The Advanced Weather Interactive Processing System (AWIPS) uses shapefiles for base maps in the system. These shapefiles contain boundaries of areas used by NWS for forecasts and warnings as well as map backgrounds.NWS BordersThe County Warning Area boundaries are the counties/zones for which each Weather Forecast Office (WFO) is responsible for issuing forecasts and warnings. The shapefile was created by aggregating public zones with the same CWA designation into a single polygon and manually adjusting the boundaries of the exceptions to the rule.The NWS county and state borders are background map used internally in NWS.Coastal Marine Zone ForecastThis map layer contains links to NWS marine weather forecasts for coastal or nearshore waters within 20nm of shore out to Day 5. It includes predictions on the likelihood of precipitation and/or reduced visibility, surface wind direction and speed, seas or combined seas, and icing. Air temperature forecasts are optional. The forecasts will also include any marine weather advisories, watches, and/or warnings. The purpose of the forecasts is to support and promote safe transportation across the coastal waters. The forecasts are issued twice per day with updates as necessary by NWS Weather Forecast Offices (WFOs) along the coast and Great Lakes.Offshore Zone ForecastsThis map layer contains links to NWS marine weather forecasts for offshore waters beyond 20 or 30nm of shore out to Day 5. The forecast provides information to mariners who travel on the oceanic waters adjacent to the U.S., its territorial coastal waters and the Caribbean Sea. The forecasts include predictions on the likelihood of precipitation and/or reduced visibility, surface wind direction and speed, seas and likelihood of icing out to Day 5 along with information about any warnings. The offshore forecasts for the Western North Atlantic and Eastern North Pacific Oceans are produced by NWS/NCEP's Ocean Prediction Center. The offshore forecasts for the Gulf of Mexico and Caribbean Sea are issued by the NWS/NCEP National Hurricane Center's Tropical Analysis and Forecast Branch (TAFB). OPC and NHC/TAFB issues the forecasts four times daily at regular intervals, with updates when necessary. The offshore forecast for the waters around Hawaii are issued by the NWS Weather Forecast Office in Honolulu, HI four times daily at regular intervals, with updates when necessary. The offshore forecasts for Alaska waters in the Bering Sea and Gulf of Alaska are issued by NWS Weather Forecast Offices in Alaska at least twice a day with updates as necessary. The WFOs in Alaska include WFO Anchorage, WFO Fairbanks, and WFO Juneau.Public Weather Zone ForecastsThis layer includes links to NWS web pages posting the latest NWS surface weather forecasts, a zone-type forecast providing the average forecast conditions across the zone, usually at the county-scale or sub-county scale. These text forecasts include predictions of weather, sky cover, maximum and minimum surface air temperatures, surface wind direction and speed, and probability of precipitation out to 7 days into the future. In addition, the forecast highlights at the top include any active weather advisories, watches, and/or warnings. These zone predictions are derived from gridded forecasts created by NWS Weather Forecast Offices throughout the U.S. The text weather forecasts are usually issued in the early morning (e.g. 4AM LT) and early evening (4PM LT). They are updated during late mornings and late night and during fast changing weather conditions.Fire Weather Zone ForecastsThis layer includes links to NWS web pages posting the latest NWS Fire Weather Planning Forecasts, a zone-type forecast providing the average fire weather conditions across the zone. According to the NWS, the forecast is "used by land management personnel primarily for input in decision-making related to pre-suppression and other planning." The forecast is valid from the time of issuance through day five and sometimes through day seven and usually has a minimum of three 12-hour time periods. The forecast will have included a discussion of weather patterns affecting the forecast zone or area, identification of any active fire weather watches/warnings and a table of predicted fire weather variables for the next two days: 1) sky/weather conditions, 2) max/min air temperatures, 3) max/min relative humidity, 4) 0-minute average wind direction/speed at 20 feet and sometimes at another height (e.g. 10,000, 15,000 ft), 5) precipitation amount, duration, and timing, 6) mixing height, 7) transport winds, 8) vent category, and 9) several fire weather indices such as Haines Index, Lightning Activity (LAL), Chance of Wetting Rainfall (CWR), Dispersion Index, Low Visibility Occurrence Risk Index (LVORI), and Max LVORI. In addition, it will usually have a forecast in plain text for days 3 to 7. Sometimes an optional outlook of expected conditions for day 6 or possibly for day 6 and 7 is expected. The forecasts are issued by NWS WFOs at least once daily during the local fire season.Metadata:CWA: https://www.weather.gov/gis/CWAmetadataCoastal Marine: https://www.weather.gov/gis/CoastalMarineMetadataOffshore: https://www.weather.gov/gis/OffshoreZoneMetadataPublic Zones: https://www.weather.gov/gis/PublicZoneMetadataFire Zones: https://www.weather.gov/gis/FireZoneMetadataCounties: https://www.weather.gov/gis/CountyMetadataStates: https://www.weather.gov/gis/StateMetadataLink to data download: https://www.weather.gov/gis/AWIPSShapefilesQuestions/Concerns about the service, please contact the DISS GIS teamTime Information:This service is not time enabled

The Community Map (World Edition) web map provides a customized world basemap that is uniquely symbolized and optimized to display special areas of interest (AOIs) that have been created and edited by Community Maps contributors. These special areas of interest include landscaping features such as grass, trees, and sports amenities like tennis courts, football and baseball field lines, and more. This basemap, included in the ArcGIS Living Atlas of the World, uses the Community 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 layer items referenced in this map.

SLIDO-4.5 is an Esri ArcGIS version 10.7 file geodatabase which can be downloaded here: https://www.oregon.gov/dogami/slido/Pages/data.aspx The geodatabase contains two feature datasets (a group of datasets within the geodatabase) containing six feature classes total, as well as two raster data sets, one individual table, and two individual feature classes. The original studies vary widely in scale, scope and focus which is reflected in the wide range of accuracy, detail, and completeness with which landslides are mapped. In the future, we propose a continuous update of SLIDO. These updates should take place: 1) each time DOGAMI publishes a new GIS dataset that contains landslide inventory or susceptibility data or 2) at the end of each winter season, a common time for landslide occurrences in Oregon, which will include recent historic landslide point data. In order to keep track of the updates, we will use a primary release number such as Release 4.0 along with a decimal number identifying the update such as 4.5.

Reference maps illustrate the location of census standard geographic areas for which census statistical data are tabulated and disseminated. The maps display the boundaries, names and unique identifiers of standard geographic areas, as well as physical features such as streets, railroads, coastlines, rivers and lakes. Reference maps include: Standard Geographical Classification (SGC) Census tracts Federal electoral districts

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.

This dataset describes the Release File structure of SNOMED CT, referred to as Release Format 2 (RF2). The US Edition of SNOMED CT is the official source of SNOMED CT for use in US healthcare systems. The US Edition is a standalone release that combines the content of both the US Extension and the International release of SNOMED CT.

A Simple Map Reference set is used to represent one-to-one maps between SNOMED CT concepts and codes in another terminology, classification or code system.

Reference maps illustrate the location of census standard geographic areas for which census statistical data are tabulated and disseminated. The maps display the boundaries, names and unique identifiers of standard geographic areas, as well as physical features such as streets, railroads, coastlines, rivers and lakes. Reference maps include: Standard Geographical Classification (SGC) Census tracts Federal electoral districts

The Atlas of Canada Small-scale Reference Maps are a collection of digital and print-ready 8.5” x 11” sized maps of Canada’s provinces and territories. It also includes a collection of maps of the continents and the World. Each map is available in three formats – colour, black and white, and black and white without names. The maps are suited for the general public and for educators to use in their classrooms wherever geography or environmental sciences are taught. This collection of maps compliment the Atlas of Canada Reference Map (wall map) Series. Further information on all these maps can be found on the Atlas of Canada web site at www.atlas.gc.ca.

Map Direct focus for viewing DEP Boundary Reference data. Originally created on 03/31/2015 in Map Direct Lite. Please contact GIS.Librarian@FloridaDEP.gov for more information.

Guide to Publicly Available Demographic Data This data source guide is a reference tool describing data important to workforce professionals. We created the guide because multiple federal and state organizations provide data relevant to workforce professionals; and skillful data use requires understanding: the sources of data how often it is collected, for what years it is available, and a link to the data release dates the geographic level of analysis (state, county, etc.) the variables included in the data how to access and use the data

R object in *.rds format saving the models for reference mapping using ProjectSVR.

Important Note: This item is in mature support as of June 2025 and will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This tile layer is designed to provide a a hydrologically oriented set of features to use with the World Terrain Base Layer or other simple base maps. The map features a hydro-centric design based on the amount of water flowing within the drainage network such that symbols of the same size and color represent roughly the same amount of water. This map shows surface water flow as a linear phenomenon even over and through bodies of water. Using the best available data we show relative flow accurately, so that if one river carries more water downstream than another river, the result will be that the river will have a thicker symbol on the map.This map is used as an overlay for content such as elevation from the World Terrain Base service or thematic services such as soil units, vegetation, or ecoregions. Combined with a basemap and your map services, this map provides a frame of reference for showing regional, national, and continental hydrologic phenomena such as drought, runoff, river level monitoring and flood forecasting.River names are collected in the UTF8 character set so river names are collected in their original language but are written in the Roman alphabet. Sources for all river names are from the open source geonames.org project so they are international by nature.The map is compiled from several sources. The global scales (very small scales through 1:2,300,000) include content from: HydroSHEDS, GTOPO30 Global Topographic Data, SRTM, GLWD, WorldClim, GRDC, and WWF Global 200 Terrestrial Eco Regions, with the latter three providing the inputs and basis for calculating flow. At medium scales (1:36,000 to 1:2,000,000) this service currently contains only U.S. data from the NHDPlusV2 that was jointly produced by the USGS and EPA.

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, consists of three as-complete-as-possible mosaic maps of velocities on the Antarctic ice sheet for the time periods 1995–2001, 2007–2009, and 2014–2017. The maps are posted at 450 m in the WGS 84/Antarctic Polar Stereographic projection. In addition to ice velocity, the data set provides maps of velocity error and standard deviation; counts of velocity estimates used per pixel; date ranges; and masks that delineate the ice fronts and grounding lines for the each period.

The Human Geography Map (World Edition) web map provides a detailed vector basemap with a 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 Label, a label reference layer including cities and communities, countries, administrative units, and at larger scales street names.Human Geography 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 Base, a simple basemap consisting of land areas in a very light 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 Introducing a 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 layer item referenced in this map.

City of Dunwoody Basic General Reference PDF Map

Reference map

These data were compiled for the use of training natural feature machine learning (GeoAI) detection and delineation. The natural feature classes include the Geographic Names Information System (GNIS) feature types Basins, Bays, Bends, Craters, Gaps, Guts, Islands, Lakes, Ridges and Valleys, and are an areal representation of those GNIS point features. Features were produced using heads-up digitizing from 2018 to 2019 by Dr. Sam Arundel's team at the U.S. Geological Survey, Center of Excellence for Geospatial Information Science, Rolla, Missouri, USA, and Dr. Wenwen Li's team in the School of Geographical Sciences at Arizona State University, Tempe, Arizona, USA.

For the purposes of training AI-based models to identify (map) road features in rural/remote tropical regions on the basis of true-colour satellite imagery, and subsequently testing the accuracy of these AI-derived road maps, we produced a dataset of 8904 satellite image ‘tiles’ and their corresponding known road features across Equatorial Asia (Indonesia, Malaysia, Papua New Guinea). Methods

1. INPUT 200 SATELLITE IMAGES

The main dataset shared here was derived from a set of 200 input satellite images, also provided here. These 200 images are effectively ‘screenshots’ (i.e., reduced-resolution copies) of high-resolution true-colour satellite imagery (~0.5-1m pixel resolution) observed using the Elvis Elevation and Depth spatial data portal (https://elevation.fsdf.org.au/), which here is functionally equivalent to the more familiar Google Earth. Each of these original images was initially acquired at a resolution of 1920x886 pixels. Actual image resolution was coarser than the native high-resolution imagery. Visual inspection of these 200 images suggests a pixel resolution of ~5 meters, given the number of pixels required to span features of familiar scale, such as roads and roofs, as well as the ready discrimination of specific land uses, vegetation types, etc. These 200 images generally spanned either forest-agricultural mosaics or intact forest landscapes with limited human intervention. Sloan et al. (2023) present a map indicating the various areas of Equatorial Asia from which these images were sourced.
IMAGE NAMING CONVENTION A common naming convention applies to satellite images’ file names: XX##.png where:

XX – denotes the geographical region / major island of Equatorial Asia of the image, as follows: ‘bo’ (Borneo), ‘su’ (Sumatra), ‘sl’ (Sulawesi), ‘pn’ (Papua New Guinea), ‘jv’ (java), ‘ng’ (New Guinea [i.e., Papua and West Papua provinces of Indonesia])

– denotes the ith image for a given geographical region / major island amongst the original 200 images, e.g., bo1, bo2, bo3…

1. INTERPRETING ROAD FEATURES IN THE IMAGES For each of the 200 input satellite images, its road was visually interpreted and manually digitized to create a reference image dataset by which to train, validate, and test AI road-mapping models, as detailed in Sloan et al. (2023). The reference dataset of road features was digitized using the ‘pen tool’ in Adobe Photoshop. The pen’s ‘width’ was held constant over varying scales of observation (i.e., image ‘zoom’) during digitization. Consequently, at relatively small scales at least, digitized road features likely incorporate vegetation immediately bordering roads. The resultant binary (Road / Not Road) reference images were saved as PNG images with the same image dimensions as the original 200 images.

2. IMAGE TILES AND REFERENCE DATA FOR MODEL DEVELOPMENT

The 200 satellite images and the corresponding 200 road-reference images were both subdivided (aka ‘sliced’) into thousands of smaller image ‘tiles’ of 256x256 pixels each. Subsequent to image subdivision, subdivided images were also rotated by 90, 180, or 270 degrees to create additional, complementary image tiles for model development. In total, 8904 image tiles resulted from image subdivision and rotation. These 8904 image tiles are the main data of interest disseminated here. Each image tile entails the true-colour satellite image (256x256 pixels) and a corresponding binary road reference image (Road / Not Road).
Of these 8904 image tiles, Sloan et al. (2023) randomly selected 80% for model training (during which a model ‘learns’ to recognize road features in the input imagery), 10% for model validation (during which model parameters are iteratively refined), and 10% for final model testing (during which the final accuracy of the output road map is assessed). Here we present these data in two folders accordingly:

'Training’ – contains 7124 image tiles used for model training in Sloan et al. (2023), i.e., 80% of the original pool of 8904 image tiles. ‘Testing’– contains 1780 image tiles used for model validation and model testing in Sloan et al. (2023), i.e., 20% of the original pool of 8904 image tiles, being the combined set of image tiles for model validation and testing in Sloan et al. (2023).

IMAGE TILE NAMING CONVENTION A common naming convention applies to image tiles’ directories and file names, in both the ‘training’ and ‘testing’ folders: XX##_A_B_C_DrotDDD where

XX – denotes the geographical region / major island of Equatorial Asia of the original input 1920x886 pixel image, as follows: ‘bo’ (Borneo), ‘su’ (Sumatra), ‘sl’ (Sulawesi), ‘pn’ (Papua New Guinea), ‘jv’ (java), ‘ng’ (New Guinea [i.e., Papua and West Papua provinces of Indonesia])

– denotes the ith image for a given geographical region / major island amongst the original 200 images, e.g., bo1, bo2, bo3…

A, B, C and D – can all be ignored. These values, which are one of 0, 256, 512, 768, 1024, 1280, 1536, and 1792, are effectively ‘pixel coordinates’ in the corresponding original 1920x886-pixel input image. They were recorded within the names of image tiles’ sub-directories and file names merely to ensure that names/directory were uniquely named)

rot – implies an image rotation. Not all image tiles are rotated, so ‘rot’ will appear only occasionally.

DDD – denotes the degree of image-tile rotation, e.g., 90, 180, 270. Not all image tiles are rotated, so ‘DD’ will appear only occasionally.

Note that the designator ‘XX##’ is directly equivalent to the filenames of the corresponding 1920x886-pixel input satellite images, detailed above. Therefore, each image tiles can be ‘matched’ with its parent full-scale satellite image. For example, in the ‘training’ folder, the subdirectory ‘Bo12_0_0_256_256’ indicates that its image tile therein (also named ‘Bo12_0_0_256_256’) would have been sourced from the full-scale image ‘Bo12.png’.

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.