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.

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.

(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.

This digital, geographically referenced data set was developed to identify the county boundaries of the Des Moines 9 County Regional GIS community. This feature class is one many feature classes developed for and maintained by the Des Moines Area Regional GIS for the purpose of performing internal and external functions of the local government it covers.

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

(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.

GDB Version: ArcGIS Pro 3.3Additional Resources:Shapefile DownloadShapefile Download (Clipped to VIMS shoreline)Administrative Boundary Data Standard REST Endpoint (Unclipped) - REST Endpoint (Clipped)The Administrative Boundary feature classes represent the best available boundary information in Virginia. VGIN initially sought to develop an improved city, county, and town boundary dataset in late 2013, spurred by response of the Virginia Administrative Boundaries Workgroup community. The feature class initially started from an extraction of features from the Census TIGER dataset for Virginia. VGIN solicited input from localities in Virginia through the Road Centerlines data submission process as well as through public forums such as the Virginia Administrative Boundaries Workgroup and VGIN listservs. Data received were analyzed and incorporated into the appropriate feature classes where locality data were a superior representation of boundaries. Administrative Boundary geodatabase and shapefiles are unclipped to hydrography features by default. The clipped to hydro dataset is included as a separate shapefile download below.

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 open space 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, permanent and 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 U.S. 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 thirty-six attributes and five separate feature classes representing the U.S. protected areas network: Fee (ownership parcels), Designation, Easement, Marine, Proclamation and Other Planning Boundaries. An additional Combined feature class includes the full PAD-US inventory to support data management, queries, web mapping services, and analyses. The Feature Class (FeatClass) field in the Combined layer allows users to extract data types as needed. A Federal Data Reference file geodatabase lookup table (PADUS3_0Combined_Federal_Data_References) facilitates the extraction of authoritative federal data provided or recommended by managing agencies from the Combined PAD-US inventory. This PAD-US Version 3.0 dataset includes a variety of updates from the previous Version 2.1 dataset (USGS, 2020, https://doi.org/10.5066/P92QM3NT ), achieving goals to: 1) Annually update and improve spatial data representing the federal estate for PAD-US applications; 2) Update state and local lands data as state data-steward and PAD-US Team resources allow; and 3) Automate data translation efforts to increase PAD-US update efficiency. 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 the PAD-US (other data were transferred from PAD-US 2.1). Federal updates - The USGS remains committed to updating federal fee owned lands data and major designation changes in annual PAD-US updates, where authoritative data provided directly by managing agencies are available or alternative data sources are recommended. The following is a list of updates or revisions associated with the federal estate: 1) Major update of the Federal estate (fee ownership parcels, easement interest, and management designations where available), including authoritative data from 8 agencies: Bureau of Land Management (BLM), U.S. Census Bureau (Census Bureau), 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), and 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) Improved the representation (boundaries and attributes) of the National Park Service, U.S. Forest Service, Bureau of Land Management, and U.S. Fish and Wildlife Service lands, in collaboration with agency data-stewards, in response to feedback from the PAD-US Team and stakeholders. 3) Added a Federal Data Reference file geodatabase lookup table (PADUS3_0Combined_Federal_Data_References) to the PAD-US 3.0 geodatabase to facilitate the extraction (by Data Provider, Dataset Name, and/or Aggregator Source) of authoritative data provided directly (or recommended) by federal managing agencies from the full PAD-US inventory. A summary of the number of records (Frequency) and calculated GIS Acres (vs Documented Acres) associated with features provided by each Aggregator Source is included; however, the number of records may vary from source data as the "State Name" standard is applied to national files. The Feature Class (FeatClass) field in the table and geodatabase describe the data type to highlight overlapping features in the full inventory (e.g. Designation features often overlap Fee features) and to assist users in building queries for applications as needed. 4) Scripted the translation of the Department of Defense, Census Bureau, and Natural Resource Conservation Service source data into the PAD-US format to increase update efficiency. 5) Revised conservation measures (GAP Status Code, IUCN Category) to more accurately represent protected and conserved areas. For example, Fish and Wildlife Service (FWS) Waterfowl Production Area Wetland Easements changed from GAP Status Code 2 to 4 as spatial data currently represents the complete parcel (about 10.54 million acres primarily in North Dakota and South Dakota). Only aliquot parts of these parcels are documented under wetland easement (1.64 million acres). These acreages are provided by the U.S. Fish and Wildlife Service and are referenced in the PAD-US geodatabase Easement feature class 'Comments' field. State updates - The USGS is committed to building capacity in the state data-steward network and the PAD-US Team to increase the frequency of state land updates, as resources allow. The USGS supported efforts to significantly increase state inventory completeness with the integration of local parks data in the PAD-US 2.1, and developed a state-to-PAD-US data translation script during PAD-US 3.0 development to pilot in future updates. Additional efforts are in progress to support the technical and organizational strategies needed to increase the frequency of state updates. The PAD-US 3.0 included major updates to the following three states: 1) California - added or updated state, regional, local, and nonprofit lands data from the California Protected Areas Database (CPAD), managed by GreenInfo Network, and integrated conservation and recreation measure changes following review coordinated by the data-steward with state managing agencies. Developed a data translation Python script (see Process Step 2 Source Data Documentation) in collaboration with the data-steward to increase the accuracy and efficiency of future PAD-US updates from CPAD. 2) Virginia - added or updated state, local, and nonprofit protected areas data (and removed legacy data) from the Virginia Conservation Lands Database, provided by the Virginia Department of Conservation and Recreation's Natural Heritage Program, and integrated conservation and recreation measure changes following review by the data-steward. 3) West Virginia - added or updated state, local, and nonprofit protected areas data provided by the West Virginia University, GIS Technical Center. For more information regarding the PAD-US dataset please visit, https://www.usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the PAD-US Data Manual available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual . A version history of PAD-US updates is summarized below (See https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-history for more information): 1) First posted - April 2009 (Version 1.0 - available from the PAD-US: Team pad-us@usgs.gov). 2) Revised - May 2010 (Version 1.1 - available from the PAD-US: Team pad-us@usgs.gov). 3) Revised - April 2011 (Version 1.2 - available from the PAD-US: Team pad-us@usgs.gov). 4) Revised - November 2012 (Version 1.3) https://doi.org/10.5066/F79Z92XD 5) Revised - May 2016 (Version 1.4) https://doi.org/10.5066/F7G73BSZ 6) Revised - September 2018 (Version 2.0) https://doi.org/10.5066/P955KPLE 7) Revised - September 2020 (Version 2.1) https://doi.org/10.5066/P92QM3NT 8) Revised - January 2022 (Version 3.0) https://doi.org/10.5066/P9Q9LQ4B Comparing protected area trends between PAD-US versions is not recommended without consultation with USGS as many changes reflect improvements to agency and organization GIS systems, or conservation and recreation measure classification, rather than actual changes in protected area acquisition on the ground.

The NSW Administrative Boundaries Web Service is a dynamic map of administrative and property boundaries. Administrative Areas Boundaries depict a polygon feature class within the NSW Digital Cadastral Database maintained by LPI. The administrative boundaries provided through this web service includes: Counties, Suburbs, Parishes, Local Government Areas, State Forests, National Parks, State Electoral Districts. For detailed information, for each individual dataset contained in this web services, please see the Digital Cadastre Database Dictionary published at http://www.lpi.nsw.gov.au/mapping_and_imagery/spatial_data.

This web service allows users to easily integrate NSW Administrative Boundaries into OGC compliant spatial platforms and applications. Administrative Boundaries can be used to aggregate information for analytical purposes and analyse time series trends. Administrative boundary data in combination with geo-coded address data, demographic information and agency specific business information underpins the ability to perform high quality spatial analysis.

This feature class represents the boundaries of the City of Austin Neighborhood Planning Areas (NPA). The status of these areas, as directed by City Council, can either be plan approved, planning underway/set to begin, future planning area, or non-neighborhood planning area. Future planning area boundaries may change before they are set by the City Council to begin. See https://www.austintexas.gov/department/planning-and-zoning/plans for more information.

Terms of Use This product is for informational purposes and may not have been prepared for or be suitable for legal, engineering, or surveying purposes. It does not represent an on-the-ground survey and represents only the approximate relative location of property boundaries. This product has been produced by the City of Austin for the sole purpose of geographic reference. No warranty is made by the City of Austin regarding specific accuracy or completeness.

Spatial analysis and statistical summaries of the Protected Areas Database of the United States (PAD-US) provide land managers and decision makers with a general assessment of management intent for biodiversity protection, natural resource management, and recreation access across the nation. The PAD-US 4.0 Combined Fee, Designation, Easement feature class (with Military Lands and Tribal Areas from the Proclamation and Other Planning Boundaries feature class) was modified to remove overlaps, avoiding overestimation in protected area statistics and to support user needs. A Python scripted process ("PADUS4_0_VectorAnalysis_Script_Python3.zip") associated with this data release prioritized overlapping designations (e.g. Wilderness within a National Forest) based upon their relative biodiversity conservation status (e.g. GAP Status Code 1 over 2), public access values (in the order of Closed, Restricted, Open, Unknown), and geodatabase load order (records are deliberately organized in the PAD-US full inventory with fee owned lands loaded before overlapping management designations, and easements). Vector Analysis ("PADUS4_0VectorAnalysis_GAP_PADUS_Only_ClipCENSUS.zip") data was created by clipping the PAD-US 4.0 Spatial Analysis and Statistics results to the Census state boundary file to define the extent and serve as a common denominator for statistical summaries. Boundaries of interest to stakeholders (State, Department of the Interior Region, Congressional District, County, EcoRegions I-IV, Urban Areas, Landscape Conservation Cooperative) were incorporated into separate geodatabase feature classes to support various data summaries ("PADUS4_0_VectorAnalysisFile_OtherExtents_ClipCENSUS2022.zip"). Comma-separated Value (CSV) tables ("PADUS4_0_SummaryStatistics_TabularData_CSV.zip") provided as an alternative format and enable users to explore and download summary statistics of interest from the PAD-US Statistics Dashboard ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-statistics ). In addition, a "flattened" version of the PAD-US 4.0 combined file without other extent boundaries ("PADUS4_0VectorAnalysis_GAP_PADUS_Only_ClipCENSUS.zip") allow for other applications that require a representation of overall protection status without overlapping designation boundaries. The "PADUS4_0VectorAnalysis_State_Clip_CENSUS2022" feature class ("PADUS4_0_VectorAnalysisFile_OtherExtents_ClipCENSUS2022.gdb") is the source of the PAD-US 4.0 Raster Analysis child item. Note, the PAD-US inventory is now considered functionally complete with the vast majority of land protection types represented in some manner, while work continues to maintain updates and improve data quality (see inventory completeness estimates at: http://www.protectedlands.net/data-stewards/ ). In addition, changes in protected area status between versions of the PAD-US may be attributed to improving the completeness and accuracy of the spatial data more than actual management actions or new acquisitions. USGS provides no legal warranty for the use of this data. While PAD-US is the official aggregation of protected areas ( https://ngda-portfolio-community-geoplatform.hub.arcgis.com/pages/portfolio ), agencies are the best source of their lands data.

This feature class represents the product of merge and dissolve operations in ArcGIS with the inputs being the individually submitted EIS boundary datasets. EIS boundaries were developed by each individual EIS in coordination with the Division of Decision Support, Planning and NEPA (WO 210). EIS boundary submissions occurred between Sept. 25th and Sept. 30th, 2013. No modifications to the source data have been made other than to add and calculate the "EIS Name" field. The following EIS boundaries are included in the dataset: 9-Plan, Bighorn Basin, Billings/Pompey's Pillar NM, Buffalo, HiLine, Idaho and SW Montana, Lander, Lewistown, Miles City, NW Colorado, Nevada and NE California, North Dakota, Oregon, South Dakota, Upper Missouri River Breaks NM, and Utah.

Description for i03_DAU_county_cnty2018 is as follows:Detailed Analysis Unit-(DAU) Convergence via County Boundary cnty18_1 for Cal-Fire, (See metadata for CAL-FIRE cnty18_1), State of California.The existing DAU boundaries were aligned with cnty18_1 feature class.Originally a collaboration by Department of Water Resources, Region Office personnel, Michael L. Serna, NRO, Jason Harbaugh - NCRO, Cynthia Moffett - SCRO and Robert Fastenau - SRO with the final merge of all data into a cohesive feature class to create i03_DAU_COUNTY_cnty24k09 alignment which has been updated to create i03_DAU_COUNTY_cnty18_1.This version was derived from a preexisting “dau_v2_105, 27, i03_DAU_COUNTY_cnty24k09” Detailed Analysis Unit feature class's and aligned with Cal-Fire's 2018 boundary.Manmade structures such as piers and breakers, small islands and coastal rocks have been removed from this version. Inlets waters are listed on the coast only.These features are reachable by County\DAU. This allows the county boundaries, the DAU boundaries and the State of California Boundary to match Cal-Fire cnty18_1.DAU BackgroundThe first investigation of California's water resources began in 1873 when President Ulysses S. Grant commissioned an investigation by Colonel B. S. Alexander of the U.S. Army Corps of Engineers. The state followed with its own study in 1878 when the State Engineer's office was created and filled by William Hammond Hall. The concept of a statewide water development project was first raised in 1919 by Lt. Robert B. Marshall of the U.S. Geological Survey.In 1931, State Engineer Edward Hyatt introduced a report identifying the facilities required and the economic means to accomplish a north-to-south water transfer. Called the "State Water Plan", the report took nine years to prepare. To implement the plan, the Legislature passed the Central Valley Act of 1933, which authorized the project. Due to lack of funds, the federal government took over the CVP as a public works project to provide jobs and its construction began in 1935.In 1945, the California Legislature authorized an investigation of statewide water resources and in 1947, the California Legislature requested that an investigation be conducted of the water resources as well as present and future water needs for all hydrologic regions in the State. Accordingly, DWR and its predecessor agencies began to collect the urban and agricultural land use and water use data that serve as the basis for the computations of current and projected water uses.The work, conducted by the Division of Water Resources (DWR’s predecessor) under the Department of Public Works, led to the publication of three important bulletins: Bulletin 1 (1951), "Water Resources of California," a collection of data on precipitation, unimpaired stream flows, flood flows and frequency, and water quality statewide; Bulletin 2 (1955), "Water Utilization and Requirements of California," estimates of water uses and forecasts of "ultimate" water needs; and Bulletin 3 (1957), "The California Water Plan," plans for full practical development of California’s water resources, both by local projects and a major State project to meet the State's ultimate needs. (See brief addendum below* “The Development of Boundaries for Hydrologic Studies for the Sacramento Valley Region”)DWR subdivided California into study areas for planning purposes. The largest study areas are the ten hydrologic regions (HR), corresponding to the State’s major drainage basins. The next levels of delineation are the Planning Areas (PA), which in turn are composed of multiple detailed analysis units (DAU). The DAUs are often split by county boundaries, so are the smallest study areas used by DWR.The DAU/counties are used for estimating water demand by agricultural crops and other surfaces for water resources planning. Under current guidelines, each DAU/County has multiple crop and land-use categories. Many planning studies begin at the DAU or PA level, and the results are aggregated into hydrologic regions for presentation.Since 1950 DWR has conducted over 250 land use surveys of all or parts of California's 58 counties. Early land use surveys were recorded on paper maps of USGS 7.5' quadrangles. In 1986, DWR began to develop georeferenced digital maps of land use survey data, which are available for download. Long term goals for this program is to survey land use more frequently and efficiently using satellite imagery, high elevation digital imagery, local sources of data, and remote sensing in conjunction with field surveys.There are currently 58 counties and 278 DAUs in California.Due to some DAUs being split by county lines, the total number of DAU’s identifiable via DAU by County is 782.**ADDENDUM**The Development of Boundaries for Hydrologic Studies for the Sacramento Valley Region[Detailed Analysis Units made up of a grouping of the Depletion Study Drainage Areas (DSA) boundaries occurred on the Eastern Foothills and Mountains within the Sacramento Region. Other DSA’s were divided into two or more DAU’s; for example, DSA 58 (Redding Basin) was divided into 3 DAU’s; 143,141, and 145. Mountain areas on both the east and west side of the Sacramento River below Shasta Dam went from ridge top to ridge top, or topographic highs. If available, boundaries were set adjacent to stream gages located at the low point of rivers and major creek drainages.Later, as the DAU’s were developed, some of the smaller watershed DSA boundaries in the foothill and mountain areas were grouped. The Pit River DSA was split so water use in the larger valleys (Alturas area, Big Valley, Fall River Valley, Hat Creek) could be analyzed. A change in the boundary of the Sacramento Region mountain area occurred at this time when Goose Lake near the Oregon State Line was included as part of the Sacramento Region.The Sacramento Valley Floor hydrologic boundary was at the edge of the alluvial soils and slightly modified to follow the water bearing sediments to a depth of 200 feet or more. Stream gages were located on incoming streams and used as an exception to the alluvial soil boundary. Another exception to the alluvial boundary was the inclusion of the foothills between Red Bluff and the Redding Basin. Modifications of the valley floor exterior boundary were made to facilitate analysis; some areas at the northern end of the valley followed section lines or other established boundaries.Valley floor boundaries, as originally shown in Bulletin 2, Water Utilization and Requirements of California, 1955 were based on physical topographic features such as ridges even if they only rise a few feet between basins and/or drainage areas. A few boundaries were based on drainage canals. The Joint DWR-USBR Depletion Study Drainage Areas (DSA) used drainage areas where topographic highs drained into one drainage basin. Some areas were difficult to study, particularly in areas transected by major rivers. Depletion Study Drainage Areas containing large rivers were separated into two DAU’s; one on each side of the river. This made it easier to analyze water source, water supply, and water use and drainage outflow from the DAU.Many of the DAUs that consist of natural drainage basins have stream gages located at outfall gates, which provided an accurate estimate of water leaving the unit. Detailed Analysis Units based on political boundaries or other criteria are much more difficult to analyze than those units that follow natural drainage basins.]**END ADDENDUM**.............................................................................................................................................cnty18_1 metadata Summary:(*See metadata for CAL-FIRE cnty18_1). CAL-FIRE cnty18_1 boundary feature class is used for cartographic purposes, for generating statistical data, and for clipping data. Ideally, state and federal agencies should be using the same framework data for common themes such as county boundaries. This layer provides an initial offering as "best available" at 1:24,000 scale.cnty18_1 metadata Description:(*See metadata for CAL-FIRE cnty18_1).cnty18_1 metadata Credits:CAL-FIRE cnty18_1 metadata comment:This specific dataset represents the full detailed county dataset with all coding (islands, inlets, constructed features, etc.). The user has the freedom to use this coding to create definition queries, symbolize, or dissolve to create a more generalized dataset as needed.In November 2015, the dataset was adjusted to include a change in the Yuba-Placer county boundary from 2010 that was not yet included in the 14_1 version of the dataset (ord. No. 5546-B). This change constitutes the difference between the 15_1 and 14_1 versions of this dataset.In March 2018, the dataset was adjusted to include a legal boundary change between Santa Clara and Santa Cruz Counties (December 11, 1998) as stated in Resolution No. 98-11 (Santa Clara) and Resolution No. 432-98 (Santa Cruz). This change constitutes the difference between the 18_1 and 15_1 versions of this dataset.(*See metadata for CAL-FIRE cnty18_1). - U.S. Bureau of Reclamation, California Department of Conservation, California Department of Fish and Game, California Department of Forestry and Fire protection

Source:

Creator: R.A. Fisher Donor: Michael Marshall (MARSHALL%PLU '@' io.arc.nasa.gov)

Data Set Information:

This is perhaps the best known database to be found in the pattern recognition literature. Fisher's paper is a classic in the field and is referenced frequently to this day. (See Duda & Hart, for example.) The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly separable from each other.

Predicted attribute: class of iris plant.

This is an exceedingly simple domain.

This data differs from the data presented in Fishers article (identified by Steve Chadwick, spchadwick '@' espeedaz.net ). The 35th sample should be: 4.9,3.1,1.5,0.2,"Iris-setosa" where the error is in the fourth feature. The 38th sample: 4.9,3.6,1.4,0.1,"Iris-setosa" where the errors are in the second and third features.

Attribute Information:

1. sepal length in cm
2. sepal width in cm
3. petal length in cm
4. petal width in cm
5. class: -- Iris Setosa -- Iris Versicolour -- Iris Virginica

Relevant Papers:

Fisher,R.A. "The use of multiple measurements in taxonomic problems" Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions to Mathematical Statistics" (John Wiley, NY, 1950).

Duda,R.O., & Hart,P.E. (1973) Pattern Classification and Scene Analysis. (Q327.D83) John Wiley & Sons. ISBN 0-471-22361-1. See page 218.

Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System Structure and Classification Rule for Recognition in Partially Exposed Environments". IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-2, No. 1, 67-71.

Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule". IEEE Transactions on Information Theory, May 1972, 431-433.

See also: 1988 MLC Proceedings, 54-64.

Parcels affected by the adoption of the 2015 International Wildland Urban-Interface Code (WUIC), which was adopted by Austin City Council April9, 2020, and implementation beginning January 1st, 2021. Parcels that are within 1.5 miles of a wildland area greater than 750 acres and parcels within 150 feet of a wildland area greater than 40 acres are wildland_urban_interface_code parcels. Parcels designated as "preserves" have been removed and are not subject to the WUI code.Dataset was created in 2020 by Austin Fire Department Wildfire Division. It was derived from the most recent Travis County Appraisal District (TCAD) Parcels, and queried based upon their planar distance to wildland areas. Wildlands are defined as undeveloped continuous areas,. The wildlands feature class is maintained by the Austin Fire Department and is derived from the City of Austin Planimetric dataset, also known as impervious cover data, and are updated every two years. ArcGIS Pro version 2 software was used to create this dataset. The data is meant to be ingested by a GIS system. Changes to the City of Austin & LTD jurisdiction warrant an update to this dataset. The data is scheduled to be updated every two years.Included in the attributes are parcel condition variables that determine the parcel's "fire hazard severity' class. These include the composite score of three variables: slope score, fuel score, and WUI class (proximity). Slope score was determined by the average degree slope of the area within each parcel and classified as less than 10%, 10% to 25%, or greater then 25%. Fuel score was determined by the average fuel class area within each parcels as defined by the Austin Travis County Community Wildfire Protection Plan (CWPP) and classified as light, medium, or heavy fuels. Proximity class was defined by the proximity of each parcel to wildlands, either as within 1.5 miles of wildlands greater than 750 acres, or within 150 feet of wildlands greater than 40 acres.Description of data fieldsGLOBALID_1 = Used for Global IdentificationOBJECTID = Object IdentificationSLOPE_DEGREE = The average slope of each parcel in degreesFIRE_HAZARD_SEVERITY = The "fire hazard severity" class of each parcelPROXIMITY_CLASS = The proximity class of each parcelSLOPE_CLASS = The slope classification of each parcelFUEL_CLASS = The fuel class of each parcelCREATED_BY = Creators nameCREATED_DATE = Date createdMODIFIED_BY = Modifiers nameMODIFIED_DATE = Date modifiedUNIQUE_ID = Unique Identification number (mirror object id)Shape_Area = Shape areaShape_Length = Shape lengthIteration ID: Parcels_AustinLTD4 2020Contact: Steven Casebeer at Steven.casebeer@austintexas.gov | Austin Fire Department Wildfire Division

This data set is available from the Alaska Department of Natural Resources Division of Oil and Gas and was developed to provide the general public with easy access to oil and gas leasing information. It is not a legal record and is for informational purposes only. Source documents remain the official record. The Areawide Boundary feature class provides individual outlines for the five Areawide lease sale areas for the State of Alaska: the Alaska Peninsula, Cook Inlet, North Slope, North Slope Foothills and Beaufort Sea. The purpose of Areawide leasing is to provide an established time each year that the state will offer for lease all available acreage within the five geographical regions. The leasing program is governed by Alaska Statute 38.05.035. PLEASE NOTE - These boundaries do not reflect tracts excluded from a particular lease sale. The user must refer to the sale announcement and possibly other documentation to identify tracts that have been permanently deleted or deferred from a particular sale. More information can be found through the Division of Oil and Gas web site, under the Leasing Section: http://www.dog.dnr.alaska.gov/