This dataset contains the Geographic Information Systems (GIS) data for the City of Little Rock boundaries.

This dataset contains the Geographic Information Systems (GIS) data for the City of Little Rock National Historic District boundaries.

This dataset contains the Geographic Information Systems (GIS) data for the City of Little Rock Ward boundaries.

ArcGIS Feature collection service created to visualize data related to Little Rock, AR tornado activity and impacts, such as tornado tracks, damage assessments, and other related information.

This dataset contains the Geographic Information Systems (GIS) data for the City of Little Rock Fire District boundaries. Each polygon represents a Fire District, used for reference by the 911 Dispatcher.

description: The Arkansas Secretary of State contracted the University of Arkansas at Little Rock, GIS Applications Laboratory (UALRGIS) to use modern geographic information technology and improved base maps to create a current and spatially accurate statewide depiction of school district boundaries in the State of Arkansas. The Arkansas Geographic Information Office merged annexed and consolidated districts. UALRGIS followed a work plan for the project that was established by the Arkansas Geographic Information Office (AGIO) for the Secretary of State. The school district boundary editing rules were as follows: 1. Legal descriptions take precedent. 2. If no legal description was provided the visual evidence presented on the digital ortho quarter quadrangle (DOQQ) was followed. 3. Section lines, county boundaries, city boundaries and / or roads have only be used as supporting visual evidence viewed on the DOQQ.; abstract: The Arkansas Secretary of State contracted the University of Arkansas at Little Rock, GIS Applications Laboratory (UALRGIS) to use modern geographic information technology and improved base maps to create a current and spatially accurate statewide depiction of school district boundaries in the State of Arkansas. The Arkansas Geographic Information Office merged annexed and consolidated districts. UALRGIS followed a work plan for the project that was established by the Arkansas Geographic Information Office (AGIO) for the Secretary of State. The school district boundary editing rules were as follows: 1. Legal descriptions take precedent. 2. If no legal description was provided the visual evidence presented on the digital ortho quarter quadrangle (DOQQ) was followed. 3. Section lines, county boundaries, city boundaries and / or roads have only be used as supporting visual evidence viewed on the DOQQ.

The Arkansas Early Childhood Asset Map (AECAM) provides a variety of information on early childhood services in Arkansas. AECAM is composed of mapping services, a resource guide, and data from the Getting Ready for School publication. This mapping service portion of the application contains layers representing the locations of DHS approved facilities that allows users to search for facilities near their place of interest, find contact information, and access driving directions to the location.

Need to be able to automate the available child care facilities for the Arkansas Dept of Human Services to keep their list of facilities up to date. Eventually we would like to use model builder and python to avoid any human intervention, but in the meantime we can get by with just replacing the data set instead of totally rebuilding the symbology with each data update.

This dataset contains the Geographic Information Systems (GIS) data for the City of Little Rock Annexation boundaries.

Data available online through the Arkansas Spatial Data Infrastructure (http://gis.arkansas.gov). This is a layer of Arkansas State Senate Information that was reapportioned in 2001 by the Secretary of State of the State of Arkansas based on the 2000 Federal Census . Senate District boundaries were provided by the State Census Data Center, University of Arkansas, Little Rock. Source data were created by the Arkansas Attorney General's Office. This feature dataset has been updated with the names of the members of the 88th General Assembly.

Need to be able to automate the available child care facilities for the Arkansas Dept of Human Services to keep their list of facilities up to date. Eventually we would like to use model builder and python to avoid any human intervention, but in the meantime we can get by with just replacing the data set instead of totally rebuilding the symbology with each data update.

This dataset contains the Geographic Information Systems (GIS) data for the City of Little Rock Neighborhood Association boundaries along with meeting information.

Map showing rainfall in Arkansas year to date (through 5/31/2020) produced by the National Weather Service Office in Little Rock, AR. For more information about the Little Rock office, visit our website at https://www.weather.gov/lzk

This layer displays a global map of land use/land cover (LULC) derived from ESA Sentinel-2 imagery at 10m resolution. Each year is generated with Impact Observatory’s deep learning AI land classification model, trained using billions of human-labeled image pixels from the National Geographic Society. The global maps are produced by applying this model to the Sentinel-2 Level-2A image collection on Microsoft’s Planetary Computer, processing over 400,000 Earth observations per year.The algorithm generates LULC predictions for nine classes, described in detail below. The year 2017 has a land cover class assigned for every pixel, but its class is based upon fewer images than the other years. The years 2018-2024 are based upon a more complete set of imagery. For this reason, the year 2017 may have less accurate land cover class assignments than the years 2018-2024. Key Properties Variable mapped: Land use/land cover in 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024Source Data Coordinate System: Universal Transverse Mercator (UTM) WGS84Service Coordinate System: Web Mercator Auxiliary Sphere WGS84 (EPSG:3857)Extent: GlobalSource imagery: Sentinel-2 L2ACell Size: 10-metersType: ThematicAttribution: Esri, Impact ObservatoryAnalysis: Optimized for analysisClass Definitions: ValueNameDescription1WaterAreas where water was predominantly present throughout the year; may not cover areas with sporadic or ephemeral water; contains little to no sparse vegetation, no rock outcrop nor built up features like docks; examples: rivers, ponds, lakes, oceans, flooded salt plains.2TreesAny significant clustering of tall (~15 feet or higher) dense vegetation, typically with a closed or dense canopy; examples: wooded vegetation, clusters of dense tall vegetation within savannas, plantations, swamp or mangroves (dense/tall vegetation with ephemeral water or canopy too thick to detect water underneath).4Flooded vegetationAreas of any type of vegetation with obvious intermixing of water throughout a majority of the year; seasonally flooded area that is a mix of grass/shrub/trees/bare ground; examples: flooded mangroves, emergent vegetation, rice paddies and other heavily irrigated and inundated agriculture.5CropsHuman planted/plotted cereals, grasses, and crops not at tree height; examples: corn, wheat, soy, fallow plots of structured land.7Built AreaHuman made structures; major road and rail networks; large homogenous impervious surfaces including parking structures, office buildings and residential housing; examples: houses, dense villages / towns / cities, paved roads, asphalt.8Bare groundAreas of rock or soil with very sparse to no vegetation for the entire year; large areas of sand and deserts with no to little vegetation; examples: exposed rock or soil, desert and sand dunes, dry salt flats/pans, dried lake beds, mines.9Snow/IceLarge homogenous areas of permanent snow or ice, typically only in mountain areas or highest latitudes; examples: glaciers, permanent snowpack, snow fields.10CloudsNo land cover information due to persistent cloud cover.11RangelandOpen areas covered in homogenous grasses with little to no taller vegetation; wild cereals and grasses with no obvious human plotting (i.e., not a plotted field); examples: natural meadows and fields with sparse to no tree cover, open savanna with few to no trees, parks/golf courses/lawns, pastures. Mix of small clusters of plants or single plants dispersed on a landscape that shows exposed soil or rock; scrub-filled clearings within dense forests that are clearly not taller than trees; examples: moderate to sparse cover of bushes, shrubs and tufts of grass, savannas with very sparse grasses, trees or other plants.NOTE: Land use focus does not provide the spatial detail of a land cover map. As such, for the built area classification, yards, parks, and groves will appear as built area rather than trees or rangeland classes.Usage Information and Best PracticesProcessing TemplatesThis layer includes a number of preconfigured processing templates (raster function templates) to provide on-the-fly data rendering and class isolation for visualization and analysis. Each processing template includes labels and descriptions to characterize the intended usage. This may include for visualization, for analysis, or for both visualization and analysis. VisualizationThe default rendering on this layer displays all classes.There are a number of on-the-fly renderings/processing templates designed specifically for data visualization.By default, the most recent year is displayed. To discover and isolate specific years for visualization in Map Viewer, try using the Image Collection Explorer. AnalysisIn order to leverage the optimization for analysis, the capability must be enabled by your ArcGIS organization administrator. More information on enabling this feature can be found in the ‘Regional data hosting’ section of this help doc.Optimized for analysis means this layer does not have size constraints for analysis and it is recommended for multisource analysis with other layers optimized for analysis. See this group for a complete list of imagery layers optimized for analysis.Prior to running analysis, users should always provide some form of data selection with either a layer filter (e.g. for a specific date range, cloud cover percent, mission, etc.) or by selecting specific images. To discover and isolate specific images for analysis in Map Viewer, try using the Image Collection Explorer.Zonal Statistics is a common tool used for understanding the composition of a specified area by reporting the total estimates for each of the classes. GeneralIf you are new to Sentinel-2 LULC, the Sentinel-2 Land Cover Explorer provides a good introductory user experience for working with this imagery layer. For more information, see this Quick Start Guide.Global land use/land cover maps provide information on conservation planning, food security, and hydrologic modeling, among other things. This dataset can be used to visualize land use/land cover anywhere on Earth. Classification ProcessThese maps include Version 003 of the global Sentinel-2 land use/land cover data product. It is produced by a deep learning model trained using over five billion hand-labeled Sentinel-2 pixels, sampled from over 20,000 sites distributed across all major biomes of the world.The underlying deep learning model uses 6-bands of Sentinel-2 L2A surface reflectance data: visible blue, green, red, near infrared, and two shortwave infrared bands. To create the final map, the model is run on multiple dates of imagery throughout the year, and the outputs are composited into a final representative map for each year.The input Sentinel-2 L2A data was accessed via Microsoft’s Planetary Computer and scaled using Microsoft Azure Batch. CitationKarra, Kontgis, et al. “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021.AcknowledgementsTraining data for this project makes use of the National Geographic Society Dynamic World training dataset, produced for the Dynamic World Project by National Geographic Society in partnership with Google and the World Resources Institute.

List of providers used as resources:Arkansas Valley Electric Cooperativehttp://208.54.216.29/OMSWebMap/OMSWebMap.htm?clientKey=undefinedBentonville Light & Water Systemhttps://www.outageentry.com/CustomerFacingAppJQM/outage.php?clientid=BentarCarroll Electric Cooperativehttps://www.outageentry.com/CustomerFacingAppJQM/outage.php?clientid=CECARCraighead Electric Cooperativehttp://outage.craigheadelectric.coop/Entergyhttp://www.entergy.com/storm_center/outages.aspxFirst Electric Cooperativehttp://outage.fecc.coop/North Arkansas Electric Cooperativehttp://outageviewer.com/OMSWebMap/OMSWebMap.htm?clientKey=undefinedNorth Little Rock Electrichttp://nlrelectric.com/outagecenter/outage-map/OG&E Energy Corp.https://www.oge.com/wps/portal/oge/outages/systemwatchOuachita Electric Cooperativehttps://outage.oecc.com/omswebmap/OMSWebMap.htm?clientKey=undefinedOzark Border Electric Coophttps://ebill.ozarkborder.org/maps/OMSWebMap/Ozarks Electric Cooperativehttps://ebill.ozarksecc.com/woViewer/mapviewer.html?config=Outage+Web+MapPetit Jean Electric Cooperativehttps://ebill.pjecc.com/woViewer/mapviewer.html?config=Outage+Web+MapSouth Central Arkansas Electric Cooperativehttps://ebill.scaec.com/woViewer/mapviewer.html?config=Outage+Web+MapSouthwest Arkansas Electric Cooperativehttps://ebill.swrea.com/woViewer/mapviewer.html?config=Outage+Web+MapSouthwest Tennessee Electric Membership Corphttp://map.stemc.com/Southwestern Electric Power Cohttp://outagemap.swepco.com.s3.amazonaws.com/external/default.htmlWhite River Valley Electric Cooperativehttps://ebill.whiteriver.org/woViewer/mapviewer.html?config=Outage+Web+MapWoodruff Electric Cooperativehttp://www.outageentry.com/dvOSM/dvOSM2.php?Client=wecc

Geospatial data about Arkansas Power Lines (USGS). Export to CAD, GIS, PDF, CSV and access via API.

Building Outline . The footprint/outline of a structure. (This is sometimes not the same as the roofline.)

This is a map of winter weather accumulations from the winter storm that affected Arkansas during the period December 12-13, 1958.It was produced by the National Weather Service Forecast Office in Little Rock, Arkansas using ArcGIS Pro and archived data from NCDC/NCEI and local newspaper reports.

This is a map of snowfall accumulations in Arkansas for the period December 3-4, 1902. It was produced by the National Weather Service forecast office in Little Rock, Arkansas using ArcGIS pro, as well as data from historical newspapers, and archived data from NCDC/NCEI.

Building Outline . The footprint/outline of a structure. (This is sometimes not the same as the roofline.)