 51,OPEN WATER,,U 52,V,,T 53,V,COASTAL FLOODPLAIN,T 54,VE,,T 55,VE,,T 56,VE,COASTAL FLOODPLAIN,T 57,VE,RIVERINE FLOODWAY SHOWN IN COASTAL ZONE,T 58,X,,F 59,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD,F 60,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD,T 61,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD,U 62,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN CHANNEL,F 63,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD CONTAINED IN STRUCTURE,F 64,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD IN COASTAL ZONE,F 65,X,0.2 PCT ANNUAL CHANCE FLOOD HAZARD IN COMBINED RIVERINE AND COASTAL ZONE,F 66,X,"1 PCT CONTAINED IN STRUCTURE, COMMUNITY ENCROACHMENT",F 67,X,"1 PCT CONTAINED IN STRUCTURE, FLOODWAY",F 68,X,1 PCT DEPTH LESS THAN 1 FOOT,F 69,X,1 PCT DRAINAGE AREA LESS THAN 1 SQUARE MILE,F 70,X,1 PCT FUTURE CONDITIONS,F 71,X,1 PCT FUTURE CONDITIONS CONTAINED IN STRUCTURE,F 72,X,"1 PCT FUTURE CONDITIONS, COMMUNITY ENCROACHMENT",F 73,X,"1 PCT FUTURE CONDITIONS, FLOODWAY",F 74,X,"1 PCT FUTURE IN STRUCTURE, COMMUNITY ENCROACHMENT",F 75,X,"1 PCT FUTURE IN STRUCTURE, FLOODWAY",F 76,X,AREA OF MINIMAL FLOOD HAZARD, 77,X,AREA OF MINIMAL FLOOD HAZARD,F 78,X,AREA OF MINIMAL FLOOD HAZARD,T 79,X,AREA OF MINIMAL FLOOD HAZARD,U 80,X,AREA OF SPECIAL CONSIDERATION,F 81,X,AREA WITH REDUCED FLOOD RISK DUE TO LEVEE,F 82,X,AREA WITH REDUCED FLOOD RISK DUE TO LEVEE,T 83,X,FLOWAGE EASEMENT AREA,F 84,X,1 PCT FUTURE CONDITIONS,T 85,AH,COASTAL FLOODPLAIN,T 86,AE,,U 87,AE,FLOODWAY,F 88,X,AREA WITH REDUCED FLOOD HAZARD DUE TO ACCREDITED LEVEE SYSTEM,F 89,X,530,F 90,VE,100,T 91,AE,100,T 92,A99,AREA WITH REDUCED FLOOD HAZARD DUE TO LEVEE SYSTEM,T 93,A99,AREA WITH REDUCED FLOOD HAZARD DUE TO NON-ACCREDITED LEVEE SYSTEM,T 94,A,COMBINED RIVERINE AND COASTAL FLOODPLAIN,T 250,AREA NOT INCLUDED,Not Mapped by FEMA, Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

This product set contains high-resolution Interferometric Synthetic Aperture Radar (IFSAR) imagery and geospatial data for the Barrow Peninsula (155.39 - 157.48 deg W, 70.86 - 71.47 deg N) and Barrow Triangle (156.13 - 157.08 deg W, 71.14 - 71.42 deg N), for use in Geographic Information Systems (GIS) and remote sensing software. The primary IFSAR data sets were acquired by Intermap Technologies from 27 to 29 July 2002, and consist of Orthorectified Radar Imagery (ORRI), a Digital Surface Model (DSM), and a Digital Terrain Model (DTM). Derived data layers include aspect, shaded relief, and slope-angle grids (floating-point binary and ArcInfo grid format), as well as a vector layer of contour lines (ESRI Shapefile format). Also available are accessory layers compiled from other sources: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); a quarter-quadrangle index map for the 26 IFSAR tiles (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow Peninsula (ESRI Shapefile format). Unmodified IFSAR data comprise 26 data tiles across UTM zones 4 and 5. The DSM and DTM tiles (5 m resolution) are provided in floating-point binary format with header and projection files. The ORRI tiles (1.25 m resolution) are available in GeoTIFF format. FGDC-compliant metadata for all data sets are provided in text, HTML, and XML formats, along with the Intermap License Agreement and product handbook. The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are provided on five DVDs, available through licensing only to National Science Foundation (NSF)-funded investigators. An NSF award number must be provided when ordering data.

The geodatabase contains 13 relate tables that together provide updated and synchronized classifications to an existing vegetation map layer for each of the nine park units in the Great Lakes Network (GLKN) of the National Park Service (NPS) Natural Resource Inventory and Monitoring Program. The classifications include 1) vegetation types at every hierarchical level in the 2015 version of the U.S. National Vegetation Classification (USNVC) and 2) map classes that represent vegetation and land cover in the vegetation map layers. Furthermore, the tables provide a crosswalk between the two classifications (vegetation and map). Each park unit in GLKN has received, at different times over several years, vegetation data products from the NPS Vegetation Mapping Inventory (VMI) Program. However, the vegetation and map classifications were at different stages of development over these years. With this geodatabase product, having a series of already linked relate tables, the original vegeta ...

The Human Geography Dark Map (World Edition) web map provides a detailed world basemap with a dark monochromatic style and content adjusted to support human geography information. Where possible, the map content has been adjusted so that it observes WCAG contrast criteria.This basemap, included in the ArcGIS Living Atlas of the World, uses 3 vector tile layers:Human Geography Dark Label, a label reference layer including cities and communities, countries, administrative units, and at larger scales street names.Human Geography Dark Detail, a detail reference layer including administrative boundaries, roads and highways, and larger bodies of water. This layer is designed to be used with a high degree of transparency so that the detail does not compete with your information. It is set at approximately 50% in this web map, but can be adjusted.Human Geography Dark Base, a simple basemap consisting of land areas in a very dark gray only.The vector tile layers in this web map are built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Learn more about this basemap from the cartographic designer in A Dark Version of the Human Geography Basemap.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layers referenced in this map.