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This ownership dataset utilizes a methodology that results in a federal ownership extent that matches the Federal Responsibility Areas (FRA) footprint from CAL FIRE's State Responsibility Areas for Fire Protection (SRA) data. FRA lands are snapped to county parcel data, thus federal ownership areas will also be snapped. Since SRA Fees were first implemented in 2011, CAL FIRE has devoted significant resources to improve the quality of SRA data. This includes comparing SRA data to data from other federal, state, and local agencies, an annual comparison to county assessor roll files, and a formal SRA review process that includes input from CAL FIRE Units. As a result, FRA lands provide a solid basis as the footprint for federal lands in California (except in the southeastern desert area). The methodology for federal lands involves:
The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .
This dataset was updated April, 2024.This ownership dataset was generated primarily from CPAD data, which already tracks the majority of ownership information in California. CPAD is utilized without any snapping or clipping to FRA/SRA/LRA. CPAD has some important data gaps, so additional data sources are used to supplement the CPAD data. Currently this includes the most currently available data from BIA, DOD, and FWS. Additional sources may be added in subsequent versions. Decision rules were developed to identify priority layers in areas of overlap.Starting in 2022, the ownership dataset was compiled using a new methodology. Previous versions attempted to match federal ownership boundaries to the FRA footprint, and used a manual process for checking and tracking Federal ownership changes within the FRA, with CPAD ownership information only being used for SRA and LRA lands. The manual portion of that process was proving difficult to maintain, and the new method (described below) was developed in order to decrease the manual workload, and increase accountability by using an automated process by which any final ownership designation could be traced back to a specific dataset.The current process for compiling the data sources includes:* Clipping input datasets to the California boundary* Filtering the FWS data on the Primary Interest field to exclude lands that are managed by but not owned by FWS (ex: Leases, Easements, etc)* Supplementing the BIA Pacific Region Surface Trust lands data with the Western Region portion of the LAR dataset which extends into California.* Filtering the BIA data on the Trust Status field to exclude areas that represent mineral rights only.* Filtering the CPAD data on the Ownership Level field to exclude areas that are Privately owned (ex: HOAs)* In the case of overlap, sources were prioritized as follows: FWS > BIA > CPAD > DOD* As an exception to the above, DOD lands on FRA which overlapped with CPAD lands that were incorrectly coded as non-Federal were treated as an override, such that the DOD designation could win out over CPAD.In addition to this ownership dataset, a supplemental _source dataset is available which designates the source that was used to determine the ownership in this dataset.Data Sources:* GreenInfo Network's California Protected Areas Database (CPAD2023a). https://www.calands.org/cpad/; https://www.calands.org/wp-content/uploads/2023/06/CPAD-2023a-Database-Manual.pdf* US Fish and Wildlife Service FWSInterest dataset (updated December, 2023). https://gis-fws.opendata.arcgis.com/datasets/9c49bd03b8dc4b9188a8c84062792cff_0/explore* Department of Defense Military Bases dataset (updated September 2023) https://catalog.data.gov/dataset/military-bases* Bureau of Indian Affairs, Pacific Region, Surface Trust and Pacific Region Office (PRO) land boundaries data (2023) via John Mosley John.Mosley@bia.gov* Bureau of Indian Affairs, Land Area Representations (LAR) and BIA Regions datasets (updated Oct 2019) https://biamaps.doi.gov/bogs/datadownload.htmlData Gaps & Changes:Known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. Additionally, any feedback received about missing or inaccurate data can be taken back to the appropriate source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.24_1: Input datasets this year included numerous changes since the previous version, particularly the CPAD and DOD inputs. Of particular note was the re-addition of Camp Pendleton to the DOD input dataset, which is reflected in this version of the ownership dataset. We were unable to obtain an updated input for tribral data, so the previous inputs was used for this version.23_1: A few discrepancies were discovered between data changes that occurred in CPAD when compared with parcel data. These issues will be taken to CPAD for clarification for future updates, but for ownership23_1 it reflects the data as it was coded in CPAD at the time. In addition, there was a change in the DOD input data between last year and this year, with the removal of Camp Pendleton. An inquiry was sent for clarification on this change, but for ownership23_1 it reflects the data per the DOD input dataset.22_1 : represents an initial version of ownership with a new methodology which was developed under a short timeframe. A comparison with previous versions of ownership highlighted the some data gaps with the current version. Some of these known gaps include several BOR, ACE and Navy lands which were not included in CPAD nor the DOD MIRTA dataset. Our hope for future versions is to refine the process by pulling in additional data sources to fill in some of those data gaps. In addition, any topological errors (like overlaps or gaps) that exist in the input datasets may thus carry over to the ownership dataset. Ideally, any feedback received about missing or inaccurate data can be taken back to the relevant source data where appropriate, so fixes can occur in the source data, instead of just in this dataset.
[Metadata] Description: Government Landownership in the State of Hawaii as of 2022: County, Federal, State, and State DHHL LandsSources: County of Kauai, April, 2022; City & County of Honolulu, April 27, 2022; County of Maui, April, 2022; County of Hawaii, April, 2022; State Department of Hawaiian Home Lands, October, 2022. This dataset was created using ownership information provided by the counties via tax map key parcel layers and ownership tables. Parcels were queried using the "Owner" field for state, county, and federal agency names. State GIS staff verified land ownership using the online service QPublic, the 2022 Department of Hawaiian Home Lands layer and other GIS layers and resources. Where ownership was still unclear, State GIS personnel reached out to appropriate agencies for clarification. Summary fields “majorowner” and “type” were created using additional filters, queries and analysis tools to summarize the data based upon government ownership sector and type. Also see detailed government ownership layer (gov_own_detailed) which is comprised of government land ownership by TMK parcel. The parcel boundaries are intended to provide a visual reference only and do not represent legal or survey level accuracy. Attributes are for assessment purposes only and are subject to change at any time. For additional information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/gov_own.pdf or contact the Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.
This map layer consists of federally owned or administered lands of the United States, Puerto Rico, and the U.S. Virgin Islands. Only areas of 640 acres or more are included. There may be private inholdings within the boundaries of Federal lands in this map layer. This is a revised version of the January 2005 map layer.
For large areas, like Washington State, download as a file geodatabase. Large data sets like this one, for the State of Washington, may exceed the limits for downloading as shape files, excel files, or KML files. For areas less than a county, you may use the map to zoom to your area and download as shape file, excel or KML, if that format is desired.The Boundary layer consists of lines representing the boundaries of Parcels and Legal Descriptions. (See the metadata for those two layers.) Boundary lines are the places that are surveyed in order to delimit the extent of Parcels and Legal Descriptions. The character and accuracy of Boundary locations is held in the attributes of the Points that are at the ends of Boundary lines. All the boundaries of Parcels and Legal Descriptions are covered by a Boundary line. Currently the Boundary layer has little functionality. The only distinction it makes is between upland boundaries and shorelines. In the future Boundary lines will have a richer set of attributes in order to accommodate cartographic needs to distinguish between types of boundaries.WA Boundaries Metadata
OSA web map to view State of Colorado property data
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This data publication contains multiple maps of Puerto Rico scanned at 600 dots per inch: full map scans, scans clipped to mapped areas only, and georeferenced scans of 1:10,000-scale land-use maps from 1950-1951 that were produced by the Rural Land Classification Program of Puerto Rico, a project led by Dr. Clarence F. Jones of Northwestern University. These historical maps classified land use and land cover into 20 different classes, including 13 different types of crops, two classes of forests, four classes of grasslands and other areas, which is a general class for non-rural areas. This package includes maps from 76 out of the 78 municipalities of Puerto Rico, covering 422 quadrangles of a 443-quadrangle grid for mainland Puerto Rico. It excludes the island municipalities of Vieques and Culebra, Mona Island and minor outlying islands.The Rural Land Classification Program of Puerto Rico produced 430 1:10,000-scale maps. That program also produced one island-wide land-use map with more generalized delineations of land use. Previously, Kennaway and Helmer (2007) scanned and georeferenced the island-wide map, and they converted it to vector and raster formats with embedded georeferencing and classification. This data publication contains the higher-resolution maps, which will provide more precise historical context for forests. It will better inform management efforts for the sustainable use of forest lands and to build resilience and resistance to various future disturbances for these and other tropical forest landscapes.
The maps were scanned and georeferenced to help with the planning and application process for the USDA Forest Service (USDA) Forest Legacy Program, a competition-based program administered by the USDA Forest Service in partnership with State agencies to encourage the protection of privately owned forest lands through conservation easements or land purchases. Geospatial products and maps will also be used by personnel at the Department of Natural and Environmental Resources and partners in Non-Governmental Organizations working with the Forest Stewardship Program. This latter program provides technical assistance and forest management plans to private landowners for the conservation and effective management of private forests across the US. The information will provide local historical context on forest change patterns that will enhance the recommendations of forest management practices for private forest landowners. These data will also be useful for urban forest professionals to understand the land legacies as a basis for planning green infrastructure interventions.
Data depict the rural areas of Puerto Rico around 1951 and how they were classified by geographers then. Having it georeferenced allows managers, teachers, students, the public and scientists to compare how these classifications have changed throughout the years. It will allow more precise identification and mapping of the past land use of present forests, forest stand age, and the past juxtaposition of different land uses relative to each other. These factors can affect forest species composition, biodiversity and ecosystem services. Forest stand age, past land-use type and past disturbance type, forest example, help gauge current forest structure, carbon storage, or rates of carbon accumulation. Another example of how the maps are important is for understanding how watersheds have changed through time, which helps assess how forest ecosystem services related to hydrology evolve. These maps will also help gauge how the forests of Puerto Rico are responding to recent disturbances, and how past disturbances over a range of scales relate to these responses.For more information on the Rural Land Classification Program of Puerto Rico, generated maps, and the island-wide land-use map, please see Jones (1952), Jones and Berrios (1956), as well as Kennaway and Helmer (2007).
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The justification and targeting of conservation policy rests on reliable measures of public and private benefits from competing land uses. Advances in Earth system observation and modeling permit the mapping of public ecosystem services at unprecedented scales and resolutions, prompting new proposals for land protection policies and priorities. Data on private benefits from land use are not available at similar scales and resolutions, resulting in a data mismatch with unknown consequences. Here I show that private benefits from land can be quantified at large scales and high resolutions, and that doing so can have important implications for conservation policy models. I develop the first high-resolution estimates of fair market value of private lands in the contiguous United States by training tree-based ensemble models on 6 million land sales. The resulting estimates predict conservation cost with up to 8.5 times greater accuracy than earlier proxies. Studies using coarser cost proxies underestimated conservation costs, especially at the expensive tail of the distribution. This might have led to underestimations of policy budgets by factors of up to 37.5 in recent work. More accurate cost accounting will help policy makers acknowledge the full magnitude of contemporary conservation challenges, and can assist with the targeting of public ecosystem service investments.
NOTE: A more current version of the Protected Areas Database of the United States (PAD-US) is available: PAD-US 3.0 https://doi.org/10.5066/P9Q9LQ4B. The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme (https://communities.geoplatform.gov/ngda-cadastre/). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas using over twenty-five attributes and five feature classes representing the U.S. protected areas network in separate feature classes: Fee (ownership parcels), Designation, Easement, Marine, Proclamation and Other Planning Boundaries. Five additional feature classes include various combinations of the primary layers (for example, Combined_Fee_Easement) to support data management, queries, web mapping services, and analyses. This PAD-US Version 2.1 dataset includes a variety of updates and new data from the previous Version 2.0 dataset (USGS, 2018 https://doi.org/10.5066/P955KPLE ), achieving the primary goal to "Complete the PAD-US Inventory by 2020" (https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-vision) by addressing known data gaps with newly available data. The following list summarizes the integration of "best available" spatial data to ensure public lands and other protected areas from all jurisdictions are represented in PAD-US, along with continued improvements and regular maintenance of the federal theme. Completing the PAD-US Inventory: 1) Integration of over 75,000 city parks in all 50 States (and the District of Columbia) from The Trust for Public Land's (TPL) ParkServe data development initiative (https://parkserve.tpl.org/) added nearly 2.7 million acres of protected area and significantly reduced the primary known data gap in previous PAD-US versions (local government lands). 2) First-time integration of the Census American Indian/Alaskan Native Areas (AIA) dataset (https://www2.census.gov/geo/tiger/TIGER2019/AIANNH) representing the boundaries for federally recognized American Indian reservations and off-reservation trust lands across the nation (as of January 1, 2020, as reported by the federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey) addressed another major PAD-US data gap. 3) Aggregation of nearly 5,000 protected areas owned by local land trusts in 13 states, aggregated by Ducks Unlimited through data calls for easements to update the National Conservation Easement Database (https://www.conservationeasement.us/), increased PAD-US protected areas by over 350,000 acres. Maintaining regular Federal updates: 1) Major update of the Federal estate (fee ownership parcels, easement interest, and management designations), including authoritative data from 8 agencies: Bureau of Land Management (BLM), U.S. Census Bureau (Census), Department of Defense (DOD), U.S. Fish and Wildlife Service (FWS), National Park Service (NPS), Natural Resources Conservation Service (NRCS), U.S. Forest Service (USFS), National Oceanic and Atmospheric Administration (NOAA). The federal theme in PAD-US is developed in close collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/); 2) Complete National Marine Protected Areas (MPA) update: from the National Oceanic and Atmospheric Administration (NOAA) MPA Inventory, including conservation measure ('GAP Status Code', 'IUCN Category') review by NOAA; Other changes: 1) PAD-US field name change - The "Public Access" field name changed from 'Access' to 'Pub_Access' to avoid unintended scripting errors associated with the script command 'access'. 2) Additional field - The "Feature Class" (FeatClass) field was added to all layers within PAD-US 2.1 (only included in the "Combined" layers of PAD-US 2.0 to describe which feature class data originated from). 3) Categorical GAP Status Code default changes - National Monuments are categorically assigned GAP Status Code = 2 (previously GAP 3), in the absence of other information, to better represent biodiversity protection restrictions associated with the designation. The Bureau of Land Management Areas of Environmental Concern (ACECs) are categorically assigned GAP Status Code = 3 (previously GAP 2) as the areas are administratively protected, not permanent. More information is available upon request. 4) Agency Name (FWS) geodatabase domain description changed to U.S. Fish and Wildlife Service (previously U.S. Fish & Wildlife Service). 5) Select areas in the provisional PAD-US 2.1 Proclamation feature class were removed following a consultation with the data-steward (Census Bureau). Tribal designated statistical areas are purely a geographic area for providing Census statistics with no land base. Most affected areas are relatively small; however, 4,341,120 acres and 37 records were removed in total. Contact Mason Croft (masoncroft@boisestate) for more information about how to identify these records. For more information regarding the PAD-US dataset please visit, https://usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual .
This layer includes all public and private protected natural areas (fee-owned and easement), as well as municipal parks for the Chicago Wilderness region. Developed by independent contractor David Holman. Originally released in 2021, but this layer is periodically updated at least annually. This layer is also used in data tracking for recently acquired conservation lands (after filtering out municipal parks).
Wildlands in New England is the first U.S. study to map and characterize within one region all conserved lands that, by design, allow natural processes to unfold with no active management or intervention. These “forever wild lands” include federal Wilderness areas along with diverse public and private natural areas and reserves. Knowing the precise locations of Wildlands, their characteristics, and their protection status is important as both a baseline for advancing conservation initiatives and an urgent call to action for supporting nature and society. Wildlands play a unique role in the integrated approach to conservation and land planning advanced by the Wildlands, Woodlands, Farmlands & Communities (WWF&C) initiative, which calls for: at least 70 percent of the region to be protected forest; Wildlands to occupy at least 10 percent of the land; and all existing farmland to be permanently conserved. This research was conducted by WWF&C partners Harvard Forest (Harvard University), Highstead Foundation, and Northeast Wilderness Trust, in collaboration with over one hundred conservation organizations and municipal, state, and federal agencies. This dataset contains the Geographical Information System (GIS) polygon layer of Wildlands created by this project and used in all analyses for the 2023 report. Another GIS layer will be updated as new Wildlands are brought to our attention or created and will be available at https://wildlandsandwoodlands.org/ for researchers.
This spatial data contains Surface Management Agency (SMA, also sometimes called Land Status) information for Idaho from the Idaho Bureau of Land Management (BLM). For federal government lands, this data displays the managing agency of the surface of the land, which does not mean the agency "owns" the land. SMA is sometimes referred to as "ownership", although this term is inaccurate when describing public lands. This Surface Management Agency data should not be used to depict boundaries (for example National Forest, National Park, National Wildlife Refuge, or Indian Reservation boundaries among others). Attribute information for the federal and private lands are from the BLM Master Title Plats (MTPs), the BLM case files, the BLM Legacy Rehost 2000 (LR2000) database, and corresponding federal Orders and official documents. Please note that because these official sources are strictly used, OTHER NON-BLM FEDERAL AGENCY LANDS MAY NOT BE ATTRIBUTED CORRECTLY unless the proper documents have been filed with the BLM and the land actions have been noted on the MTPs and in LR2000. Starting in the spring of 2011 a field called AGNCY_NAME is present in the data. The AGNCY_NAME field is intended to indicate the managing agency for polygons coded as OTHER in the MGMT_AGNCY field. The AGNCY_NAME field will not be used for the 100K Map Series published by the BLM for use by the public as all agencies in this field are not included in H-1553 Publication Standards Manual Handbook and, therefore, have no BLM Cartographic Standard. Except for polygons coded as OTHER in the MGMT_AGNCY field, all managing agency information in the AGNCY_NAME field should be the same as that of the MGMT_AGNCY field. The only intended difference between the AGNCY_NAME field and the MGMT_AGNCY field is where the MGMT_AGNCY is OTHER. In this case, the AGNCY_NAME will contain an abbreviation for an agency that is not represented in the H-1553 Publication Standards Manual Handbook. Examples of the agencies there are BIA (Bureau of Indian Affairs), USGS (United States Geological Survey), and FAA (Federal Aviation Administration). Attribute information for the State lands is received primarily through cooperation with the Idaho Department of Lands. This information might not reflect all State agency lands completely. A detailed analysis of State owned lands has not been done since June 2011; therefore, recent changes in ownership of State lands may not be reflected. Inclusion of State land information into this dataset is supplemental and should not be viewed as the authoritative source of State lands; please contact State agencies for questions about State lands. This data does not depict land management arrangements between government agencies such as Memorandums of Understanding or other similar agreements. When this data was originally generated in the early 2000's, the primary source of the geometry was the BLM Geographic Coordinate Database (GCDB), if it was available. In areas where GCDB was/is unavailable, the spatial features are taken from a variety of sources including the BLM Idaho Resource Base Data collection, BLM Idaho Master Title Plat AutoCad files, US Geological Survey Digital Line Graphs (DLGs), and US Forest Service Cartographic Feature Files (CFFs), among others (see Process Steps). It should be stressed that the geometry of a feature may not be GCDB-based in the first place, the geometry may shift away from GCDB due to a variety of reasons (topology procedures, automated software processes such as projections, etc.), and the GCDB-based features are not necessarily currently being edited to match improved GCDB. Therefore this data should NOT be considered actual GCDB data. For the latest Idaho GCDB spatial data, please contact the BLM Idaho State Office Cadastral Department at 208-373-4000. The BLM in Idaho creates and maintains this spatial data. This dataset is derived by dissolving based on the "MGMT_AGNCY" field from the master SMA GIS dataset (which is edited often) kept by the BLM Idaho State Office. Please get a fresh copy of this data a couple times a year as the SMA data is continually changing. Official actions that affect the managing agency happen often and changes to correct errors are always being made. Nevada SMA data was acquired from the BLM Nevada web site and clipped to the area that is managed by Idaho BLM Boise District. The data steward approved this dataset in October 2023. For more information contact us at blm_id_stateoffice@blm.gov.
An area depicting a privilege to pass over the land of another in some particular path; usually an easement over the land of another; a strip of land used in this way for railroad and highway purposes, for pipelines or pole lines and for private and public passage. Metadata
The National Conservation Easement Database (NCED) is the first national database of conservation easement information, compiling records from land trusts and public agencies throughout the United States. This public-private partnership brings together national conservation groups, local and regional land trusts, and local, state and federal agencies around a common objective. This effort helps agencies, land trusts, and other organizations plan more strategically, identify opportunities for collaboration, advance public accountability, and raise the profile of what’s happening on-the-ground in the name of conservation.For an introductory tour of the NCED and its benefits check out the story map.
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Contains boundary and attribute information for parcels of public, private and Aboriginal lands in Australia. Data are sourced primarly from government gazette notices, cadastral maps and plans. A …Show full descriptionContains boundary and attribute information for parcels of public, private and Aboriginal lands in Australia. Data are sourced primarly from government gazette notices, cadastral maps and plans. A nominal scale of around 1:5 million and a minimum 50 square kilometre threshold limit for land parcels was used in the generalisation of this product from the National Public and Aboriginal Lands data. Data is suitable for GIS applications. This map shows public and private land tenure, including Indigenous land for the whole of Australia at a scale of 1:4.7 million. The land tenure boundaries depicted on this map generally define broadly classified areas greater than 50 square kilometres. Indigenous land areas between 0.1 and 100 square kilometres are shown more comprehensively by symbols. The information on this map is complemented by statistical tables giving the total area of the land tenure categories for each State and Territory. This map is also available as free vector GIS data, ArcInfo Export, ArcView Shapefile and MapInfo mid/mif. Please direct any corrections or feedback on this map to mapfeedback@ga.gov.au. Product Specifications: Coverage: Australia Currency: Mid 1993 Coordinates: Geographical Datum: AGD66 Projection: Simple Conic on two standard parallels 18S and 36S Medium: Printed map (flat and folded); Data - Free online Forward Program: See Public Lands 2004 PDF map above
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ForestOwn_v1 is a 250-meter spatial resolution raster geospatial dataset of forest ownership of the conterminous United States (CONUS). The dataset was prepared by the Forest Inventory and Analysis (FIA) program, Northern Research Station, Forest Service, United States Department of Agriculture (USDA), and differentiates forest from non-forest land and water, public and private ownership, and the percent of private forest land in corporate ownership. The forest/non-forest land/water classification is derived from the USDA Forest Service's CONUS Forest/Nonforest dataset. Public and private land ownership class is derived from the Protected Areas Database of the United States, Version 1.1 (CBI Edition). Corporate ownership of private forest land is derived from the Forest Service's 2007 Resources Planning Act (RPA) dataset, summarized over the Environmental Protection Agency's Original Environmental Monitoring & Assessment Program (EMAP) grid 648 square kilometer hexagon dataset.The ForestOwn_v1 dataset is designed for conducting geospatial analyses and for producing cartographic products over regional to national geographic extents.A corresponding Research Map (RMAP) has been produced to cartographically portray this dataset.
Original metadata date was 02/09/2011. Minor metadata updates were made on 05/10/2013, 04/16/2014, 12/21/2016, and 02/06/2017. Additional minor metadata updates were made on 04/20/2023.
On 07/23/2020 a newer version of these data became available (Sass et al. 2020).
description: This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The second division of the PLSS is quarter, quarter-quarter, sixteenth or government lot division of the PLSS. The second and third divisions are combined into this feature class as an intentional de-normalization of the PLSS hierarchical data. The polygons in this feature class represent the smallest division to the sixteenth that has been defined for the first division. For example In some cases sections have only been divided to the quarter. Divisions below the sixteenth are in the Special Survey or Parcel Feature Class. In the Public Land Survey System a Township refers to a unit of land, that is nominally six miles on a side, usually containing 36 sections.; abstract: This data represents the GIS Version of the Public Land Survey System including both rectangular and non-rectangular survey data. The rectangular survey data are a reference system for land tenure based upon meridian, township/range, section, section subdivision and government lots. The non-rectangular survey data represent surveys that were largely performed to protect and/or convey title on specific parcels of land such as mineral surveys and tracts. The data are largely complete in reference to the rectangular survey data at the level of first division. However, the data varies in terms of granularity of its spatial representation as well as its content below the first division. Therefore, depending upon the data source and steward, accurate subdivision of the rectangular data may not be available below the first division and the non-rectangular minerals surveys may not be present. At times, the complexity of surveys rendered the collection of data cost prohibitive such as in areas characterized by numerous, overlapping mineral surveys. In these situations, the data were often not abstracted or were only partially abstracted and incorporated into the data set. These PLSS data were compiled from a broad spectrum or sources including federal, county, and private survey records such as field notes and plats as well as map sources such as USGS 7 minute quadrangles. The metadata in each data set describes the production methods for the data content. This data is optimized for data publication and sharing rather than for specific "production" or operation and maintenance. A complete PLSS data set includes the following: PLSS Townships, First Divisions and Second Divisions (the hierarchical break down of the PLSS Rectangular surveys) PLSS Special surveys (non-rectangular components of the PLSS) Meandered Water, Corners, Metadata at a Glance (which identified last revised date and data steward) and Conflicted Areas (known areas of gaps or overlaps or inconsistencies). The Entity-Attribute section of this metadata describes these components in greater detail. The second division of the PLSS is quarter, quarter-quarter, sixteenth or government lot division of the PLSS. The second and third divisions are combined into this feature class as an intentional de-normalization of the PLSS hierarchical data. The polygons in this feature class represent the smallest division to the sixteenth that has been defined for the first division. For example In some cases sections have only been divided to the quarter. Divisions below the sixteenth are in the Special Survey or Parcel Feature Class. In the Public Land Survey System a Township refers to a unit of land, that is nominally six miles on a side, usually containing 36 sections.
The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme (https://communities.geoplatform.gov/ngda-cadastre/). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all public and nonprofit lands and waters. Most are public lands owned in fee (the owner of the property has full and irrevocable ownership of the land); however, long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas using over twenty-five attributes and five feature classes representing the U.S. protected areas network in separate feature classes: Fee (ownership parcels), Designation, Easement, Marine, Proclamation and Other Planning Boundaries. Five additional feature classes include various combinations of the primary layers (for example, Combined_Fee_Easement) to support data management, queries, web mapping services, and analyses. This PAD-US Version 2.1 dataset includes a variety of updates and new data from the previous Version 2.0 dataset (USGS, 2018 https://doi.org/10.5066/P955KPLE ), achieving the primary goal to "Complete the PAD-US Inventory by 2020" (https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/pad-us-vision) by addressing known data gaps with newly available data. The following list summarizes the integration of "best available" spatial data to ensure public lands and other protected areas from all jurisdictions are represented in PAD-US, along with continued improvements and regular maintenance of the federal theme. Completing the PAD-US Inventory: 1) Integration of over 75,000 city parks in all 50 States (and the District of Columbia) from The Trust for Public Land's (TPL) ParkServe data development initiative (https://parkserve.tpl.org/) added nearly 2.7 million acres of protected area and significantly reduced the primary known data gap in previous PAD-US versions (local government lands). 2) First-time integration of the Census American Indian/Alaskan Native Areas (AIA) dataset (https://www2.census.gov/geo/tiger/TIGER2019/AIANNH) representing the boundaries for federally recognized American Indian reservations and off-reservation trust lands across the nation (as of January 1, 2020, as reported by the federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey) addressed another major PAD-US data gap. 3) Aggregation of nearly 5,000 protected areas owned by local land trusts in 13 states, aggregated by Ducks Unlimited through data calls for easements to update the National Conservation Easement Database (https://www.conservationeasement.us/), increased PAD-US protected areas by over 350,000 acres. Maintaining regular Federal updates: 1) Major update of the Federal estate (fee ownership parcels, easement interest, and management designations), including authoritative data from 8 agencies: Bureau of Land Management (BLM), U.S. Census Bureau (Census), Department of Defense (DOD), U.S. Fish and Wildlife Service (FWS), National Park Service (NPS), Natural Resources Conservation Service (NRCS), U.S. Forest Service (USFS), National Oceanic and Atmospheric Administration (NOAA). The federal theme in PAD-US is developed in close collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/); 2) Complete National Marine Protected Areas (MPA) update: from the National Oceanic and Atmospheric Administration (NOAA) MPA Inventory, including conservation measure ('GAP Status Code', 'IUCN Category') review by NOAA; Other changes: 1) PAD-US field name change - The "Public Access" field name changed from 'Access' to 'Pub_Access' to avoid unintended scripting errors associated with the script command 'access'. 2) Additional field - The "Feature Class" (FeatClass) field was added to all layers within PAD-US 2.1 (only included in the "Combined" layers of PAD-US 2.0 to describe which feature class data originated from). 3) Categorical GAP Status Code default changes - National Monuments are categorically assigned GAP Status Code = 2 (previously GAP 3), in the absence of other information, to better represent biodiversity protection restrictions associated with the designation. The Bureau of Land Management Areas of Environmental Concern (ACECs) are categorically assigned GAP Status Code = 3 (previously GAP 2) as the areas are administratively protected, not permanent. More information is available upon request. 4) Agency Name (FWS) geodatabase domain description changed to U.S. Fish and Wildlife Service (previously U.S. Fish & Wildlife Service). 5) Select areas in the provisional PAD-US 2.1 Proclamation feature class were removed following a consultation with the data-steward (Census Bureau). Tribal designated statistical areas are purely a geographic area for providing Census statistics with no land base. Most affected areas are relatively small; however, 4,341,120 acres and 37 records were removed in total. Contact Mason Croft (masoncroft@boisestate) for more information about how to identify these records. For more information regarding the PAD-US dataset please visit, https://usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the Online PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual. Some of the the American Indian reservations (AIR) polygons are based on the 2010 USA Indian Reservations dataset distributed by USGS (https://www.sciencebase.gov/catalog/item/4f4e4a2ee4b07f02db61576c).
The Maryland Department of Natural Resources (DNR) manages over 446,000 acres of public lands and protected open space in the state. The DNR Lands data (part of Technology Toolbox Protected Lands data set) consists of mapped information that represent those lands that are owned by the Maryland Department of Natural Resources. Utilizing various land protection programs and funding sources, the Maryland Department of Natural Resources has preserved environmentally important lands through the use of perpetual conservation easements. The Forest Legacy Program is designed to identify and protect environmentally important forest lands that are threatened by present or future conversion to non-forest use through the use of perpetual conservation easements between willing sellers and willing buyers. Only private forest land in a Forest Legacy Area is eligible for the program. Marylands Conservation Reserve Enhancement Program (CREP) has helped thousands of Maryland landowners plant streamside buffers, establish wetlands, protect highly erodible land, and create wildlife habitat. The State of Maryland has entered into a memorandum of Agreement with USDA authorizing the State of Maryland to continue the voluntary program for the purchase of perpetual easements for Conservation Reserve Program (CRP) land. A perpetual CREP easement is a written legal agreement between a landowner and the State of Maryland in which there is an acquired permanent interest in the land to install or maintain conservation practices that protect water quality and natural resources. The Maryland Department of Natural Resources (DNR) administers the CREP easement program. DNR is also assisted by a number of local governments and non-government organization sponsors.Data from individual county and state records were used in production of DNR Lands. Specific Project boundary maps, subdivision plats and deed plots were used to create boundary polygons. In the case of the Chesapeake Forest properties, original property boundary data was received from the Chesapeake Corporation. The horizontal accuracy of these lines is being continually improved.The Department of Natural Resources makes no warranty, expressed or implied, as to the use or appropriateness of Spatial Data, and there are no warranties of merchantability or fitness for a particular purpose or use. The information contained in Spatial Data is from publicly available sources, but no representation is made as to the accuracy or completeness of Spatial Data. The Department of Natural Resources shall not be subject to liability for human error, error due to software conversion, defect, or failure of machines, or any material used in the connection with the machines, including tapes, disks, CD-ROMs or DVD-ROMs and energy. The Department of Natural Resources shall not be liable for any lost profits, consequential damages, or claims against the Department of Natural Resources by third parties. The liability of the Department of Natural Resources for damage regardless of the form of the action shall not exceed any distribution fees that may have been paid in obtaining Spatial Data.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Feature Service Link:https://geodata.md.gov/imap/rest/services/Environment/MD_ProtectedLands/FeatureServer/0
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This ownership dataset utilizes a methodology that results in a federal ownership extent that matches the Federal Responsibility Areas (FRA) footprint from CAL FIRE's State Responsibility Areas for Fire Protection (SRA) data. FRA lands are snapped to county parcel data, thus federal ownership areas will also be snapped. Since SRA Fees were first implemented in 2011, CAL FIRE has devoted significant resources to improve the quality of SRA data. This includes comparing SRA data to data from other federal, state, and local agencies, an annual comparison to county assessor roll files, and a formal SRA review process that includes input from CAL FIRE Units. As a result, FRA lands provide a solid basis as the footprint for federal lands in California (except in the southeastern desert area). The methodology for federal lands involves: