100+ datasets found
  1. Geospatial data for the Vegetation Mapping Inventory Project of Bryce Canyon...

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Jun 5, 2024
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    National Park Service (2024). Geospatial data for the Vegetation Mapping Inventory Project of Bryce Canyon National Park [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-bryce-canyon-national-park
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    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. The mapping component of the BRCA project used a combination of methods to interpret and delineate vegetation and land use polygons. The USGS applied an electronic segmentation method (e-Cognition software) to create preliminary linework on features with high-contrast photo-signatures. Using the preliminary linework as a baseline starting point, the primary photointerpreter drew polygons directly on screen through heads-up digitizing using ArcGIS editing tools. Additionally, trained photointerpreters assisting the primary photointerpreter drew polygons on Mylar overlays covering 1m resolution, 1:12,000-scale, 9 x 9-inch true-color aerial photographs. This process enabled the photointerpreters to view the landscape in stereo in order to identify finer details. The linework drawn on Mylar overlays was then transferred into digital media by heads-up digitizing using ArcGIS software. The park and environs were interpreted and mapped to the same level of detail.

  2. w

    Light Rail and Subway Lines, This Layer was created in ArcView through...

    • data.wu.ac.at
    Updated Aug 19, 2017
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    NSGIC Regional | GIS Inventory (2017). Light Rail and Subway Lines, This Layer was created in ArcView through "heads up" digitizing, using MARTA's digital road network as a basemap., Published in 2000, 1:63360 (1in=1mile) scale, Atlanta Regional Commission. [Dataset]. https://data.wu.ac.at/schema/data_gov/ZTc5YTExODEtZWVmZi00MTI4LWJkOTEtNzY2NDUwM2FlNDQ4
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    Dataset updated
    Aug 19, 2017
    Dataset provided by
    NSGIC Regional | GIS Inventory
    Area covered
    35b8fcb999781d662e80564e003a3a278fd7ca09
    Description

    Light Rail and Subway Lines dataset current as of 2000. This Layer was created in ArcView through "heads up" digitizing, using MARTA's digital road network as a basemap..

  3. a

    Data from: Miscellaneous Structures

    • data-desmoines.hub.arcgis.com
    Updated Jun 23, 2025
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    City of Des Moines (2025). Miscellaneous Structures [Dataset]. https://data-desmoines.hub.arcgis.com/datasets/miscellaneous-structures
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    City of Des Moines
    Area covered
    Description

    Planimetric Miscellaneous Structure features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintenance of the data includes heads-up digitizing using the orthophoto images.

  4. g

    Imagery data for the Vegetation Mapping Inventory Project of Homestead...

    • gimi9.com
    Updated Jul 7, 2011
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    (2011). Imagery data for the Vegetation Mapping Inventory Project of Homestead National Monument | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_imagery-data-for-the-vegetation-mapping-inventory-project-of-homestead-national-monument/
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    Dataset updated
    Jul 7, 2011
    Description

    This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. The mapping component was initiated by photo interpretation and digitization of 3-band 2001 color infrared (CIR) IKONOS imagery for the vegetation and land use classes determined through the field visit and expert knowledge of project team members. The heads-up digitization was performed at a display scale of 1:1000 to 1:1500. The digitization, evaluation, and modifications were iterative and collaborative processes involving the GIS analysts and the rest of the team. Preliminary maps were checked, corrected, and rechecked for boundary delineations. Final edits were made using the 2009 NAIP imagery, which captured the changes made along the eastern end of the property with the construction of the visitor’s center.

  5. d

    Bridges

    • data.dsm.city
    • data-desmoines.hub.arcgis.com
    Updated Jun 18, 2025
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    City of Des Moines (2025). Bridges [Dataset]. https://data.dsm.city/datasets/bridges
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    Dataset updated
    Jun 18, 2025
    Dataset authored and provided by
    City of Des Moines
    Area covered
    Description

    Planimetric Bridge features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintainenance of the data includes heads-up digitizing using the orthophoto images.

  6. Geospatial data for the Vegetation Mapping Inventory Project of Vicksburg...

    • catalog.data.gov
    • data.amerigeoss.org
    Updated Jun 5, 2024
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    National Park Service (2024). Geospatial data for the Vegetation Mapping Inventory Project of Vicksburg National Military Park [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-vicksburg-national-militar
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Vicksburg
    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 used ERDAS Imagine ® Professional 9.2, ENVI ® 4.5, and ArcGIS ® 9.3 with Arc Workstation to develop the vegetation spatial database. Existing GIS datasets that we used to provide mapping information include a NPS park boundary shapefile for VICK (including a 100 meter buffer boundary around the Louisiana Circle, South Fort, and Navy Circle satellite units), a land cover shapefile created by the NWRC (Rangoonwala et al. 2007), and the National Elevation Dataset (NED) (used as the source of the 10-meter elevation model and derived streams, slope, and hillshade). To make the entire spatial data set consistent with NPSVI policies to map only to park boundaries, we clipped the vegetation in and around the previously buffered areas around the Louisiana Circle, South Fort, and Navy Circle satellite unit NPS boundaries. We also added to the spatial database vegetation polygons for the previously omitted Grant’s Canal satellite unit by heads-up digitizing this area from a National Agricultural Information Program (NAIP) image.

  7. D

    Land Use 2000

    • catalog.dvrpc.org
    api, geojson, html +1
    Updated May 23, 2025
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    DVRPC (2025). Land Use 2000 [Dataset]. https://catalog.dvrpc.org/dataset/land-use-2000
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    geojson, html, xml, apiAvailable download formats
    Dataset updated
    May 23, 2025
    Dataset provided by
    Delaware Valley Regional Planning Commissionhttps://www.dvrpc.org/
    Authors
    DVRPC
    Description

    Every five years, since 1990, the Delaware Valley Regional Planning Commission has produced a GIS Land Use layer for its 9-county region. In 2000, digital orthophotography was flown by DVRPC. Utilizing this orthophotography, all Land Use annotation and digitizing was performed on-screen, or "heads-up," a first at DVRPC. Digitizing was done using ESRI ArcGIS 8 software at a 1:2400 (1 inch = 200 feet) scale.

  8. Imagery data for the Vegetation Mapping Inventory Project of Tallgrass...

    • catalog.data.gov
    Updated Jun 5, 2024
    + more versions
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    National Park Service (2024). Imagery data for the Vegetation Mapping Inventory Project of Tallgrass Prairie National Preserve [Dataset]. https://catalog.data.gov/dataset/imagery-data-for-the-vegetation-mapping-inventory-project-of-tallgrass-prairie-national-pr
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Description

    This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. The mapping component was initiated by photo interpretation and digitization of 4-band 2005 IKONOS imagery for the vegetation and land use classes determined through the field visit and expert knowledge of project team members. The heads-up digitization was performed at a display scale of 1:1500 to 1:2000. The digitization, evaluation, and modifications comprised an iterative and collaborative process involving the GIS analysts and the rest of the team. Preliminary maps were checked, corrected, and rechecked for boundary delineations. These image sources included 2003, 2004, 2005, 2006 (3-band, Red, Green, Blue), and 2008 (4-band, Red, Green, Blue, Near Infrared) USDA FSA NAIP, 2002 and 1991 USGS DOQQs, and 1938 panchromatic imagery. Two additional 4-band (Red, Green, Blue, Near Infrared) IKONOS scenes were acquired in June and September of 2008 specifically for this project. These IKONOS image acquisitions targeted specific phenological windows that were generally not covered by other imagery.

  9. d

    Driveway Boundary

    • data.dsm.city
    • data-desmoines.hub.arcgis.com
    Updated Jun 20, 2025
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    City of Des Moines (2025). Driveway Boundary [Dataset]. https://data.dsm.city/maps/desmoines::driveway-boundary
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    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    City of Des Moines
    Area covered
    Description

    Planimetric Driveway features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintenance of the data includes heads-up digitizing using the orthophoto images.

  10. a

    Building Footprints

    • data-desmoines.hub.arcgis.com
    • data.dsm.city
    Updated Jun 3, 2025
    + more versions
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    City of Des Moines (2025). Building Footprints [Dataset]. https://data-desmoines.hub.arcgis.com/datasets/building-footprints-1
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    Dataset updated
    Jun 3, 2025
    Dataset authored and provided by
    City of Des Moines
    Area covered
    Description

    Planimetric Building Footprint features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintenance of the data includes heads-up digitizing using the orthophoto images.

  11. a

    Bridges

    • data-desmoines.hub.arcgis.com
    Updated Aug 2, 2021
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    City of Des Moines (2021). Bridges [Dataset]. https://data-desmoines.hub.arcgis.com/datasets/bridges-1
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    Dataset updated
    Aug 2, 2021
    Dataset authored and provided by
    City of Des Moines
    Area covered
    Description

    Planimetric Bridge features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintenance of the data includes heads-up digitizing using the orthophoto images.

  12. c

    Vegetation Public

    • gisdata.countyofnapa.org
    • hub.arcgis.com
    Updated Apr 30, 2019
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    Napa County GIS | ArcGIS Online (2019). Vegetation Public [Dataset]. https://gisdata.countyofnapa.org/datasets/napacounty::vegetation-public/about
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    Dataset updated
    Apr 30, 2019
    Dataset authored and provided by
    Napa County GIS | ArcGIS Online
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    Description

    Napa County has used a 2004 edition vegetation map produced using the Manual of California Vegetation classification system (Thorne et al. 2004) as one of the input layers for land use decision and policy. The county decided to update the map because of its utility. A University of California, Davis (UCD) group was engaged to produce the map. The earlier map used black and white digital orthophoto quadrangles from 1993, with a pixel resolution of 3 meters. This image was delineated using a heads up digitization technique produced by ASI (Aerial Services Incorporated). The resulting polygons were the provided vegetation and landcover attributes following the classification system used by California State Department of Fish and Wildlife mappers in the Manual of California Vegetation. That effort included a brief field campaign in which surveyors drove accessible roads and verified or corrected the dominant vegetation of polygons adjacent to roadways or visible using binoculars. There were no field relevé or rapid assessment plots conducted. This update version uses a 2016 edition of 1 meter color aerial imagery taken by the National Agriculture Imagery Program (NAIP) as the base imagery. In consultation with the county we decided to use similar methods to the previous mapping effort, in order to preserve the capacity to assess change in the county over time. This meant forgoing recent data and innovations in remote sensing such as the use LiDAR and Ecognition’s segmentation of imagery to delineate stands, which have been recently used in a concurrent project mapping of Sonoma County. The use of such technologies would have made it more difficult to track changes in landcover, because differences between publication dates would not be definitively attributable to either actual land cover change or to change in methodology. The overall cost of updating the map in the way was approximately 20% of the cost of the Sonoma vegetation mapping program.Therefore, we started with the original map, and on-screen inspections of the 2004 polygons to determine if change had occurred. If so, the boundaries and attributes were modified in this new edition of the map. We also used the time series of imagery available on Google Earth, to further inspect many edited polygons. While funding was not available to do field assessments, we incorporated field expertise and other map data from four projects that overlap with parts of Napa Count: the Angwin Experimental Forest; a 2014 vegetation map of the Knoxville area; agricultural rock piles were identified by Amber Manfree; and parts of a Sonoma Vegetation Map that used 2013 imagery.The Angwin Experimental Forest was mapped by Peter Lecourt from Pacific Union College. He identified several polygons of redwoods in what are potentially the eastern-most extent of that species. We reviewed those polygons with him and incorporated some of the data from his area into this map.The 2014 Knoxville Vegetation map was developed by California Department of Fish and Wildlife. It was made public in February of 2019, close to the end of this project. We reviewed the map, which covers part of the northeast portion of Napa County. We incorporated polygons and vegetation types for 18 vegetation types including the rare ones, we reviewed and incorporated some data for another 6 types, and we noted in comments the presence of another 5 types. There is a separate report specifically addressing the incorporation of this map to our map.Dr Amber Manfree has been conducting research on fire return intervals for parts of Napa County. In her research she identified that large piles of rocks are created when vineyards are put in. These are mapable features. She shared the locations of rock piles she identified, which we incorporated into the map. The Sonoma Vegetation Map mapped some distance into the western side of Napa County. We reviewed that map’s polygons for coast redwood. We then examined our imagery and the Google imagery to see if we could discern the whorled pattern of tree branches. Where we could, we amended or expanded redwood polygons in our map.The Vegetation classification systems used here follows California’s Manual of California Vegetation and the National Vegetation Classification System (MCV and NVCS). We started with the vegetation types listed in the 2004 map. We predominantly use the same set of species names, with modifications/additions particularly from the Knoxville map. The NVCS uses Alliance and Association as the two most taxonomically detailed levels. This map uses those levels. It also refers to vegetation types that have not been sampled in the field and that has 3-6 species and a site descriptor as Groups, which is the next more general level in the NVCS classification. We conducted 3 rounds of quality assessment/quality control exercises.

  13. a

    Public Safety Emergency Service Number

    • gis.data.alaska.gov
    • data.matsugov.us
    • +3more
    Updated Aug 26, 2016
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    Matanuska-Susitna Borough (2016). Public Safety Emergency Service Number [Dataset]. https://gis.data.alaska.gov/datasets/MSB::public-safety-emergency-service-number/api
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    Dataset updated
    Aug 26, 2016
    Dataset authored and provided by
    Matanuska-Susitna Borough
    Area covered
    Description

    Zones of common emergency response assignments for fire, rescue, police, and medical personnel. Used for E911 response purposes. Data was originally entered using ArcView. Data was entered using heads-up digitizing methods. Shapefile polygons were constructed using the RDS shapefile as the primary basis of reference. In densely developed areas, the tax map drawing files were also used as a supplemental basis of reference. Data was then converted to ArcInfo coverage format and the CLEAN command (using a tolerance of 10 feet) was used to reconstruct polygon topology. Several gaps and sliver polygons resulted from the CLEAN process. These were remedied using the MERGE subcommand found within ArcEdit. Feature attributes were then verified to insure that data had not been lost during the conversion and editing process. After successfully insuring that all data was still resident, the data was converted to Shapefile format for public distribution. In 2013 we shifted our core area parcel base therefore this dataset was shifted and manually corrected to follow updated parcel and road lines. In August 2015 we shifted our parcel base for areas along the Parks Highway from Houston to Talkeetna/Trapper Creek. Therefore this dataset was shifted and manually corrected to follow updated parcel and road lines.

  14. c

    Coastal Zone Boundary [ds990] GIS Dataset

    • map.dfg.ca.gov
    Updated Jan 12, 2024
    + more versions
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    (2024). Coastal Zone Boundary [ds990] GIS Dataset [Dataset]. https://map.dfg.ca.gov/metadata/ds0990.html
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    Dataset updated
    Jan 12, 2024
    Description

    CDFW BIOS GIS Dataset, Contact: Greg Benoit, Description: Polygon versions of the terrestrial CZB with a generalized shoreline (USGS 1:24,000 Quadrangle shoreline heads up digitized at 1:3000) and with a more detailed shoreline that includes most bays and estuaries. It was digitized within AutoCAD from the Commission's certified Coastal Zone Boundary hard copy maps. The files were then imported into ArcView, and merged together following Commission jurisdictional boundaries (North Coast, North Central Coast, Central Coast, South Central Coast, South

  15. a

    Game Management Units (Subunits)

    • gis.data.alaska.gov
    • hub.arcgis.com
    Updated Oct 12, 2015
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    Alaska Department of Fish & Game (2015). Game Management Units (Subunits) [Dataset]. https://gis.data.alaska.gov/maps/adfg::game-management-units-subunits
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    Dataset updated
    Oct 12, 2015
    Dataset authored and provided by
    Alaska Department of Fish & Game
    Area covered
    Description

    The Department of Fish and Game - Division of Wildlife Conservation's game management units and subunits are the most requested of the Division's GIS data. Hunting and trapping regulations and other wildlife management issues often refer geographically to the effected Game Management Unit (GMU). This file gives the user access to the currently available digital representation of the GMU/UCUs. The purpose of the GMU and associated Subunits and Uniform coding units is to give a uniform, geographic based coding system for all State of Alaska wildlife population and habitat management and regulations. This data can be used for mapping or analysis purposes assuming it is used with comparable data.Uniform Coding UnitsPrior to 1982, Alaska Department of Fish and Game - Division of Wildlife Conservation (ADFG-DWC) had a variety of coding schemes (18) relating harvest and management information to geographical areas. This made it difficult when comparing statewide wildlife information gathered across the state. In 1982, a new standardized statewide, geographically-based, hierarchy system of coding was created called the Uniform Coding Unit or UCU system. Game management units (GMUs), Subunits, and uniform coding units (UCUs) are the underlying geographic foundation of the wildlife and habitat management and regulations for ADFG-DWC. The GMU/UCU system consists of five Regions which are divided into twenty-six (26) Game Management Units (GMUs). Many of the GMUs are divided into Subunits (e.g. GMU 15 has three (3) Subunits, 15A, 15B, and 15C). GMUs that are not divided into subunits have a "Z" designation for the subunit. GMUs and Subunits are further divided into Major Drainages, Minor Drainages and Specific Areas. The smallest of these areas (down to the "specific area") is referred to as a Uniform Coding Unit (UCU) and has a unique 10 character code associated with it. (NOTE: UCU layer is for internal and official use only, not for public use or distribution). The UCU code is used for geographically classifying harvest and management information. Data that cannot be tied to a specific code can be generalized to the next higher level of the hierarchy. For example:a location description that is within multiple "specific areas" within a "minor drainage" can be coded to the minor code with a "00" for the specific area. Unknown "minor drainages" can be coded to the "major drainage" level, etc. If the subunit is unknown or the area covers multiple subunits within a unit, the subunit can be specified as a "Z" code (e.g. an area within subunits 15A and 15B could be recorded as 15Z). If a geographic location covers multiple units or the unit is unknown, the most general code (statewide code) is recorded as 27Z-Z00. The original hardcopy master maps were drawn to portray the UCUs fairly accurately geographically, but were not necessarily precisely drawn (i.e. left vs. right bank of a river, or exact ridge line). Each UCU was represented by drawing boundaries on USGS 1:250,000 scale quadrangle maps with a thick magic marker. A list (database) of place-names and their corresponding UCU codes was created and is still used today to assign permit, harvest, and sealing information to one of these geographic areas. In 1988, the UCU boundaries were digitized (traced) from the original maps into a computerized Geographic Information System (ArcInfo). Minor changes were made in 1989. Effective July 1, 2006 - GMU 24 is now divided up into four subunit 24A, 24B, 24C, 24D. - GMU 21A and 21B - - boundary has been modified. Phase I2006-2008 - initial clean-up of boundaries for GMU 6, 9, 10, 12, 16, 19, 20, 25. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Jan 2009 - Priority has shifted to getting the bulk of the updates into the master. Verification and modifications based on the UCU list and the AB corrections will come at a later date. This shift is to attempt to get the master into a permanent SDE GDB, set it up with the GDB topology, make additional clean-up/edits using the GDB tools, set up versioning, make it easier to replicate to area offices, and to take advantage of the tools/features available thru ArcGIS Server with versioned GDBs. June 2009 - initial clean-up of boundaries for Southeast (GMU 1-5), GMU 17, and GMU 18. These have NOT been verified against the UCU master list or by area biologists. -ras July 1 2009 - initial clean-up of boundaries for GMU 7 and 8. Also some adjustments for 25D based on the NHD 2008 version and ArcHydro Tools "raindrop" feature. These have NOT been verified against the UCU master list or by area biologists. -ras Sept 17, 2009 - initial clean-up of boundaries for GMU 13. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Oct 21, 2009 - initial clean-up of boundaries for GMU 14 These modification have NOT been verified against the UCU master list or by area biologists. -rasNov 19, 2009 - initial clean-up of boundaries for GMU 15. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Dec 7, 2009 - initial clean-up of boundaries for GMU 22. These modification have NOT been verified against the UCU master list or by area biologists. -ras March 3, 2010 - initial clean-up of boundaries for GMU 23. These modification have NOT been verified against the UCU master list or by area biologists. -rasApril 10, 2010 - initial clean-up of boundaries for GMU 26. These modification have NOT been verified against the UCU master list or by area biologists. -ras May 2010 - This completes Phase I of refining the UCUs - bulk heads-up re-digitizing of all arcs. Phase II - Converting and establishing procedures for maintaining the master in an Enterprise GDB is underway. Effective July 1, 2010, Region II was split into Region 2 (GMU's 6, 7, 8, 14C, 15) and Region 4 (GMU's 9, 10, 11, 13, 14AB, 16, 17. This version was updated to reflect the change. An archive of the previous version (with Regions I, II, III, and V) is available on request as GMUMaster_063010. -ras2012-present - minor updates continue as needed and time allows, and as newer base maps are used.2014 minor updates continue as needed, including updates to domain listings (not affecting GIS geometry)Effective July 1, 2014- revision to GMU 18/19/21 boundary to clarify/correct previous insufficient boundary description. Passed during Spring 2014 Board of Game.2015 minor changes as needed

  16. Geospatial data for the Vegetation Mapping Inventory Project of Arkansas...

    • catalog.data.gov
    • data.amerigeoss.org
    Updated Jun 5, 2024
    + more versions
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    National Park Service (2024). Geospatial data for the Vegetation Mapping Inventory Project of Arkansas Post National Memorial [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-arkansas-post-national-mem
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    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. The mapping component was produced by identifying land cover on air photos and hand digitizing on-screen. Heads-up digitizing was accomplished at a display scale of not more than 1:1,000 against a back-drop of air photos. Imagery was the most recent available from the National Agriculture Imagery Program. This included 2010 leaf-on true color and 2006 leaf-off color infrared images.

  17. Data from: Architect of the Capitol

    • catalog.data.gov
    • opendata.dc.gov
    • +4more
    Updated Feb 5, 2025
    + more versions
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    Architect of the Capitol (2025). Architect of the Capitol [Dataset]. https://catalog.data.gov/dataset/architect-of-the-capitol
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    Dataset updated
    Feb 5, 2025
    Dataset provided by
    Architect of the Capitolhttps://aoc.gov/
    Description

    Architect of the Capitol jurisdiction boundary. The dataset contains locations and attributes of the Architect of the Capitol jurisdiction boundary, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. The boundary was identified from public records (including the Architect's http://www.aoc.gov/cc/cc_map.htm ) and heads-up digitized using a combination of the 1995/1999 orthophotographs and planimetric roads features.

  18. n

    North Slope Infrastructure (V13): Roads, Pipelines and Developed Areas -...

    • catalog.northslopescience.org
    Updated Mar 28, 2018
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    (2018). North Slope Infrastructure (V13): Roads, Pipelines and Developed Areas - Update 03/22/2023 [Dataset]. https://catalog.northslopescience.org/dataset/2663
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    Dataset updated
    Mar 28, 2018
    Area covered
    North Slope Borough
    Description

    This North Slope infrastructure GIS dataset includes roads (line), pipelines (line) and developed areas (polygon) as separate feature classes. Downloads are in shapefile and geodatabase format. Major, maintained road features on the North Slope are provided. Minor connections or roads within developed areas may not be represented or are generalized. Above surface pipeline features are provided. Multiple adjacent pipelines may be represented as one pipeline, features along routes may be simplified and pipelines within developed areas omitted. Developed area features include gravel pads, material pits, constructed water features and village areas. Road locations within villages have been updated using Alaska Department of Transportation GIS data. Road, pipeline and developed area feature attributes have been assigned oil and gas unit designations using Alaska Division of Oil and Gas GIS data. The Trans-Alaska Pipeline (TAPS) was not digitized and is available via the link below. These infrastructure data were originally compiled by Audubon in 2014 and provided to the Bureau of Land Management (BLM) Rapid Ecological Assessment (REA) project for the North Slope region. Those data were edited by the Alaska Center for Conservation Science (ACCS) for the REA and released for public distribution on the BLM/REA website. The North Slope Science Initiative (NSSI) subsequently updated the REA product using high resolution imagery as a verification base and heads up digitizing to produce an initial version of this infrastructure dataset. Annual updates to these data have been performed by ACCS and funded by BLM. These updates are based on interpretation of 2022 Sentinel imagery for the Prudhoe Bay development area and other image products as available for the greater North Slope region. All locations are approximate. Neither ACCS, BLM, NSSI or other contributors to this dataset shall be held liable for improper or incorrect use of the data described and/or contained herein. In an effort to provide the most comprehensive overview possible, these updates have incorporated many data sources, using a variety compilation methods. As a result, there are a variety of limitations to the thematic and spatial accuracy of these data. The appropriate use of these data is the responsibility of the user. A link to a web map containing this infrastructure data as well as land ownership and administrative information is provided below.

  19. m

    Infrastructure Separated Paths

    • data.matsugov.us
    • gis.data.alaska.gov
    • +2more
    Updated Jul 16, 2016
    + more versions
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    Matanuska-Susitna Borough (2016). Infrastructure Separated Paths [Dataset]. https://data.matsugov.us/maps/MSB::infrastructure-separated-paths-1/about
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    Dataset updated
    Jul 16, 2016
    Dataset authored and provided by
    Matanuska-Susitna Borough
    Area covered
    Description

    This dataset provides the location of separated paved paths in the Matanuska-Susitna Borough. These paths are typically paved, along side an existing roadway, constructed as part of a road construction or upgrade project, and provide an alternative to motorized transportation methods. This dataset does not include sidewalks. Most trails in this dataset were heads up digitized (scale

  20. Imagery data for the Vegetation Mapping Inventory Project of Bryce Canyon...

    • catalog.data.gov
    Updated Jun 5, 2024
    + more versions
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    National Park Service (2024). Imagery data for the Vegetation Mapping Inventory Project of Bryce Canyon National Park [Dataset]. https://catalog.data.gov/dataset/imagery-data-for-the-vegetation-mapping-inventory-project-of-bryce-canyon-national-park
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Description

    This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Vegetation and land use were interpreted to as detailed a level as possible from high-resolution, 9” x 9” stereo pairs of 1:12,000-scale true color aerial photography. Polygons representing vegetation or land use map classes were delineated on Mylar overlays on aerial photographs (where signatures were confusing) and with the heads-up digitizing technique (where signatures had high contrast), then transferred to a spatial database. The project used the national program standard minimum mapping unit of 0.5 ha with few exceptions.

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National Park Service (2024). Geospatial data for the Vegetation Mapping Inventory Project of Bryce Canyon National Park [Dataset]. https://catalog.data.gov/dataset/geospatial-data-for-the-vegetation-mapping-inventory-project-of-bryce-canyon-national-park
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Geospatial data for the Vegetation Mapping Inventory Project of Bryce Canyon National Park

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Dataset updated
Jun 5, 2024
Dataset provided by
National Park Servicehttp://www.nps.gov/
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. The mapping component of the BRCA project used a combination of methods to interpret and delineate vegetation and land use polygons. The USGS applied an electronic segmentation method (e-Cognition software) to create preliminary linework on features with high-contrast photo-signatures. Using the preliminary linework as a baseline starting point, the primary photointerpreter drew polygons directly on screen through heads-up digitizing using ArcGIS editing tools. Additionally, trained photointerpreters assisting the primary photointerpreter drew polygons on Mylar overlays covering 1m resolution, 1:12,000-scale, 9 x 9-inch true-color aerial photographs. This process enabled the photointerpreters to view the landscape in stereo in order to identify finer details. The linework drawn on Mylar overlays was then transferred into digital media by heads-up digitizing using ArcGIS software. The park and environs were interpreted and mapped to the same level of detail.

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