60 datasets found
  1. n

    Administrative Forest Boundaries - Dataset - CKAN

    • nationaldataplatform.org
    Updated Mar 6, 2025
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    (2025). Administrative Forest Boundaries - Dataset - CKAN [Dataset]. https://nationaldataplatform.org/catalog/dataset/fdh-administrative-forest-boundaries1
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    Dataset updated
    Mar 6, 2025
    Description

    An area encompassing all the National Forest System lands administered by an administrative unit. The area encompasses private lands, other governmental agency lands, and may contain National Forest System lands within the proclaimed boundaries of another administrative unit. All National Forest System lands fall within one and only one Administrative Forest Area. This data is intended for read-only use. These data were prepared to describe Forest Service administrative area boundaries. The purpose of the data is to provide display, identification, and analysis tools for determining current boundary information for Forest Service managers, GIS Specialists, and others. The Forest Service has multiple types of boundaries represented by different feature classes (layers): Administrative, Ownership and Proclaimed. 1) ADMINISTRATIVE boundaries (e.g. AdministrativeForest and RangerDistrict feature classes) encompass National Forest System lands managed by an administrative unit. These are dynamic layers that should not be considered "legal" boundaries as they are simply intended to identify the specific organizational units that administer areas. As lands are acquired and disposed, the administrative boundaries are adjusted to expand or shrink accordingly. Please note that ranger districts are sub units of National Forests. An administrative forest boundary can contain one or more Proclaimed National Forests, National Grasslands, Purchase Units, Research and Experimental Areas, Land Utilization Projects and various "Other" Areas. If needed, OWNERSHIP boundaries (e.g. BasicOwnership and SurfaceOwnership feature classes) should be reviewed along with these datasets to determine parcels that are federally managed within the administrative boundaries. 2) OWNERSHIP boundaries (e.g. BasicOwnership and SurfaceOwnership feature classes) represent parcels that are tied to legal transactions of ownership. These are parcels of Federal land managed by the USDA Forest Service. Please note that the BasicOwnership layer is simply a dissolved version of the SurfaceOwnership layer. 3) PROCLAIMED boundaries (e.g. ProclaimedForest and ProclaimedForest_Grassland) encompass areas of National Forest System land that is set aside and reserved from public domain by executive order or proclamation. Please note that the ProclaimedForest layer contains only proclaimed forests while ProclaimedForest_Grassland layer contains both proclaimed forests and proclaimed grasslands. For boundaries that reflect current National Forest System lands managed by an administrative unit, see the ADMINISTRATIVE boundaries (AdministrativeForest and RangerDistrict feature classes). For a visual comparison of the different kinds of USFS boundary datasets maintained by the USFS, see the Forest Service Boundary Comparison map at https://usfs.maps.arcgis.com/apps/CompareAnalysis/index.html?appid=fe7b9f56217949a291356f08cfccb119. USFS boundaries are often referenced in national datasets maintained by other federal agencies. Please note that variations may be found between USFS data and other boundary datasets due to differing update frequencies. PAD-US (Protected Areas Database of the United States), maintained by the U.S. Geological Survey, is a "best available" inventory of protected areas including data provided by managing agencies and organizations including the Forest Service. For more information see https://gapanalysis.usgs.gov/padus/data/metadata/. SMA (Surface Management Agency), maintained by the Bureau of Land Management, depicts Federal land for the United States and classifies this land by its active Federal surface managing agency. It uses data provided by the Forest Service and other agencies, combined with National Regional Offices collection efforts. For more information see https://landscape.blm.gov/geoportal/catalog/search/resource/details.page?uuid=%7B2A8B8906-7711-4AF7-9510-C6C7FD991177%7D.

  2. A

    VT Boundaries - LEPC polygons

    • data.amerigeoss.org
    csv, esri rest +5
    Updated Jul 30, 2019
    + more versions
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    United States[old] (2019). VT Boundaries - LEPC polygons [Dataset]. https://data.amerigeoss.org/es/dataset/vt-boundaries-lepc-polygons
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    kml, zip, esri rest, csv, ogc wms, geojson, htmlAvailable download formats
    Dataset updated
    Jul 30, 2019
    Dataset provided by
    United States[old]
    Area covered
    Vermont
    Description

    (Link to Metadata) The BNDHASH dataset depicts Vermont villages, towns, counties, Regional Planning Commissions (RPC), and LEPC (Local Emergency Planning Committee) boundaries. It is a composite of generally 'best available' boundaries from various data sources (refer to ARC_SRC and SRC_NOTES attributes). However, this dataset DOES NOT attempt to provide a legally definitive boundary. The layer was originally developed from TBHASH, which was the master VGIS town boundary layer prior to the development and release of BNDHASH. By integrating village, town, county, RPC, and state boundaries into a single layer, VCGI has assured vertical integration of these boundaries and simplified maintenance. BNDHASH also includes annotation text for town, county, and RPC names. BNDHASH includes the following feature classes: 1) VILLAGES = Vermont villages 2) TOWNS = Vermont towns 3) COUNTIES = Vermont counties 4) RPCS = Vermont's Regional Planning Commissions 5) LEPC = Local Emergency Planning Committee boundaries 6) VTBND = Vermont's state boundary The master BNDHASH layer is managed as ESRI geodatabase feature dataset by VCGI. The dataset stores villages, towns, counties, and RPC boundaries as seperate feature classes with a set of topology rules which binds the features. This arrangement assures vertical integration of the various boundaries. VCGI will update this layer on an annual basis by reviewing records housed in the VT State Archives - Secretary of State's Office. VCGI also welcomes documented information from VGIS users which identify boundary errors. NOTE - VCGI has NOT attempted to create a legally definitive boundary layer. Instead the idea is to maintain an integrated village/town/county/rpc boundary layer which provides for a reasonably accurate representation of these boundaries (refer to ARC_SRC and SRC_NOTES). BNDHASH includes all counties, towns, and villages listed in "Population and Local Government - State of Vermont - 2000" published by the Secretary of State. BNDHASH may include changes endorsed by the Legislature since the publication of this document in 2000 (eg: villages merged with towns). Utlimately the Vermont Secratary of State's Office and the VT Legislature are responsible for maintaining information which accurately describes the location of these boundaries. BNDHASH should be used for general mapping purposes only. * Users who wish to determine which boundaries are different from the original TBHASH boundaries should refer to the ORIG_ARC field in the BOUNDARY_BNDHASH_LINE (line featue with attributes). Also, updates to BNDHASH are tracked by version number (ex: 2003A). The UPDACT field is used to track changes between versions. The UPDACT field is flushed between versions.

  3. a

    Prison Boundaries

    • disaster-amerigeoss.opendata.arcgis.com
    • azgeo-open-data-agic.hub.arcgis.com
    • +4more
    Updated Sep 16, 2024
    + more versions
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    GeoPlatform ArcGIS Online (2024). Prison Boundaries [Dataset]. https://disaster-amerigeoss.opendata.arcgis.com/datasets/geoplatform::prison-boundaries-1
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    Dataset updated
    Sep 16, 2024
    Dataset authored and provided by
    GeoPlatform ArcGIS Online
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    The prison boundary feature class contains secure detention facilities. These facilities range in jurisdiction from federal(excluding military) to local governments. Polygon geometry is used to describe the extent of where the incarcerated population is located (fence lines or building footprints). This feature class's attribution describes many physical and social characteristics of detention facilities in the United States and some of its territories. The attribution for this feature class was populated by open source search methodologies of authoritative sources. Changes from the previous version include 80 records added, 132 closed, 30 reopened, and 363 removed.

  4. BLM CA Administrative Unit Boundary Field Office Polygon

    • catalog.data.gov
    • gbp-blm-egis.hub.arcgis.com
    Updated Nov 20, 2024
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    Bureau of Land Management (2024). BLM CA Administrative Unit Boundary Field Office Polygon [Dataset]. https://catalog.data.gov/dataset/blm-ca-administrative-unit-boundary-field-office-polygon
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    Dataset updated
    Nov 20, 2024
    Dataset provided by
    Bureau of Land Managementhttp://www.blm.gov/
    Description

    This polygon feature class represents the spatial extent of historical BLM Administrative Unit Boundaries (at the State, District, and Field Office levels).This state dataset may have published a dataset that is more current than the National dataset; there may be geometry variations between the state and national dataset which may have different results. The national dataset is updated following the data standard schedule

  5. E

    Standardisation of River Classifications in Greece

    • bodc.ac.uk
    • edmed.seadatanet.org
    nc
    Updated Aug 28, 2015
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    Hellenic Centre for Marine Research, Institute of Marine Biological Resources and Inland Waters, Dept. of Inland Waters (2015). Standardisation of River Classifications in Greece [Dataset]. https://www.bodc.ac.uk/resources/inventories/edmed/report/1222/
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    ncAvailable download formats
    Dataset updated
    Aug 28, 2015
    Dataset authored and provided by
    Hellenic Centre for Marine Research, Institute of Marine Biological Resources and Inland Waters, Dept. of Inland Waters
    License

    https://vocab.nerc.ac.uk/collection/L08/current/UN/https://vocab.nerc.ac.uk/collection/L08/current/UN/

    Time period covered
    Jan 1, 2002 - Dec 31, 2005
    Area covered
    Description

    Standardisation of River Classifications: Framework method for calibrating different biological survey results against ecological quality classifications to be developed for the Water Framework Directive. Problems to be solved: The variety of assessment methods for streams and rivers in Europe provides good opportunities for implementing the Water Framework Directive but their diversity may also result in serious strategic problems. The number of organism groups that will be used to assess Ecological Status, and the number of methods available for doing so are so diverse that inter-calibration and standardisation of methods is crucial. Similarly, protocols need to be devised to integrate the information gathered on the different taxonomic groups. The project aims to derive a detailed picture of which methods are best suited for which circumstances as a basis for standardisation. We propose to develop a standard for determining class boundaries of Ecological Status and another for inter-calibrating existing methods. Scientific objectives and approach: Data will be used to answer the following questions, which form the basis of a conceptual model: 1) How can data resulting from different assessment methods be compared and standardised? 2) Which methods/taxonomic groups are most capable of indicating particular individual stressors? 3) Which method can be used on which scale? 4) Which method is suited for early and late warnings? 5) How are different assessment methods affected by errors? 6) What can be standardised and what should be standardised? For the purposes of this project two 'core streams types' are recognised: small, shallow, upland streams and medium-sized, deeper lowland streams. Besides the evaluation of existing data, a completely new data set is sampled to gain comparable data on macroinvertebrates, phytobenthos, fish and stream morphology taken with a set of different methods from sites representing different stages of degradation. This will be the main source of data for cross-comparisons and the preparation of standards. A number of 'additional stream types' will be investigated in order to extend the range of sites at which field methods and assessment procedures are compared. The participants will be trained in sampling workshops and quality assurance will be implemented through an audit. Using the project database, assessment methods based on benthic macroinvertebrates will be compared and inter-calibrated, particularly in terms of errors, precision, relation to reference conditions and possible class boundaries. The discriminatory power of different organism groups to detect ecological change will be tested through various statistical procedures. Two CEN Workshops will be held during the contracted period. These will result in the formulation of draft standards for circulation, amendment, agreement by participating countries in CEN.STAR will benefit from clustering with the complementary Framework V Project, FAME. Project FAME will develop European fish assessment protocols using existing data. STAR fish sampling will be based on FAME protocols and STAR field data will be used by FAME to test these new protocols. Expected impacts: The project will provide a general concept understanding of how to use different organism groups for stream assessment. The project findings will be implemented through a decision support system. Existing methods based on benthic macroinvertebrates will be inter-calibrated to enable a future comparison of river quality classes throughout Europe. Existing assessment methods will be supplemented by an 'error module'. A matrix of possible class boundaries of grades of 'Ecological Status' associated with different methods and stressors will be developed. Committee drafts for the relevant CEN working group and draft standards on stream assessment methods will be produced. Deliverables: Please see: www.eu-star.at/frameset.htm

  6. v

    VT Data - Village Boundaries

    • geodata.vermont.gov
    • sov-vcgi.opendata.arcgis.com
    • +2more
    Updated Jun 17, 2003
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    VT Center for Geographic Information (2003). VT Data - Village Boundaries [Dataset]. https://geodata.vermont.gov/datasets/vt-data-village-boundaries-1/about
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    Dataset updated
    Jun 17, 2003
    Dataset authored and provided by
    VT Center for Geographic Information
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    (Link to Metadata) The BNDHASH dataset depicts Vermont village, town, county, and Regional Planning Commission (RPC) boundaries. It is a composite of generally 'best available' boundaries from various data sources (refer to ARC_SRC and SRC_NOTES attributes). However, this dataset DOES NOT attempt to provide a legally definitive boundary. The layer was originally developed from TBHASH, which was the master VGIS town boundary layer prior to the development and release of BNDHASH. By integrating village, town, county, RPC, and state boundaries into a single layer, VCGI has assured vertical integration of these boundaries and simplified maintenance. BNDHASH also includes annotation text for town, county, and RPC names. BNDHASH includes the following feature classes: 1) BNDHASH_POLY_VILLAGES = Vermont villages 2) BNDHASH_POLY_TOWNS = Vermont towns 3) BNDHASH_POLY_COUNTIES = Vermont counties 4) BNDHASH_POLY_RPCS = Vermont's Regional Planning Commissions 5) BNDHASH_POLY_VTBND = Vermont's state boundary 6) BNDHASH_LINE = Lines on which all POLY feature classes are built The master BNDHASH data is managed as an ESRI geodatabase feature dataset by VCGI. The dataset stores village, town, county, RPC, and state boundaries as seperate feature classes with a set of topology rules which binds the features. This arrangement assures vertical integration of the various boundaries. VCGI will update this layer on an annual basis by reviewing records housed in the VT State Archives - Secretary of State's Office. VCGI also welcomes documented information from VGIS users which identify boundary errors. NOTE - VCGI has NOT attempted to create a legally definitive boundary layer. Instead the idea is to maintain an integrated village/town/county/RPC/state boundary layer which provides for a reasonably accurate representation of these boundaries (refer to ARC_SRC and SRC_NOTES). BNDHASH includes all counties, towns, and villages listed in "Population and Local Government - State of Vermont - 2000" published by the Secretary of State. BNDHASH may include changes endorsed by the Legislature since the publication of this document in 2000 (eg: villages merged with towns). Utlimately the Vermont Secratary of State's Office and the VT Legislature are responsible for maintaining information which accurately describes the locations of these boundaries. BNDHASH should be used for general mapping purposes only. * Users who wish to determine which boundaries are different from the original TBHASH boundaries should refer to the ORIG_ARC field in the BOUNDARY_BNDHASH_LINE (line feature with attributes). Also, updates to BNDHASH are tracked by version number (ex: 2003A). The UPDACT field is used to track changes between versions. The UPDACT field is flushed between versions.

  7. d

    Study Area Boundary Malakoff DIggins State Historic Park, California

    • datasets.ai
    • data.usgs.gov
    • +2more
    55
    Updated Sep 23, 2024
    + more versions
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    Department of the Interior (2024). Study Area Boundary Malakoff DIggins State Historic Park, California [Dataset]. https://datasets.ai/datasets/study-area-boundary-malakoff-diggins-state-historic-park-california
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    55Available download formats
    Dataset updated
    Sep 23, 2024
    Dataset authored and provided by
    Department of the Interior
    Description

    One of the largest hydraulic mines (1.6 km2) is located in California’s Sierra Nevada within the Humbug Creek watershed and Malakoff Diggins State Historic Park (MDSHP). MDSHP’s denuded and dissected landscape is composed of weathered Eocene auriferous sediments susceptible to chronic rill and gully erosion whereas block failures and debris flows occur in more cohesive terrain. This data release includes a 2014 digital elevation model (DEM), a study area boundary, and a geomorphic map. The 2014 DEM was derived from an available aerial LiDAR dataset collected in 2014 by the California Department of Conservation. The geomorphic map was derived for the study area from using a multi-scale spatial analysis. A topographic position index (TPI) was created using focal statistics to compare the elevations across the study area. We calculated a fine-scale TPI using a circular neighborhood with a radius of 25-meters and large-scale TPI using a circular neighborhood with a radius of 100-meters. In the resulting raster positive TPI values are assigned to cells with elevations higher than the surrounding area and negative TPI values are assigned to cells with elevations lower than the surrounding area. The geomorphic map was then created using a nested conditional statement to apply classification thresholds on the basis the fine and large-scale TPI rasters and a slope raster. Ten geomorphic feature classes were defined and the map can be symbolized by feature class. The geomorphic map includes both channel and hillslope features and can be used to assess erosional and depositional processes at the landscape scale.

  8. i

    Parcel Boundaries of Indiana Current

    • indianamap.org
    • indianamapold-inmap.hub.arcgis.com
    • +1more
    Updated Nov 13, 2024
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    IndianaMap (2024). Parcel Boundaries of Indiana Current [Dataset]. https://www.indianamap.org/maps/INMap::parcel-boundaries-of-indiana-current-1
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    Dataset updated
    Nov 13, 2024
    Dataset authored and provided by
    IndianaMap
    Area covered
    Description

    This data layer is an Esri file geodatabase polygon feature class that contains parcel boundaries maintained by county agencies in Indiana. It was released by the Indiana Geographic Information Office (IGIO) on November 13, 2024. The IGIO compiled the data as part of the Indiana Data Harvest program between the Indiana Geographic Information Council (IGIC) and Indiana local governments to provide the most accurate framework data for the citizens of Indiana. These layers include address points, street centerlines, land parcels, and governmental boundaries.

  9. v

    RPC Boundaries

    • vtculverts.org
    Updated Jun 3, 2024
    + more versions
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    VT Association of Planning and Development Agencies Hub Community (2024). RPC Boundaries [Dataset]. https://www.vtculverts.org/datasets/vapda-hub::rpc-boundaries
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    Dataset updated
    Jun 3, 2024
    Dataset authored and provided by
    VT Association of Planning and Development Agencies Hub Community
    Area covered
    Description

    The BNDHASH dataset depicts Vermont villages, towns, counties, Regional Planning Commissions (RPC), and LEPC (Local Emergency Planning Committee) boundaries. It is a composite of generally 'best available' boundaries from various data sources (refer to ARC_SRC and SRC_NOTES attributes). However, this dataset DOES NOT attempt to provide a legally definitive boundary. The layer was originally developed from TBHASH, which was the master VGIS town boundary layer prior to the development and release of BNDHASH. By integrating village, town, county, RPC, and state boundaries into a single layer, VCGI has assured vertical integration of these boundaries and simplified maintenance. BNDHASH also includes annotation text for town, county, and RPC names. BNDHASH includes the following feature classes: 1) VILLAGES = Vermont villages 2) TOWNS = Vermont towns 3) COUNTIES = Vermont counties 4) RPCS = Vermont's Regional Planning Commissions 5) LEPC = Local Emergency Planning Committee boundaries 6) VTBND = Vermont's state boundary The master BNDHASH layer is managed as ESRI geodatabase feature dataset by VCGI. The dataset stores villages, towns, counties, and RPC boundaries as seperate feature classes with a set of topology rules which binds the features. This arrangement assures vertical integration of the various boundaries. VCGI will update this layer on an annual basis by reviewing records housed in the VT State Archives - Secretary of State's Office. VCGI also welcomes documented information from VGIS users which identify boundary errors. NOTE - VCGI has NOT attempted to create a legally definitive boundary layer. Instead the idea is to maintain an integrated village/town/county/rpc boundary layer which provides for a reasonably accurate representation of these boundaries (refer to ARC_SRC and SRC_NOTES). BNDHASH includes all counties, towns, and villages listed in "Population and Local Government - State of Vermont - 2000" published by the Secretary of State. BNDHASH may include changes endorsed by the Legislature since the publication of this document in 2000 (eg: villages merged with towns). Utlimately the Vermont Secratary of State's Office and the VT Legislature are responsible for maintaining information which accurately describes the location of these boundaries. BNDHASH should be used for general mapping purposes only. * Users who wish to determine which boundaries are different from the original TBHASH boundaries should refer to the ORIG_ARC field in the BOUNDARY_BNDHASH_LINE (line featue with attributes). Also, updates to BNDHASH are tracked by version number (ex: 2003A). The UPDACT field is used to track changes between versions. The UPDACT field is flushed between versions.

  10. BLM ID Field Office Administrative Unit Boundary

    • catalog.data.gov
    • gbp-blm-egis.hub.arcgis.com
    Updated Nov 20, 2024
    + more versions
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    Bureau of Land Management (2024). BLM ID Field Office Administrative Unit Boundary [Dataset]. https://catalog.data.gov/dataset/blm-id-field-office-administrative-unit-boundary-hub
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    Dataset updated
    Nov 20, 2024
    Dataset provided by
    Bureau of Land Managementhttp://www.blm.gov/
    Description

    This data set shows the Idaho Bureau of Land Management (BLM) Field Office, District Office and State Office boundaries and names as per the three-tier organization initiated in February 2007. A Bureau of Land Management (BLM) Administrative Unit is a geographic area in which an organizational unit of the BLM has distinct jurisdictional responsibility for land and resource management activities occurring on the public lands, the maintained rights of the United States (i.e. mineral estate) and actions relating to the Trust responsibilities of the U.S. Government as stipulated in Law or Treaty.The State Office is the top layer of the three-tier organization, with District Offices being the middle layer and providing coordination, oversight and support to the lowest level, the Field Office. Idaho has one State Office, four Districts and twelve Field Offices. This feature class documents the physical boundary of an administrative unit. In some cases, the administrative unit may manage areas outside of the boundary for other programs’ purposes - this datset does not show these areas. BLM Idaho administers a little land in Nevada also, which is included here. For more information contact us at blm_id_stateoffice@blm.gov.

  11. P

    Data from: SBD Dataset

    • paperswithcode.com
    Updated Feb 11, 2021
    + more versions
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    Bharath Hariharan; Pablo Arbelaez; Lubomir D. Bourdev; Subhransu Maji; Jitendra Malik (2021). SBD Dataset [Dataset]. https://paperswithcode.com/dataset/sbd
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    Dataset updated
    Feb 11, 2021
    Authors
    Bharath Hariharan; Pablo Arbelaez; Lubomir D. Bourdev; Subhransu Maji; Jitendra Malik
    Description

    The Semantic Boundaries Dataset (SBD) is a dataset for predicting pixels on the boundary of the object (as opposed to the inside of the object with semantic segmentation). The dataset consists of 11318 images from the trainval set of the PASCAL VOC2011 challenge, divided into 8498 training and 2820 test images. This dataset has object instance boundaries with accurate figure/ground masks that are also labeled with one of 20 Pascal VOC classes.

  12. BLM CA Land Use Planning Area Boundary Polygon

    • catalog.data.gov
    • gbp-blm-egis.hub.arcgis.com
    Updated Nov 20, 2024
    + more versions
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    Bureau of Land Management (2024). BLM CA Land Use Planning Area Boundary Polygon [Dataset]. https://catalog.data.gov/dataset/blm-ca-land-use-planning-areas-17255
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    Dataset updated
    Nov 20, 2024
    Dataset provided by
    Bureau of Land Managementhttp://www.blm.gov/
    Description

    This polygon feature class represents the spatial extent and boundaries for anticipated, in-progress, existing and historic BLM Land Use Planning Area (LUPA) polygons. Land Use Planning Areas are geographic areas within which the BLM will make decisions during a land use planning effort. Land Use Planning Area Boundaries shift from an "in-progress" status and become Existing Land Use Planning Areas when the Land Use Plan has been approved and a Record of Decision Date has been established. At this point, these LUPAs are officially "existing" and the previous plan is moved to a "historic" status.

  13. K

    NZ FSMS6 (North Island)

    • koordinates.com
    csv, dwg, geodatabase +6
    Updated Feb 1, 2001
    + more versions
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    Ollivier & Co (2001). NZ FSMS6 (North Island) [Dataset]. https://koordinates.com/layer/300-nz-fsms6-north-island/
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    geodatabase, geopackage / sqlite, csv, kml, pdf, dwg, mapinfo mif, shapefile, mapinfo tabAvailable download formats
    Dataset updated
    Feb 1, 2001
    Dataset authored and provided by
    Ollivier & Co
    Area covered
    Description

    1.1.1 Forest Service Mapping Series 6 (FSMS6)

    The 23 completed maps provide the distribution of indigenous forest vegetation for all of the North Island and the bulk of the South Island at a scale of 1:250,000. These maps were primarily compiled by Mr John Nicholls with some of the South Island maps compiled by Mr Dudley Franklin. Black and white aerial photographs, dating from 1948 to 1955 and at a scale of 15 chains per inch, supplemented by extensive ground truthing and some 16,000 National Forest Survey and Ecosurvey plots, were used to determine forest class boundaries. These were transferred to 1:63360 topographic maps. The maps were field checked and then copied for production by FRI graphics staff (Herbert 1997, pers. comm.).

    Most maps were completed by the NZ Forest Service, with a small number being finished by the Ministry of Forestry and then by Landcare Research Ltd. Appendix 1 gives the list of maps digitised. The date of the photographs that were used to compile each map is not known exactly.

    1.1.2 Forest Service Mapping Series 15 (FSMS15)

    There are two FSMS15 comprising 1:1,000,000 maps of the North Island, and South Island (including Stewart Island). These were compiled by NZFS Conservancy and Head Office staff for the 1974 Forestry Development Conference. Forest boundaries for the 1:1,000,000 FSMS15 maps are significantly less accurate than those for the 1:250,000 FSMS6 maps (Herbert and Nicholls, 1997, pers. comm.). Data sources included existing FSMS6 maps (with 18 classes coalesced into eight super classes), local published and unpublished maps and local knowledge for areas not cover by the FSMS6. The Te Anau, Hauroko and Mataura FSMS6 series maps were substituted for by the South Island FSMS15 map.

    1.1.3 Forest Service Type Map Series No. 2 (FSTM2)

    These are a collection of detailed forest class maps at 1:63360 scale. Coverage is confined to parts of the central North Island.

    ### 1.1.4 Vegetation of Stewart Island

    Mr Hugh Wilson (Wilson, 1987) developed a detailed map of the vegetation of Steward Island. Wilson’s Podocarp/hardwood forest, and rata-kamahi hardwood forest polygons (Types A 1-2, B3) were digitised.

    1.2 Forest Class Description

    There are eighteen forest classes described in the FSMS6 map series. These are described in Table 1. The source is Nicholls and Herbert (1995). FSMS15 has eight super classes and these are defined in Table 2.

    *Table 1: Forest classes, codes and IPCC class

            (Dbase)
    

    *Class Code IPCC Class

    *Kauri A C

    *Kauri -Softwoods-Hardwoods B M

    *Kauri -Softwoods-Hardwoods-Beeches C M

    *Softwoods L C

    *Rimu-Matai-Hardwoods M M

    *Rimu-Taraire - Tawa E M

    *Rimu-Tawa D M

    *Rimu-General Hardwoods F M

    *Lowland Steepland and Highland Softwoods - Hardwoods G M

    *Rimu-Tawa-Beeches H M

    *Rimu - General Hardwoods - Beeches I M

    *Highland Softwoods-Beeches J M

    *Taraire-Tawa S B

    *Tawa N B

    *General Hardwoods P B

    *Tawa Beeches O B

    *General Hardwoods - Beeches T B

    *Beeches K B

    IPCC Class Definitions: C: Conifer, B: Broadleaf, M: Mixed.

    Table 2: FSMS15 forest classes

          Dbase
    

    Class code / FSMS6Classes Description IPCC Class

    Kauri - Podocarp - Hardwood /A, B, C All forest containing kauri, including minor area of pure kauri and local occurrence of beech M

    Podocarp L/ L Forest of abundant podocarps C

    Lowland Podocarp - Hardwood 1/ D, E, F, M, pt. G Virgin or lightly logged podocarp - hardwood forest below the altitudinal limit of rimu M

    Lowland Hardwood 2/ N, S, pt. P Residual and second growth forest below the altitudinal limit of rimu and minor areas of natural pure hardwood forest. B

    Upland Podocarp - Hardwood 3/ Pts G, P Virgin or lightly logged podocarp - hardwood above the altitudinal limit of rimu and minor areas of natural pure hardwood forest.
    M

    Podocarp - Hardwood - Beech 4/ H, I Virgin or lightly logged forest of mixed podocarp - hardwood and beech below the altitudinal limit of rimu M

    Hardwood - Beech 5/ O, T Residual or second growth forest and minor areas of natural pure hardwood - beech. B

    Beech 6/ J, K Virgin and lightly logged or second-growth forests predominantly composed of beech B

    Wilson Stewart Island 7/ Podocarp/hardwood forest, and rata-kamahi hardwood forest. M

    2. METHODS

    2.1 Digitising and Topology Generation

    The maps were digitised by staff at the Forest Research Institute under standards listed in Appendix 2, using the Terrasoft Geographic Information System. The linear features that made up each forest class polygon are shared between two feature classes one, called NZFS6 which contains the national coverage, and the other based on the respective map sheet number. This allows themes to be developed for a national view and also for the individual map sheets.

    The line work is topologically correct with no over-, or under- shoots.

    Each polygon has a nationally unique identifier and which is linked to a dbase table containing a code letter which describes the forest vegetation class.

    These maps were digitised for the purpose of providing indigenous forest vegetation cover for usage at a national scale. There has been no formal checking of the accuracy of the digitised linework. Any errors are considered to be insignificant for determining a 1990 indigenous forest vegetation baseline database. Each polygon was checked to confirm correct tagging. During that process any significant linear differences were noted and corrected.

    2.2 Problems

    2.2.1 Incorrect map details

    In several places errors on the maps were found. Either the FSTM2 maps were consulted for greater detail where coverage existed or Mr John Nicholls was, personally, consulted and the error corrected.

    2.2.2 Map source quality

    Most FSMS6 maps where unused, unfolded sheets with only sheet 12 being an unused folded map. The FSMS15 South Island map was a well used map with significant fold lines. This map also had other printed information which made precise measurement of some forest class boundaries difficult.

    Standards

    This document defines the standards used for digitising the forest class maps (NZFS Map Series 6, FSMS15 and Wilson, 1987).

    Source

    The source of the FSMS6 data is the 1:125,000 flat map sheets, the FSMS15 maps and the Vegetation map contained in Wilson (1987).

    Digitising

    The following digitising standards were used.

    A minimum of five points for registration should be selected from a rectangular range encapsulating the immediate digitising area. These points then should he entered into Convert and both the input and the resultant NZMG coordinates checked before the map is registered. The registration error should be (in Terrasoft) 0.00%. The media should be anchored firmly to the digitiser. The RMU laboratory should be used with the air conditioning turn on. Registration should occur at least twice a day, but occur more frequently if the humidity changes. All lines and polygon which represent a forest type needs to be captured irrespective of size. All intersections should have a node digitised. The two feature classes are NZFS6 and NZFS6_

    Output

    Shape must be identical

    Theme creation

    A Theme will be created for each map sheet. The national NZFS6 theme will be created by including the previously digitised map sheets and the FSMS15 and Wilson’s map. Polygon tags are to be corrected between the map sheets to make them all unique. All dangles and overlaps, and bad polygons are to be corrected.

    Tagging

    All polygons are to be tagged with a code representing the forest type. All sliver polygons are to be removed.

    Checking

    A plot should be created at the original scale and overlayed over the original map. Each polygon is checked to confirm correct tagging.

  14. d

    Data: Boundary lines of historical territories of Spanish America, 1701-1808...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Dec 16, 2023
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    Stangl, Werner (2023). Data: Boundary lines of historical territories of Spanish America, 1701-1808 [Dataset]. http://doi.org/10.7910/DVN/KJPNFJ
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    Dataset updated
    Dec 16, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Stangl, Werner
    Time period covered
    Jan 1, 1701 - Dec 31, 1808
    Description

    Derived from the territorial polygon dataset (https://doi.org/10.7910/DVN/YPEU5E ), we produced line feature classes of the boundary lines between the bishoprics, provinces, jurisdictions, etc. The resulting files are smaller and do not include the coastline or inner frontiers. Therefore, they are better suited for cartographical representations of boundaries, while the polygon dataset is better suited for displaying data associated with the areas. There are always two lines for the same boundary, each holding the information of both neighboring entities. Each object has a chronological validity marked by the fields START and END_

  15. M

    Constructon and Maintenance Boundaries in Minnesota

    • gisdata.mn.gov
    fgdb, gpkg, html, shp
    Updated Dec 1, 2022
    + more versions
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    Transportation Department (2022). Constructon and Maintenance Boundaries in Minnesota [Dataset]. https://gisdata.mn.gov/el/dataset/groups/bdry-mndot
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    gpkg, fgdb, shp, htmlAvailable download formats
    Dataset updated
    Dec 1, 2022
    Dataset provided by
    Transportation Department
    Area covered
    Minnesota
    Description

    The Minnesota Department of Transportation (MnDOT) divides the state into eight administrative zonal areas referred to as construction districts. The boundaries of these districts are used to determine which district is responsible for construction activities on trunk highways, and for reporting purposes.
    Construction Districts is a polygon feature class that represents an area that defines the portions of trunk highways and their junctions served by each of the eight districts.

    The Minnesota Department of Transportation (MnDOT) divides the state into eight administrative zonal areas called Construction Districts. Some of these Construction Districts have been further sub-divided into Maintenance SubDistricts, which may identify a region for operational or administrative purposes. Maintenance SubDistricts is a polygon feature class that represents this area, and defines the portions of trunk highways and their junctions served by each SubDistrict. They are derived from the SubDistrict attribute field from the Maintenance Subareas feature class.

    The Minnesota Department of Transportation (MnDOT) divides the state into eight administrative zonal areas call construction districts. Within each construction district, there are a varying number of maintenance subareas. These subareas represent which facility is responsible for maintenance activities on trunk highways, specifically winter maintenance. Note that summer maintenance activates may deviate substantially from these boundaries. Maintenance Subareas is a polygon feature class that represents the area, and defines the portions of trunk highways and their junctions served by each districts subarea.


    Check other metadata records in this package for more information on MnDOT Boundaries

  16. BLM AK Administrative Unit Boundary (Line)

    • catalog.data.gov
    Updated Nov 20, 2024
    + more versions
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    Bureau of Land Management (2024). BLM AK Administrative Unit Boundary (Line) [Dataset]. https://catalog.data.gov/dataset/blm-ak-administrative-unit-boundary-line
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    Dataset updated
    Nov 20, 2024
    Dataset provided by
    Bureau of Land Managementhttp://www.blm.gov/
    Description

    This polygon feature class represents the spatial extent of active BLM Alaska Administrative Unit Boundaries at the State, District, and Field Office levels.

  17. Public Land Survey System - Sections on USDA Forest Service Lands

    • catalog.data.gov
    • gstore.unm.edu
    • +2more
    Updated Dec 2, 2020
    + more versions
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    USDA Forest Service, Southwest Regional Office (Point of Contact) (2020). Public Land Survey System - Sections on USDA Forest Service Lands [Dataset]. https://catalog.data.gov/dataset/public-land-survey-system-sections-on-usda-forest-service-lands
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    Dataset updated
    Dec 2, 2020
    Dataset provided by
    U.S. Department of Agriculture Forest Servicehttp://fs.fed.us/
    Description

    This feature class depicts the boundaries of Land Survey features called sections, defined by the Public Lands Survey System Grid. Normally, 36 sections make up a township. The entire extent of each of these units should be collected, not just the portion on National Forest System lands. This dataset is derived from the USFS Southwestern Region ALP (Automated Lands Program) data Project. This is one of six layers derived from ALP for the purpose of supplying data layers for recourse GIS analysis and data needs within the Forest Service. The six layers are Surface Ownership, Administrative Forest Boundary, District Boundary, Townships, Sections, and Wilderness. There were some gapes in the ALP data so a small portion of this dataset comes from CCF (Cartographic Feature Files) datasets and the USFS Southwestern Region Core Data Project. ALP data is developed from data sources of differing accuracy, scales, and reliability. Where available it is developed from GCDB (Geographic Coordinate Data Base) data. GCDB data is maintained by the Bureau of Land Management in their State Offices. GCDB data is mostly corner data. Not all corners and not all boundaries are available in GCDB so ALP also utilizes many other data sources like CFF data to derive its boundaries. GCDB data is in a constant state of change because land corners are always getting resurveyed. The GCDB data used in this dataset represents a snapshot in time at the time the GCDB dataset was published by the BLM and may not reflect the most current GCDB dataset available. The Forest Service makes no expressed or implied warranty with respect to the character, function, or capabilities of these data. These data are intended to be used for planning and analyses purposes only and are not legally binding with regards to title or location of National Forest System lands.

  18. BLM Eastern States SO Land Use Planning Area Boundary Polygon Arcs

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Nov 20, 2024
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    Bureau of Land Management (2024). BLM Eastern States SO Land Use Planning Area Boundary Polygon Arcs [Dataset]. https://catalog.data.gov/dataset/blm-eastern-states-so-land-use-planning-area-boundary-polygon-arcs
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    Dataset updated
    Nov 20, 2024
    Dataset provided by
    Bureau of Land Managementhttp://www.blm.gov/
    Description

    This polyline feature class represents the arc features that will define the boundaries of the Bureau of Land Management (BLM) Eastern States (ES) Land Use Planning Areas (LUPA) polygons. Land Use Planning Areas are geographic areas within which the BLM makes decisions during land use planning efforts.

  19. v

    VT Data - State Boundary

    • geodata.vermont.gov
    • anrgeodata.vermont.gov
    • +3more
    Updated Jun 17, 2003
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    VT Center for Geographic Information (2003). VT Data - State Boundary [Dataset]. https://geodata.vermont.gov/maps/vt-data-state-boundary-1
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    Dataset updated
    Jun 17, 2003
    Dataset authored and provided by
    VT Center for Geographic Information
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    (Link to Metadata) The BNDHASH dataset depicts Vermont village, town, county, and Regional Planning Commission (RPC) boundaries. It is a composite of generally 'best available' boundaries from various data sources (refer to ARC_SRC and SRC_NOTES attributes). However, this dataset DOES NOT attempt to provide a legally definitive boundary. The layer was originally developed from TBHASH, which was the master VGIS town boundary layer prior to the development and release of BNDHASH. By integrating village, town, county, RPC, and state boundaries into a single layer, VCGI has assured vertical integration of these boundaries and simplified maintenance. BNDHASH also includes annotation text for town, county, and RPC names. BNDHASH includes the following feature classes: 1) BNDHASH_POLY_VILLAGES = Vermont villages 2) BNDHASH_POLY_TOWNS = Vermont towns 3) BNDHASH_POLY_COUNTIES = Vermont counties 4) BNDHASH_POLY_RPCS = Vermont's Regional Planning Commissions 5) BNDHASH_POLY_VTBND = Vermont's state boundary 6) BNDHASH_LINE = Lines on which all POLY feature classes are built The master BNDHASH data is managed as an ESRI geodatabase feature dataset by VCGI. The dataset stores village, town, county, RPC, and state boundaries as seperate feature classes with a set of topology rules which binds the features. This arrangement assures vertical integration of the various boundaries. VCGI will update this layer on an annual basis by reviewing records housed in the VT State Archives - Secretary of State's Office. VCGI also welcomes documented information from VGIS users which identify boundary errors. NOTE - VCGI has NOT attempted to create a legally definitive boundary layer. Instead the idea is to maintain an integrated village/town/county/RPC/state boundary layer which provides for a reasonably accurate representation of these boundaries (refer to ARC_SRC and SRC_NOTES). BNDHASH includes all counties, towns, and villages listed in "Population and Local Government - State of Vermont - 2000" published by the Secretary of State. BNDHASH may include changes endorsed by the Legislature since the publication of this document in 2000 (eg: villages merged with towns). Utlimately the Vermont Secratary of State's Office and the VT Legislature are responsible for maintaining information which accurately describes the locations of these boundaries. BNDHASH should be used for general mapping purposes only. * Users who wish to determine which boundaries are different from the original TBHASH boundaries should refer to the ORIG_ARC field in the BOUNDARY_BNDHASH_LINE (line feature with attributes). Also, updates to BNDHASH are tracked by version number (ex: 2003A). The UPDACT field is used to track changes between versions. The UPDACT field is flushed between versions.

  20. g

    Population by Sex and Social Class, Small Areas, Census 2016, Theme 9.1,...

    • geohive.ie
    • census.geohive.ie
    • +2more
    Updated Aug 1, 2017
    + more versions
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    censuscurator_geohive (2017). Population by Sex and Social Class, Small Areas, Census 2016, Theme 9.1, Ireland, 2016, CSO & Tailte Éireann [Dataset]. https://www.geohive.ie/datasets/population-by-sex-and-social-class-small-areas-census-2016-theme-9-1-ireland-2016-cso-osi
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    Dataset updated
    Aug 1, 2017
    Dataset authored and provided by
    censuscurator_geohive
    Area covered
    Description

    Please be advised that there are issues with the Small Area boundary dataset generalised to 20m which affect Small Area 268014010 in Ballygall D, Dublin City. The Small Area boundary dataset generalised to 20m is in the process of being revised and the updated datasets will be available as soon as the boundaries are amended. This feature layer was created using Census 2016 data produced by the Central Statistics Office (CSO) and Small Areas national boundary data (generalised to 20m) produced by Tailte Éireann. The layer represents Census 2016 theme 9.1, population aged 15+ by sex and social class. Attributes include population breakdown by social class and sex (e.g. skilled manual - males, non-manual - females). Census 2016 theme 9 represents Social Class and Socio-Economic Group. The Census is carried out every five years by the CSO to determine an account of every person in Ireland. The results provide information on a range of themes, such as, population, housing and education. The data were sourced from the CSO. The Small Area Boundaries were created with the following credentials. National boundary dataset. Consistent sub-divisions of an ED. Created not to cross some natural features. Defined area with a minimum number of GeoDirectory building address points. Defined area initially created with minimum of 65 – approx. average of around 90 residential address points. Generated using two bespoke algorithms which incorporated the ED and Townland boundaries, ortho-photography, large scale vector data and GeoDirectory data. Before the 2011 census they were split in relation to motorways and dual carriageways. After the census some boundaries were merged and other divided to maintain privacy of the residential area occupants. They are available as generalised and non generalised boundary sets.

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(2025). Administrative Forest Boundaries - Dataset - CKAN [Dataset]. https://nationaldataplatform.org/catalog/dataset/fdh-administrative-forest-boundaries1

Administrative Forest Boundaries - Dataset - CKAN

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Dataset updated
Mar 6, 2025
Description

An area encompassing all the National Forest System lands administered by an administrative unit. The area encompasses private lands, other governmental agency lands, and may contain National Forest System lands within the proclaimed boundaries of another administrative unit. All National Forest System lands fall within one and only one Administrative Forest Area. This data is intended for read-only use. These data were prepared to describe Forest Service administrative area boundaries. The purpose of the data is to provide display, identification, and analysis tools for determining current boundary information for Forest Service managers, GIS Specialists, and others. The Forest Service has multiple types of boundaries represented by different feature classes (layers): Administrative, Ownership and Proclaimed. 1) ADMINISTRATIVE boundaries (e.g. AdministrativeForest and RangerDistrict feature classes) encompass National Forest System lands managed by an administrative unit. These are dynamic layers that should not be considered "legal" boundaries as they are simply intended to identify the specific organizational units that administer areas. As lands are acquired and disposed, the administrative boundaries are adjusted to expand or shrink accordingly. Please note that ranger districts are sub units of National Forests. An administrative forest boundary can contain one or more Proclaimed National Forests, National Grasslands, Purchase Units, Research and Experimental Areas, Land Utilization Projects and various "Other" Areas. If needed, OWNERSHIP boundaries (e.g. BasicOwnership and SurfaceOwnership feature classes) should be reviewed along with these datasets to determine parcels that are federally managed within the administrative boundaries. 2) OWNERSHIP boundaries (e.g. BasicOwnership and SurfaceOwnership feature classes) represent parcels that are tied to legal transactions of ownership. These are parcels of Federal land managed by the USDA Forest Service. Please note that the BasicOwnership layer is simply a dissolved version of the SurfaceOwnership layer. 3) PROCLAIMED boundaries (e.g. ProclaimedForest and ProclaimedForest_Grassland) encompass areas of National Forest System land that is set aside and reserved from public domain by executive order or proclamation. Please note that the ProclaimedForest layer contains only proclaimed forests while ProclaimedForest_Grassland layer contains both proclaimed forests and proclaimed grasslands. For boundaries that reflect current National Forest System lands managed by an administrative unit, see the ADMINISTRATIVE boundaries (AdministrativeForest and RangerDistrict feature classes). For a visual comparison of the different kinds of USFS boundary datasets maintained by the USFS, see the Forest Service Boundary Comparison map at https://usfs.maps.arcgis.com/apps/CompareAnalysis/index.html?appid=fe7b9f56217949a291356f08cfccb119. USFS boundaries are often referenced in national datasets maintained by other federal agencies. Please note that variations may be found between USFS data and other boundary datasets due to differing update frequencies. PAD-US (Protected Areas Database of the United States), maintained by the U.S. Geological Survey, is a "best available" inventory of protected areas including data provided by managing agencies and organizations including the Forest Service. For more information see https://gapanalysis.usgs.gov/padus/data/metadata/. SMA (Surface Management Agency), maintained by the Bureau of Land Management, depicts Federal land for the United States and classifies this land by its active Federal surface managing agency. It uses data provided by the Forest Service and other agencies, combined with National Regional Offices collection efforts. For more information see https://landscape.blm.gov/geoportal/catalog/search/resource/details.page?uuid=%7B2A8B8906-7711-4AF7-9510-C6C7FD991177%7D.

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