100+ datasets found
  1. a

    Service Locations

    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Jan 5, 2025
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    Town of Apex, North Carolina (2025). Service Locations [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/apexnc::service-locations
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    Dataset updated
    Jan 5, 2025
    Dataset authored and provided by
    Town of Apex, North Carolina
    Area covered
    Description

    The construction of this data model was adapted from the Telvent Miner & Miner ArcFM MultiSpeak data model to provide interface functionality with Milsoft Utility Solutions WindMil engineering analysis program. Database adaptations, GPS data collection, and all subsequent GIS processes were performed by Southern Geospatial Services for the Town of Apex Electric Utilities Division in accordance to the agreement set forth in the document "Town of Apex Electric Utilities GIS/GPS Project Proposal" dated March 10, 2008. Southern Geospatial Services disclaims all warranties with respect to data contained herein. Questions regarding data quality and accuracy should be directed to persons knowledgeable with the forementioned agreement.The data in this GIS with creation dates between March of 2008 and April of 2024 were generated by Southern Geospatial Services, PLLC (SGS). The original inventory was performed under the above detailed agreement with the Town of Apex (TOA). Following the original inventory, SGS performed maintenance projects to incorporate infrastructure expansion and modification into the GIS via annual service agreements with TOA. These maintenances continued through April of 2024.At the request of TOA, TOA initiated in house maintenance of the GIS following delivery of the final SGS maintenance project in April of 2024. GIS data created or modified after April of 2024 are not the product of SGS.With respect to SGS generated GIS data that are point features:GPS data collected after January 1, 2013 were surveyed using mapping grade or survey grade GPS equipment with real time differential correction undertaken via the NC Geodetic Surveys Real Time Network (VRS). GPS data collected prior to January 1, 2013 were surveyed using mapping grade GPS equipment without the use of VRS, with differential correction performed via post processing.With respect to SGS generated GIS data that are line features:Line data in the GIS for overhead conductors were digitized as straight lines between surveyed poles. Line data in the GIS for underground conductors were digitized between surveyed at grade electric utility equipment. The configurations and positions of the underground conductors are based on TOA provided plans. The underground conductors are diagrammatic and cannot be relied upon for the determination of the actual physical locations of underground conductors in the field.The Service Locations feature class was created by Southern Geospatial Services (SGS) from a shapefile of customer service locations generated by dataVoice International (DV) as part of their agreement with the Town of Apex (TOA) regarding the development and implemention of an Outage Management System (OMS).Point features in this feature class represent service locations (consumers of TOA electric services) by uniquely identifying the features with the same unique identifier as generated for a given service location in the TOA Customer Information System (CIS). This is also the mechanism by which the features are tied to the OMS. Features are physically located in the GIS based on CIS address in comparison to address information found in Wake County GIS property data (parcel data). Features are tied to the GIS electric connectivity model by identifying the parent feature (Upline Element) as the transformer that feeds a given service location.SGS was provided a shapefile of 17992 features from DV. Error potentially exists in this DV generated data for the service location features in terms of their assigned physical location, phase, and parent element.Regarding the physical location of the features, SGS had no part in physically locating the 17992 features as provided by DV and cannot ascertain the accuracy of the locations of the features without undertaking an analysis designed to verify or correct for error if it exists. SGS constructed the feature class and loaded the shapefile objects into the feature class and thus the features exist in the DV derived location. SGS understands that DV situated the features based on the address as found in the CIS. No features were verified as to the accuracy of their physical location when the data were originally loaded. It is the assumption of SGS that the locations of the vast majority of the service location features as provided by DV are in fact correct.SGS understands that as a general rule that DV situated residential features (individually or grouped) in the center of a parcel. SGS understands that for areas where multiple features may exist in a given parcel (such as commercial properties and mobile home parks) that DV situated features as either grouped in the center of the parcel or situated over buildings, structures, or other features identifiable in air photos. It appears that some features are also grouped in roads or other non addressed locations, likely near areas where they should physically be located, but that these features were not located in a final manner and are either grouped or strung out in a row in the general area of where DV may have expected they should exist.Regarding the parent and phase of the features, the potential for error is due to the "first order approximation" protocol employed by DV for assigning the attributes. With the features located as detailed above, SGS understands that DV identified the transformer closest to the service location (straight line distance) as its parent. Phase was assigned to the service location feature based on the phase of the parent transformer. SGS expects that this protocol correctly assigned parent (and phase) to a significant portion of the features, however this protocol will also obviously incorretly assign parent in many instances.To accurately identify parent for all 17992 service locations would require a significant GIS and field based project. SGS is willing to undertake a project of this magnitude at the discretion of TOA. In the meantime, SGS is maintaining (editing and adding to) this feature class as part of the ongoing GIS maintenance agreement that is in place between TOA and SGS. In lieu of a project designed to quality assess and correct for the data provided by DV, SGS will verify the locations of the features at the request of TOA via comparison of the unique identifier for a service location to the CIS address and Wake County parcel data address as issues arise with the OMS if SGS is directed to focus on select areas for verification by TOA. Additionally, as SGS adds features to this feature class, if error related to the phase and parent of an adjacent feature is uncovered during a maintenance, it will be corrected for as part of that maintenance.With respect to the additon of features moving forward, TOA will provide SGS with an export of CIS records for each SGS maintenance, SGS will tie new accounts to a physical location based on address, SGS will create a feature for the CIS account record in this feature class at the center of a parcel for a residential address or at the center of a parcel or over the correct (or approximately correct) location as determined via air photos or via TOA plans for commercial or other relevant areas, SGS will identify the parent of the service location as the actual transformer that feeds the service location, and SGS will identify the phase of the service address as the phase of it's parent.Service locations with an ObjectID of 1 through 17992 were originally physically located and attributed by DV.Service locations with an ObjectID of 17993 or higher were originally physically located and attributed by SGS.DV originated data are provided the Creation User attribute of DV, however if SGS has edited or verified any aspect of the feature, this attribute will be changed to SGS and a comment related to the edits will be provided in the SGS Edits Comments data field. SGS originated features will be provided the Creation User attribute of SGS. Reference the SGS Edits Comments attribute field Metadata for further information.

  2. Geospatial data for the Vegetation Mapping Inventory Project of Pictured...

    • catalog.data.gov
    Updated Nov 25, 2025
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    National Park Service (2025). Geospatial data for the Vegetation Mapping Inventory Project of Pictured Rocks National Lakeshore [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-pictured-rocks-national-la
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    Dataset updated
    Nov 25, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Pictured Rocks
    Description

    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.

  3. a

    ArcGIS Pro Permitting and Environmental Information Tool (APPEIT) Project...

    • hub.arcgis.com
    Updated Dec 19, 2024
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    NBAM_Org (2024). ArcGIS Pro Permitting and Environmental Information Tool (APPEIT) Project Package [Dataset]. https://hub.arcgis.com/content/37fa42c6313e4bdb9d8a9c05d2624891
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    Dataset updated
    Dec 19, 2024
    Dataset authored and provided by
    NBAM_Org
    Description

    The ArcGIS Pro Permitting and Environmental Information Tool (APPEIT) Project Package includes all of the layers that are in the NTIA Permitting and Environmental Information Application as well as the APPEIT Tool which will allow users to input a project area and determine what layers from the application overlap with it. An overview of the project package and the APPEIT tool is provided below. User instructions on how to use the tool are available here. Instructions now include how to customize the tool by adding your own data. A video explaining how to use the Project Package is also available here. Project Package OverviewThis map package includes all of the layers from the NTIA Permitting and Environmental Information Application. The layers included are all feature services from various Federal and State agencies. The map package was created with ArcGIS Pro 3.4.0. The map package was created to allow users easy access to all feature services including symbology. The map package will allow users to avoid downloading datasets individually and easily incorporate into their own GIS system. The map package includes three maps.1. Permitting and Environmental Information Application Layers for GIS Analysis - This map includes all of the map tabs shown in the application, except State Data which is provided in another tab. This map includes feature services that can be used for analysis with other project layers such as a route or project area. 2. Permitting and Environmental Information Application Layers – For Reference Only - This map includes layers that cannot be used for analysis since they are either imagery or tile layers.3. State Data - Reference Only - This map includes all relevant state data that is shown in the application.The NTIA Permitting and Environmental Information Application was created to help with your permitting planning and environmental review preparation efforts by providing access to multiple maps from publicly available sources, including federal review, permitting, and resource agencies. The application should be used for informational purposes only and is intended solely to assist users with preliminary identification of areas that may require permits or planning to avoid potentially significant impacts to environmental resources subject to the National Environmental Policy Act (NEPA) and other statutory requirements. Multiple maps are provided in the application which are created from public sources. This application does not have an exhaustive list of everything you need for permitting or environmental review for a project but is an initial starting point to see what might be required.APPEIT Tool OverviewThe Department of Commerce’s National Telecommunications and Information Administration (NTIA) is providing the ArcGIS Pro Permitting and Environmental Information Tool (APPEIT) to help federal broadband grant recipients and subgrantees identify permits and environmental factors as they plan routes for their broadband deployments. Identifying permit requirements early, initiating pre-application coordination with permitting agencies, and avoiding environmental impacts help drive successful infrastructure projects. NTIA’s public release of the APPEIT tool supports government-wide efforts to improve permitting and explore how online and digital technologies can promote efficient environmental reviews. This Esri ArcGIS Pro tool is included in the map package and was created to support permitting, planning, and environmental review preparation efforts by providing access to data layers from publicly available sources, including federal review, permitting, and resource agencies. An SOP on how to use the tool is available here. For the full list of APPEIT layers, see Appendix Table 1 in the SOP. The tool is comprised of an ArcGIS Pro Project containing a custom ArcGIS Toolbox tool, linked web map shared by the NTIA’s National Broadband Map (NBAM), a report template, and a Tasks item to guide users through using the tool. This ArcGIS Pro project and its contents (maps and data) are consolidated into this (.ppkx) project file. To use APPEIT, users will input a project area boundary or project route line in a shapefile or feature class format. The tool will return as a CSV and PDF report that lists any federal layers from the ArcGIS Pro Permitting and Environmental Information Web Map that intersect the project. Users may only input a single project area or line at a time; multiple projects or project segments will need to be screened separately. For project route lines, users are required to specify a buffer distance. The buffer distance that is used for broadband projects should be determined by the area of anticipated impact and should generally not exceed 500 feet. For example, the State of Maryland recommends a 100-foot buffer for broadband permitting. The tool restricts buffers to two miles to ensure relevant results. DisclaimerThis document is intended solely to assist federal broadband grant recipients and subgrantees in better understanding Infrastructure Investment and Jobs Act (IIJA) broadband grant programs and the requirements set forth in the Notice of Funding Opportunity (NOFO) for this program. This document does not and is not intended to supersede, modify, or otherwise alter applicable statutory or regulatory requirements, the terms and conditions of the award, or the specific application requirements set forth in the NOFO. In all cases, statutory and regulatory mandates, the terms and conditions of the award, the requirements set forth in the NOFO, and follow-on policies and guidance, shall prevail over any inconsistencies contained in this document. NTIA’s ArcGIS Pro Permitting and Environmental Information Tool (APPEIT) should be used for informational purposes only and is intended solely to assist users with preliminary identification of broadband deployments that may require permits or planning to avoid potentially significant impacts to environmental resources subject to the National Environmental Policy Act (NEPA) and other statutory requirements. The tool is not an exhaustive or complete resource and does not and is not intended to substitute for, supersede, modify, or otherwise alter any applicable statutory or regulatory requirements, or the specific application requirements set forth in any NTIA NOFO, Terms and Conditions, or Special Award Condition. In all cases, statutory and regulatory mandates, and the requirements set forth in NTIA grant documents, shall prevail over any inconsistencies contained in these templates. The tool relies on publicly available data available on the websites of other federal, state, local, and Tribal agencies, and in some instances, private organizations and research institutions. Layers identified with a double asterisk include information relevant to determining if an “extraordinary circumstance” may warrant more detailed environmental review when a categorical exclusion may otherwise apply. While NTIA continues to make amendments to its websites to comply with Section 508, NTIA cannot ensure Section 508 compliance of federal and non-federal websites or resources users may access from links on NTIA websites. All data is presented “as is,” “as available” for informational purposes. NTIA does not warrant the accuracy, adequacy, or completeness of this information and expressly disclaims liability for any errors or omissions. Please e-mail NTIAanalytics@ntia.gov with any questions.

  4. Median Type TDA

    • gis-fdot.opendata.arcgis.com
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +2more
    Updated Jul 20, 2017
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    Florida Department of Transportation (2017). Median Type TDA [Dataset]. https://gis-fdot.opendata.arcgis.com/datasets/median-type-tda
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    Dataset updated
    Jul 20, 2017
    Dataset authored and provided by
    Florida Department of Transportationhttps://www.fdot.gov/
    Area covered
    Description

    The FDOT GIS Roads with Median Types feature class provides spatial information on Florida Median Types distinguishing between lawn, paved, painted, and curbed medians. It also notes where a fence, guardrail, or barrier wall divides the two sides of a divided road. A median is defined as a barrier or other physical separation between two lanes of traffic traveling in opposite directions, which can either be raised, painted, or paved. This information is required for all functionally classified roadways On or Off the SHS. This dataset is maintained by the Transportation Data & Analytics office (TDA). The source spatial data for this hosted feature layer was created on: 11/08/2025.For more details please review the FDOT RCI Handbook Download Data: Enter Guest as Username to download the source shapefile from here: https://ftp.fdot.gov/file/d/FTP/FDOT/co/planning/transtat/gis/shapefiles/median_type.zip

  5. w

    Roosevelt Hot Springs, Utah FORGE Geology Map and GIS Data...

    • data.wu.ac.at
    zip
    Updated Jun 19, 2018
    + more versions
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    HarvestMaster (2018). Roosevelt Hot Springs, Utah FORGE Geology Map and GIS Data Utah_FORGE_geology_data_gdb.zip [Dataset]. https://data.wu.ac.at/schema/geothermaldata_org/ZGExNTJjYzAtOWM1ZS00NzZmLThhNjgtZjVhYmRjM2I3ODU5
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    zipAvailable download formats
    Dataset updated
    Jun 19, 2018
    Dataset provided by
    HarvestMaster
    Area covered
    3448b0431d49e56df985a62696ff3b8fe56e9a15
    Description

    This archive contains a geology map of the general Roosevelt Hot Springs region, both in PDF and ArcGIS geodatabase formats, that was created as part of the Utah FORGE project. This archive contains an ArcGIS geodatabase containing the GIS feature classes and symbology for the geology of the general Roosevelt Hot Springs region in Utah.

  6. a

    OGC Web Map Service (WMS): Petroleum System and Assessment of Oil and Gas,...

    • catalogue.arctic-sdi.org
    Updated May 23, 2022
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    (2022). OGC Web Map Service (WMS): Petroleum System and Assessment of Oil and Gas, Cotton Valley Group, East Texas Basin and Louisiana-Mississippi Salt Basins Provinces, Texas, Louisiana, Mississippi, Alabama, and Florida [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/search?keyword=Gulf%20Coast,%20Impacts%20of%20Energy%20Production,%20Sedimentary%20Basin,%20Oil%20and%20Natural%20Gas,%20Energy%20Resources,%20Earth%20Science,%20Natural%20Resources,%20U.S.%20Geological%20Survey,%20USGS,%20Geology,%20Natural%20Gas,%20Petroleum,%20Oil,%20Gas,%20Oil%20and%20Gas%20Exploration,%20Oil%20and%20Gas%20Production
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    Dataset updated
    May 23, 2022
    Area covered
    Texas
    Description

    (See USGS Digital Data Series DDS-69-E) A geographic information system focusing on the Jurassic-Cretaceous Cotton Valley Group was developed for the U.S. Geological Survey's (USGS) 2002 assessment of undiscovered, technically recoverable oil and natural gas resources of the Gulf Coast Region. The USGS Energy Resources Science Center has developed map and metadata services to deliver the 2002 assessment results GIS data and services online. The Gulf Coast assessment is based on geologic elements of a total petroleum system (TPS) as described in Dyman and Condon (2005). The estimates of undiscovered oil and gas resources are within assessment units (AUs). The hydrocarbon assessment units include the assessment results as attributes within the AU polygon feature class (in geodatabase and shapefile format). Quarter-mile cells of the land surface that include single or multiple wells were created by the USGS to illustrate the degree of exploration and the type and distribution of production for each assessment unit. Other data that are available in the map documents and services include the TPS and USGS province boundaries. To easily distribute the Gulf Coast maps and GIS data, a web mapping application has been developed by the USGS, and customized ArcMap (by ESRI) projects are available for download at the Energy Resources Science Center Gulf Coast website. ArcGIS Publisher (by ESRI) was used to create a published map file (pmf) from each ArcMap document (.mxd). The basemap services being used in the GC map applications are from ArcGIS Online Services (by ESRI), and include the following layers: -- Satellite imagery -- Shaded relief -- Transportation -- States -- Counties -- Cities -- National Forests With the ESRI_StreetMap_World_2D service, detailed data, such as railroads and airports, appear as the user zooms in at larger scales. This map service shows the structural configuration on the top of the Cotton Valley Group in feet below sea level. The map was produced by calculating the difference between a datum at the land surface (either the kelly bushing elevation or the ground surface elevation) and the reported depth of the Cotton Valley Group. This map service also shows the thickness of the interval from the top of the Cotton Valley Group to the top of the Smackover Formation.

  7. o

    Level III Ecoregions

    • geohub.oregon.gov
    • data.oregon.gov
    • +3more
    Updated Jan 1, 2006
    + more versions
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    State of Oregon (2006). Level III Ecoregions [Dataset]. https://geohub.oregon.gov/datasets/oregon-geo::level-iii-ecoregions
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    Dataset updated
    Jan 1, 2006
    Dataset authored and provided by
    State of Oregon
    Area covered
    Description

    Ecoregions denote areas of general similarity in ecosystems and in the type quality, and quantity of environmental resources. The ecoregions shown here have been derived from the "Level III Ecoregions of the continental United States" GIS coverage created by the US Environmental Protection Agency. The useco polygon was converted to a shapefile in ArcToolbox using the "Feature Class To Shapefile" tool. The shapefile was reprojected from Albers Conical Equal Area to Oregon Lambert. The shapefile was clipped to the boundary of Oregon.

  8. Interstates TDA

    • geodata.floridagio.gov
    • arc-gis-hub-home-arcgishub.hub.arcgis.com
    • +4more
    Updated Jul 19, 2017
    + more versions
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    Florida Department of Transportation (2017). Interstates TDA [Dataset]. https://geodata.floridagio.gov/datasets/fdot::interstates-tda/about
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    Dataset updated
    Jul 19, 2017
    Dataset authored and provided by
    Florida Department of Transportationhttps://www.fdot.gov/
    Area covered
    Description

    The FDOT GIS Interstates feature class provides spatial information on Florida Interstate highways. The interstate and US route numbers are assigned by the Federal American Association of State Highway and Transportation Officials (AASHTO) usually following recommendations by the each state department. Both interstate and US routes are coded under the USROUTE characteristic. Interstate numbers are assigned with even numbers for west to east routes and odd numbers for routes going south to north, starting with the lowest number in the lowest part of the nation and progressing higher nationwide. US route numbers are assigned with odd numbers for north and south routes with the low number beginning in the east and progressing higher toward the west. This numbering practice is used across all states for all interstates and US routes for the public traveling purposes. This information is required for roadways functionally classified as principal, minor arterials that have US route designations, and all Active Exclusive roads that are associated with Interstate and the US route. This dataset is maintained by the Transportation Data & Analytics office (TDA). The source spatial data for this hosted feature layer was created on: 11/08/2025.For more details please review the FDOT RCI Handbook Download Data: Enter Guest as Username to download the source shapefile from here: https://ftp.fdot.gov/file/d/FTP/FDOT/co/planning/transtat/gis/shapefiles/interstates.zip

  9. a

    OGC Web Map Service (WMS):Petroleum System and Assessment of Oil and Gas,...

    • catalogue.arctic-sdi.org
    Updated May 23, 2022
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    (2022). OGC Web Map Service (WMS):Petroleum System and Assessment of Oil and Gas, Travis Peak-Hosston Formations, East Texas Basin and Louisiana-Mississippi Salt Basins Provinces, Texas, Louisiana, Mississippi, Alabama, and Florida [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/resources/datasets/c8997b22-359e-4046-a988-f67ee73f034a
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    Dataset updated
    May 23, 2022
    Area covered
    Travis Peak, Texas
    Description

    (See USGS Digital Data Series DDS-69-E) A geographic information system focusing on the Cretaceous Travis Peak and Hosston Formations was developed for the U.S. Geological Survey's (USGS) 2002 assessment of undiscovered, technically recoverable oil and natural gas resources of the Gulf Coast Region. The USGS Energy Resources Science Center has developed map and metadata services to deliver the 2002 assessment results GIS data and services online. The Gulf Coast assessment is based on geologic elements of a total petroleum system (TPS) as described in Dyman and Condon (2005). The estimates of undiscovered oil and gas resources are within assessment units (AUs). The hydrocarbon assessment units include the assessment results as attributes within the AU polygon feature class (in geodatabase and shapefile format). Quarter-mile cells of the land surface that include single or multiple wells were created by the USGS to illustrate the degree of exploration and the type and distribution of production for each assessment unit. Other data that are available in the map documents and services include the TPS and USGS province boundaries. To easily distribute the Gulf Coast maps and GIS data, a web mapping application has been developed by the USGS, and customized ArcMap (by ESRI) projects are available for download at the Energy Resources Science Center Gulf Coast website. ArcGIS Publisher (by ESRI) was used to create a published map file (pmf) from each ArcMap document (.mxd). The basemap services being used in the GC map applications are from ArcGIS Online Services (by ESRI), and include the following layers: -- Satellite imagery -- Shaded relief -- Transportation -- States -- Counties -- Cities -- National Forests With the ESRI_StreetMap_World_2D service, detailed data, such as railroads and airports, appear as the user zooms in at larger scales. This map service shows the structural configuration of the top of the Travis Peak or Hosston Formations in feet below sea level. The map was produced by calculating the difference between a datum at the land surface (either the Kelly bushing elevation or the ground surface elevation) and the reported depth of the Travis Peak or Hosston. This map service also shows the thickness of the interval from the top of the Travis Peak or Hosston Formations to the top of the Cotton Valley Group.

  10. d

    Data and Results for GIS-Based Identification of Areas that have Resource...

    • catalog.data.gov
    • data.usgs.gov
    • +2more
    Updated Nov 13, 2025
    + more versions
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    U.S. Geological Survey (2025). Data and Results for GIS-Based Identification of Areas that have Resource Potential for Lode Gold in Alaska [Dataset]. https://catalog.data.gov/dataset/data-and-results-for-gis-based-identification-of-areas-that-have-resource-potential-for-lo
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    Dataset updated
    Nov 13, 2025
    Dataset provided by
    U.S. Geological Survey
    Description

    This data release contains the analytical results and evaluated source data files of geospatial analyses for identifying areas in Alaska that may be prospective for different types of lode gold deposits, including orogenic, reduced-intrusion-related, epithermal, and gold-bearing porphyry. The spatial analysis is based on queries of statewide source datasets of aeromagnetic surveys, Alaska Geochemical Database (AGDB3), Alaska Resource Data File (ARDF), and Alaska Geologic Map (SIM3340) within areas defined by 12-digit HUCs (subwatersheds) from the National Watershed Boundary dataset. The packages of files available for download are: 1. LodeGold_Results_gdb.zip - The analytical results in geodatabase polygon feature classes which contain the scores for each source dataset layer query, the accumulative score, and a designation for high, medium, or low potential and high, medium, or low certainty for a deposit type within the HUC. The data is described by FGDC metadata. An mxd file, and cartographic feature classes are provided for display of the results in ArcMap. An included README file describes the complete contents of the zip file. 2. LodeGold_Results_shape.zip - Copies of the results from the geodatabase are also provided in shapefile and CSV formats. The included README file describes the complete contents of the zip file. 3. LodeGold_SourceData_gdb.zip - The source datasets in geodatabase and geotiff format. Data layers include aeromagnetic surveys, AGDB3, ARDF, lithology from SIM3340, and HUC subwatersheds. The data is described by FGDC metadata. An mxd file and cartographic feature classes are provided for display of the source data in ArcMap. Also included are the python scripts used to perform the analyses. Users may modify the scripts to design their own analyses. The included README files describe the complete contents of the zip file and explain the usage of the scripts. 4. LodeGold_SourceData_shape.zip - Copies of the geodatabase source dataset derivatives from ARDF and lithology from SIM3340 created for this analysis are also provided in shapefile and CSV formats. The included README file describes the complete contents of the zip file.

  11. e

    GIS Shapefile - Libraries, Baltimore City, Shapefile

    • portal.edirepository.org
    zip
    Updated Dec 31, 2009
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    Jarlath O'Neil-Dunne; Morgan Grove (2009). GIS Shapefile - Libraries, Baltimore City, Shapefile [Dataset]. http://doi.org/10.6073/pasta/fdaac2d98c7df74c60067c52470151f4
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    zip(8 kilobyte)Available download formats
    Dataset updated
    Dec 31, 2009
    Dataset provided by
    EDI
    Authors
    Jarlath O'Neil-Dunne; Morgan Grove
    Time period covered
    Jan 1, 2004 - Nov 17, 2011
    Area covered
    Description

    libraries_BACI

       File Geodatabase Feature Class
    
    
       Thumbnail Not Available
    
       Tags
    
       BES, Library
    
    
    
    
       Summary
    
    
       Socioeconomic analysis.
    
    
       Description
    
    
       Location of Baltimore City libraries. This dataset was obtained from BNIA; no metadata was provided. A limited assessment comparing this dataset to IKONOS imagery acquired in 2001 indicates that the point locations have most likely been geocoded and thus are in the vicinity of, but generally not at the precise location of the facility.
    
    
       Credits
    
    
       BNIA
    
    
       Use limitations
    
    
       BES research only.
    
    
       Extent
    
    
    
       West -76.700693  East -76.536224 
    
       North 39.360509  South 39.236629 
    
    
    
    
       Scale Range
    
       There is no scale range for this item.
    
  12. a

    OGC Web Map Service (WMS): Petroleum Systems and Geologic Assessment of...

    • catalogue.arctic-sdi.org
    Updated May 23, 2022
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    (2022). OGC Web Map Service (WMS): Petroleum Systems and Geologic Assessment of Undiscovered Oil and Gas, Taylor and Navarro Groups, Western Gulf Province, Texas [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/search?keyword=Gulf%20Coast,%20Impacts%20of%20Energy%20Production,%20Sedimentary%20Basin,%20Oil%20and%20Natural%20Gas,%20Energy%20Resources,%20Earth%20Science,%20Natural%20Resources,%20U.S.%20Geological%20Survey,%20USGS,%20Geology,%20Natural%20Gas,%20Petroleum,%20Oil,%20Gas,%20Oil%20and%20Gas%20Exploration,%20Oil%20and%20Gas%20Production
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    Dataset updated
    May 23, 2022
    Description

    (See USGS Digital Data Series DDS-69-H) A geographic information system focusing on the Upper Cretaceous Taylor and Navarro Groups was developed for the U.S. Geological Survey's (USGS) 2003 assessment of undiscovered, technically recoverable oil and natural gas resources of the Gulf Coast Region. The USGS Energy Resources Science Center has developed map and metadata services to deliver the 2003 assessment results GIS data and services online. The Gulf Coast assessment is based on geologic elements of a total petroleum system (TPS) as described in Condon and Dyman (2005). The estimates of undiscovered oil and gas resources are within assessment units (AUs). The hydrocarbon assessment units include the assessment results as attributes within the AU polygon feature class (in geodatabase and shapefile format). Quarter-mile cells of the land surface that include single or multiple wells were created by the USGS to illustrate the degree of exploration and the type and distribution of production for each assessment unit. Other data that are available in the map documents and services include the TPS and USGS province boundaries. To easily distribute the Gulf Coast maps and GIS data, a web mapping application has been developed by the USGS, and customized ArcMap (by ESRI) projects are available for download at the Energy Resources Science Center Gulf Coast website. ArcGIS Publisher (by ESRI) was used to create a published map file (pmf) from each ArcMap document (.mxd). The basemap services being used in the GC map applications are from ArcGIS Online Services (by ESRI), and include the following layers: -- Satellite imagery -- Shaded relief -- Transportation -- States -- Counties -- Cities -- National Forests With the ESRI_StreetMap_World_2D service, detailed data, such as railroads and airports, appear as the user zooms in at larger scales.

  13. d

    Data from: Data and Results for GIS-Based Identification of Areas that have...

    • catalog.data.gov
    Updated Oct 8, 2025
    + more versions
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    U.S. Geological Survey (2025). Data and Results for GIS-Based Identification of Areas that have Resource Potential for Sediment-Hosted Pb-Zn Deposits in Alaska [Dataset]. https://catalog.data.gov/dataset/data-and-results-for-gis-based-identification-of-areas-that-have-resource-potential-for-se
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    Dataset updated
    Oct 8, 2025
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Description

    This data release contains the analytical results and the evaluated source data files of a geospatial analysis for identifying areas in Alaska that may have potential for sediment-hosted Pb-Zn (lead-zinc) deposits. The spatial analysis is based on queries of statewide source datasets Alaska Geochemical Database (AGDB3), Alaska Resource Data File (ARDF), and Alaska Geologic Map (SIM3340) within areas defined by 12-digit HUCs (subwatersheds) from the National Watershed Boundary dataset. The packages of files available for download are: 1. "SedPbZn_Results_gdb.zip". The analytical results (.gbd - geodatabase format) for sediment-hosted Pb-Zn deposits are in a polygon feature class which contains the points scored for each source data layer query, the accumulative score, and a designation for high, medium, or low potential and high, medium, or low certainty for sediment-hosted Pb-Zn deposits for each HUC. An mxd file, layer file, and cartographic feature classes are provided for display of the results in ArcMap. 2. "SedPbZn_Results_kmz.zip". The analytical results (.kmz - keyhole markup language format) for sediment-hosted Pb-Zn deposits are shown as polygons containing the points scored for each source data layer query, the accumulative score, and designation of high, medium, or low potential and high, medium, or low certainty for sediment-hosted Pb-Zn deposits for each HUC. This file may be viewed in an Earth viewer, such as Google Earth. 3. "SedPbZn_Results_shape.zip". The analytical results (.shp - Esri shapefile format) for sediment-hosted Pb-Zn deposits are in a polygon feature class which contains the points scored for each source data layer query, the accumulative score, and designation for high, medium, or low potential and high, medium, or low certainty for sediment-hosted Pb-Zn deposits for each HUC. The results are also provided as a CSV file. 4. "SedPbZn_SourceData_gdb.zip". Source data (.gbd - geodatabase format); layers include AGDB3, ARDF, lithology from SIM3340, and HUC subwatersheds. An mxd file and cartographic feature classes are provided for display of the source data in ArcMap. Also included are two python scripts 1) to score the ARDF records based on the presence of certain keywords, and 2) to evaluate the ARDF, AGDB3, and lithology layers for the potential for sediment-hosted Pb-Zn deposits within subwatershed polygons. Users may modify the scripts to design their own analyses. 5. "SedPbZn_SourceData_shape.zip". Source data (.shp - Esri shapefile and .csv tabular formats); layers include ARDF and lithology from SIM3340, and HUC subwatersheds. The ARDF keyword tables available in the geodatabase package are presented here as CSV files. 6. "SedPbZn_Appendices.zip". Appendices 2-4 (.csv and .xlsx tabular formats) of the associated USGS Open File Report: OFR 2020-1147; https://doi.org/10.3133/ofr20201147

  14. GIS Shapefile - Health Organizations, Baltimore City, Shapefile

    • search.datacite.org
    • portal.edirepository.org
    Updated 2018
    + more versions
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove (2018). GIS Shapefile - Health Organizations, Baltimore City, Shapefile [Dataset]. http://doi.org/10.6073/pasta/a33f4214c5438674896c00c8236ce147
    Explore at:
    Dataset updated
    2018
    Dataset provided by
    DataCitehttps://www.datacite.org/
    Environmental Data Initiative
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove
    Description

    Health_Organizations_BACI

       File Geodatabase Feature Class
    
    
       Thumbnail Not Available
    
       Tags
    
       BES, Health Organizations
    
    
    
    
       Summary
    
    
       Socioeconomic analysis.
    
    
       Description
    
    
       Location of Baltimore City health organizations. This dataset was obtained from BNIA; no metadata was provided. A limited assessment comparing this dataset to IKONOS imagery acquired in 2001 indicates that the point locations have most likely been geocoded and thus are in the vicinity of, but generally not at the precise location of the facility.
    
    
       Credits
    
    
       BNIA
    
    
       Use limitations
    
    
       BES research only.
    
    
       Extent
    
    
    
       West -76.687816  East -76.556835 
    
       North 39.354983  South 39.273377 
    
    
    
    
       Scale Range
    
       There is no scale range for this item.
    
  15. GIS Shapefile - Newcomer Hotspots, Baltimore City, Shapefile

    • search.datacite.org
    • search.dataone.org
    • +1more
    Updated 2018
    + more versions
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove (2018). GIS Shapefile - Newcomer Hotspots, Baltimore City, Shapefile [Dataset]. http://doi.org/10.6073/pasta/d79cf1b38424ca0d76b86fa774c1a57a
    Explore at:
    Dataset updated
    2018
    Dataset provided by
    DataCitehttps://www.datacite.org/
    Environmental Data Initiative
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove
    Description

    Newcomer_Hotspots_BACI

       File Geodatabase Feature Class
    
    
       Thumbnail Not Available
    
       Tags
    
       BES, Newcomers, Hotspots
    
    
    
    
       Summary
    
    
       BES analysis.
    
    
       Description
    
    
       Baltimore City hotspots for newcomers to the area.
    
    
       Credits
    
    
       BNIA
    
    
       Use limitations
    
    
       BES research only.
    
    
       Extent
    
    
    
       West -76.681749  East -76.561269 
    
       North 39.356084  South 39.236417 
    
    
    
    
       Scale Range
    
       There is no scale range for this item.
    
  16. GIS Shapefile - Land Use by Parcel, Baltimore City, Shapefile

    • search.datacite.org
    • search.dataone.org
    • +1more
    Updated 2018
    + more versions
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove (2018). GIS Shapefile - Land Use by Parcel, Baltimore City, Shapefile [Dataset]. http://doi.org/10.6073/pasta/89cb094e6cfeef283a3a86788ec7f85a
    Explore at:
    Dataset updated
    2018
    Dataset provided by
    DataCitehttps://www.datacite.org/
    Environmental Data Initiative
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove
    Description

    Parcels_PROW_LU_2003_BACI

       File Geodatabase Feature Class
    
    
       Thumbnail Not Available
    
       Tags
    
       BES, Parcel, Land Use, Urban, Land
    
    
    
    
       Summary
    
    
       BES research
    
    
       Description
    
    
       Parcel-based land use (LU) and public rights-of-way (PROW), for Baltimore City. Land use (LU) codes were obtained from the 2003 MD Property View A&Tdatabase.
    
    
       Credits
    
    
       Jarlath O'Neil-Dunne, UVM Spatial Analysis Lab
    
    
       Use limitations
    
    
       Approved BES research only
    
    
       Extent
    
    
    
       West -76.713449  East -76.525885 
    
       North 39.374474  South 39.195049 
    
    
    
    
       Scale Range
    
       There is no scale range for this item.
    
  17. c

    i07 PreSGMA GroundWaterManagementPlans

    • gis.data.cnra.ca.gov
    • data.ca.gov
    • +9more
    Updated Feb 7, 2023
    + more versions
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    Carlos.Lewis@water.ca.gov_DWR (2023). i07 PreSGMA GroundWaterManagementPlans [Dataset]. https://gis.data.cnra.ca.gov/items/7cdf65e496e24b43af4252d9bf9be824
    Explore at:
    Dataset updated
    Feb 7, 2023
    Dataset authored and provided by
    Carlos.Lewis@water.ca.gov_DWR
    Area covered
    Description

    This polygon feature class is a data set compiled by DWR employees in 2013 and represents the statewide Groundwater Management Plan (Plan) boundaries predating the Sustainable Groundwater Management Act (SGMA) requirements. Each polygon represents the area in which a Plan is to be implemented. The boundaries were provided to DWR by the affiliated public agency and compiled into a single statewide data set. Spatial plan boundaries were provided by agencies to DWR either via shapefiles or PDFs. PDFs were georeferenced and turned into GIS layers by DWR employees. This feature class is for legacy purposes only and will not be changed nor updated. It needs to be memorialized for spatial coverage of Groundwater Management Plans prior to SGMA and because SGMA only requires medium and high priority basins to have a Groundwater Sustainability Plan. The Plans outlined in this shapefile by medium and high priority basins are in effect until SGMA goes into effect. Some low and very low priority basins will likely use the existing plans to get funding for future basin management (since it is only voluntary for them to provide a Plan under SGMA, but they already have one in place). The data set is considered complete because of its legacy status. However, anyone using the data set will notice boundary inconsistencies, agency plan overlaps, mismatches, and other topology errors. The data set is based on boundary estimations and in the cases of medium and high priority basins will be outdated with in implementation of SGMA.The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.1, dated September 11, 2019. This data set was not produced by DWR. Data were originally developed and supplied by each individual plan agency and compiled by DWR. DWR makes no warranties or guarantees — either expressed or implied— as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to GIS@water.ca.gov.

  18. GIS Shapefile - Religious Organization Parcels, Baltimore City, Shapefile

    • search.datacite.org
    • portal.edirepository.org
    • +1more
    Updated 2018
    + more versions
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove (2018). GIS Shapefile - Religious Organization Parcels, Baltimore City, Shapefile [Dataset]. http://doi.org/10.6073/pasta/99f0a9a07e456680bf76997cd42b5e47
    Explore at:
    Dataset updated
    2018
    Dataset provided by
    DataCitehttps://www.datacite.org/
    Environmental Data Initiative
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove
    Description

    religious_orgs_BACI

       File Geodatabase Feature Class
    
    
       Thumbnail Not Available
    
       Tags
    
       BES, Religous Organizations
    
    
    
    
       Summary
    
    
       BES analysis
    
    
       Description
    
    
       Religious Organization parcels in Baltimore City.
    
    
       Credits
    
    
       BNIA
    
    
       Use limitations
    
    
       BES research only.
    
    
       Extent
    
    
    
       West -76.713134  East -76.527132 
    
       North 39.374461  South 39.220870 
    
    
    
    
       Scale Range
    
       There is no scale range for this item.
    
  19. e

    GIS Shapefile - Brownfields, Baltimore City, Shapefile

    • portal.edirepository.org
    • search.dataone.org
    zip
    Updated Dec 31, 2009
    + more versions
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    Jarlath O'Neil-Dunne (2009). GIS Shapefile - Brownfields, Baltimore City, Shapefile [Dataset]. http://doi.org/10.6073/pasta/7fa226bd972513581f5ec578fa0b2bb6
    Explore at:
    zip(51 kilobyte)Available download formats
    Dataset updated
    Dec 31, 2009
    Dataset provided by
    EDI
    Authors
    Jarlath O'Neil-Dunne
    Time period covered
    Jan 1, 2004 - Nov 17, 2011
    Area covered
    Description

    Brownfields_BACI

       File Geodatabase Feature Class
    
    
       Thumbnail Not Available
    
       Tags
    
       Biophysical Resources, Air, Land, Water, BES, Brownfields, Pollution
    
    
    
    
       Summary
    
    
       BES Analysis
    
    
       Description
    
    
       Brownfield parcels in Baltimore City. No metadata was provided with this dataset; the UVM Spatial Analysis Lab has attempted to evaluate this dataset and generate metadata. This dataset appears to have a high degree of positional accuracy based on comparisons with high resolution imagery.
    
    
       Credits
    
    
       Maryland Department of the Environment
    
    
       Use limitations
    
    
       BES research only.
    
    
       Extent
    
    
    
       West -76.661468  East -76.530941 
    
       North 39.334224  South 39.235433 
    
    
    
    
       Scale Range
    
       There is no scale range for this item.
    
  20. GIS Shapefile - Landmarks, Baltimore City, Shapefile

    • search.datacite.org
    • portal.edirepository.org
    • +1more
    Updated 2018
    + more versions
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    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove (2018). GIS Shapefile - Landmarks, Baltimore City, Shapefile [Dataset]. http://doi.org/10.6073/pasta/3bf1b9ac39b7a2b80d756e3d4896d706
    Explore at:
    Dataset updated
    2018
    Dataset provided by
    DataCitehttps://www.datacite.org/
    Environmental Data Initiative
    Authors
    Cary Institute Of Ecosystem Studies; Jarlath O'Neil-Dunne; Morgan Grove
    Description

    landmark_BACI

       File Geodatabase Feature Class
    
    
       Thumbnail Not Available
    
       Tags
    
       BES, Landmarks
    
    
    
    
       Summary
    
    
       Socioeconomic analysis.
    
    
       Description
    
    
       Baltimore City Landmarks.
    
    
       Credits
    
    
       BNIA
    
    
       Use limitations
    
    
       BES research only.
    
    
       Extent
    
    
    
       West -76.678418  East -76.535599 
    
       North 39.359323  South 39.245599 
    
    
    
    
       Scale Range
    
       There is no scale range for this item.
    
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Town of Apex, North Carolina (2025). Service Locations [Dataset]. https://arc-gis-hub-home-arcgishub.hub.arcgis.com/maps/apexnc::service-locations

Service Locations

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Dataset updated
Jan 5, 2025
Dataset authored and provided by
Town of Apex, North Carolina
Area covered
Description

The construction of this data model was adapted from the Telvent Miner & Miner ArcFM MultiSpeak data model to provide interface functionality with Milsoft Utility Solutions WindMil engineering analysis program. Database adaptations, GPS data collection, and all subsequent GIS processes were performed by Southern Geospatial Services for the Town of Apex Electric Utilities Division in accordance to the agreement set forth in the document "Town of Apex Electric Utilities GIS/GPS Project Proposal" dated March 10, 2008. Southern Geospatial Services disclaims all warranties with respect to data contained herein. Questions regarding data quality and accuracy should be directed to persons knowledgeable with the forementioned agreement.The data in this GIS with creation dates between March of 2008 and April of 2024 were generated by Southern Geospatial Services, PLLC (SGS). The original inventory was performed under the above detailed agreement with the Town of Apex (TOA). Following the original inventory, SGS performed maintenance projects to incorporate infrastructure expansion and modification into the GIS via annual service agreements with TOA. These maintenances continued through April of 2024.At the request of TOA, TOA initiated in house maintenance of the GIS following delivery of the final SGS maintenance project in April of 2024. GIS data created or modified after April of 2024 are not the product of SGS.With respect to SGS generated GIS data that are point features:GPS data collected after January 1, 2013 were surveyed using mapping grade or survey grade GPS equipment with real time differential correction undertaken via the NC Geodetic Surveys Real Time Network (VRS). GPS data collected prior to January 1, 2013 were surveyed using mapping grade GPS equipment without the use of VRS, with differential correction performed via post processing.With respect to SGS generated GIS data that are line features:Line data in the GIS for overhead conductors were digitized as straight lines between surveyed poles. Line data in the GIS for underground conductors were digitized between surveyed at grade electric utility equipment. The configurations and positions of the underground conductors are based on TOA provided plans. The underground conductors are diagrammatic and cannot be relied upon for the determination of the actual physical locations of underground conductors in the field.The Service Locations feature class was created by Southern Geospatial Services (SGS) from a shapefile of customer service locations generated by dataVoice International (DV) as part of their agreement with the Town of Apex (TOA) regarding the development and implemention of an Outage Management System (OMS).Point features in this feature class represent service locations (consumers of TOA electric services) by uniquely identifying the features with the same unique identifier as generated for a given service location in the TOA Customer Information System (CIS). This is also the mechanism by which the features are tied to the OMS. Features are physically located in the GIS based on CIS address in comparison to address information found in Wake County GIS property data (parcel data). Features are tied to the GIS electric connectivity model by identifying the parent feature (Upline Element) as the transformer that feeds a given service location.SGS was provided a shapefile of 17992 features from DV. Error potentially exists in this DV generated data for the service location features in terms of their assigned physical location, phase, and parent element.Regarding the physical location of the features, SGS had no part in physically locating the 17992 features as provided by DV and cannot ascertain the accuracy of the locations of the features without undertaking an analysis designed to verify or correct for error if it exists. SGS constructed the feature class and loaded the shapefile objects into the feature class and thus the features exist in the DV derived location. SGS understands that DV situated the features based on the address as found in the CIS. No features were verified as to the accuracy of their physical location when the data were originally loaded. It is the assumption of SGS that the locations of the vast majority of the service location features as provided by DV are in fact correct.SGS understands that as a general rule that DV situated residential features (individually or grouped) in the center of a parcel. SGS understands that for areas where multiple features may exist in a given parcel (such as commercial properties and mobile home parks) that DV situated features as either grouped in the center of the parcel or situated over buildings, structures, or other features identifiable in air photos. It appears that some features are also grouped in roads or other non addressed locations, likely near areas where they should physically be located, but that these features were not located in a final manner and are either grouped or strung out in a row in the general area of where DV may have expected they should exist.Regarding the parent and phase of the features, the potential for error is due to the "first order approximation" protocol employed by DV for assigning the attributes. With the features located as detailed above, SGS understands that DV identified the transformer closest to the service location (straight line distance) as its parent. Phase was assigned to the service location feature based on the phase of the parent transformer. SGS expects that this protocol correctly assigned parent (and phase) to a significant portion of the features, however this protocol will also obviously incorretly assign parent in many instances.To accurately identify parent for all 17992 service locations would require a significant GIS and field based project. SGS is willing to undertake a project of this magnitude at the discretion of TOA. In the meantime, SGS is maintaining (editing and adding to) this feature class as part of the ongoing GIS maintenance agreement that is in place between TOA and SGS. In lieu of a project designed to quality assess and correct for the data provided by DV, SGS will verify the locations of the features at the request of TOA via comparison of the unique identifier for a service location to the CIS address and Wake County parcel data address as issues arise with the OMS if SGS is directed to focus on select areas for verification by TOA. Additionally, as SGS adds features to this feature class, if error related to the phase and parent of an adjacent feature is uncovered during a maintenance, it will be corrected for as part of that maintenance.With respect to the additon of features moving forward, TOA will provide SGS with an export of CIS records for each SGS maintenance, SGS will tie new accounts to a physical location based on address, SGS will create a feature for the CIS account record in this feature class at the center of a parcel for a residential address or at the center of a parcel or over the correct (or approximately correct) location as determined via air photos or via TOA plans for commercial or other relevant areas, SGS will identify the parent of the service location as the actual transformer that feeds the service location, and SGS will identify the phase of the service address as the phase of it's parent.Service locations with an ObjectID of 1 through 17992 were originally physically located and attributed by DV.Service locations with an ObjectID of 17993 or higher were originally physically located and attributed by SGS.DV originated data are provided the Creation User attribute of DV, however if SGS has edited or verified any aspect of the feature, this attribute will be changed to SGS and a comment related to the edits will be provided in the SGS Edits Comments data field. SGS originated features will be provided the Creation User attribute of SGS. Reference the SGS Edits Comments attribute field Metadata for further information.

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