Class I and II surface water classification. The Clean Water Act requires that the surface waters of each state be classified according to designated uses. Florida has six classes with associated designated uses, which are arranged in order of degree of protection required: Class I - Potable Water Supplies Fourteen general areas throughout the state including: impoundments and associated tributaries, certain lakes, rivers, or portions of rivers, used as a drinking water supply. Class II - Shellfish Propagation or Harvesting Generally coastal waters where shellfish harvesting occurs. For a more detailed description of classes and specific waterbody designations, see 62-302.400.

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.

Accuracy assessment is one of the most important components of both applied and research-oriented remote sensing projects. For mapped classes that have sharp and easily identified boundaries, a broad array of accuracy assessment methods has been developed. However, accuracy assessment is in many cases complicated by classes that have fuzzy, indeterminate, or gradational boundaries, a condition which is common in real landscapes; for example, the boundaries of wetlands, many soil map units, and tree crowns. In such circumstances, the conventional approach of treating all reference pixels as equally important, whether located on the map close to the boundary of a class, or in the class center, can lead to misleading results. We therefore propose an accuracy assessment approach that relies on center-weighting map segment area to calculate a variety of common classification metrics including overall accuracy, class user’s and producer’s accuracy, precision, recall, specificity, and the F1 score. This method offers an augmentation of traditional assessment methods, can be used for both binary and multiclass assessment, allows for the calculation of count- and area-based measures, and permits the user to define the impact of distance from map segment edges based on a distance weighting exponent and a saturation threshold distance, after which the weighting ceases to grow. The method is demonstrated using synthetic and real examples, highlighting its use when the accuracy of maps with inherently uncertain class boundaries is evaluated.

(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.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

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.

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.

(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.

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

Official NYC East-of-Hudson and West-of-Hudson outer watershed boundaries delineated from 2009 LiDAR-derived 1-meter Digital Elevation Model (DEM). The 1m DEM was derived from airborne LiDAR data collected in 2009 as part of the NYS Digital Ortho Program under contract with NYCDEP under CAT-371. For individual reservoir drainage basin boundaries, see the "NYCbasin1m" feature class.As part of the NYC Watershed 2009 LiDAR National Hydrography Dataset (NHD) Update Project: Reservoir and Watershed Boundary Dataset 8-digit Hydrologic Unit (8-d HU) boundaries were created by IAGT/RACNE under CAT-393 for each of the West of Hudson (WOH) Reservoirs in the Catskills Mountains. In the EOH Taconic Mountains, there is a single 8-digit HUC boundary for all of the 17 reservoirs draining into the Lower Hudson sub-watershed through the New Croton Reservoir spillway, plus another for the Kensico Reservoir. These basins were dissolved together by DEP staff to create this layer representing only the outer NYC watershed boundary.Polygons representing differences between this 1m product and older 1:24K-derived basins were created and manually reviewed for correctness by NYSDEP BWS GIS and ERA Wetlands staff using high resolution aerial imagery, 2 ft contours, 1m DEM hillshade, GPS-ed culvert locations, GoogleMaps drive-by imagery, and BING Birds-eye imagery. In cases where office techniques could not easily determine correctness, field visits using sub-meter GPS data collection were performed by ERA Wetlands and GIS staff to make final determination. 1m Basin data were edited as needed by BWS GIS staff based on manual review. FALL 2020 NOTE: In Fall 2020, two changes were made to the official NYC watershed and basin boundaries as follows: 1) The Diverting Reservoir boundary in EOH was updated, which in-turn required a change in the basin and subbasin boundary there. 2) Based on the results of a watershed boundary field inspection by REP and GIS Staff, as per the watershed delineation SOP, a very small portion of the outer Cannonsville Reservoir boundary in WOH, T. Delhi required updating, which in-turn required a change in the basin and subbasin boundary there.These changes have been reflected in this basin-derived dataset.Because original vector data contained jagged edges as a by-products of the original raster gridded elevation data, a 10m x 10m smoothing filter was run on the exterior NYC watershed boundary and interior WOH basin boundaries, while a 5m x 5m smoothing filter was run on the smaller interior EOH basins. Each smoothed line was checked to ensure any elevation summits and ridgelines were still captured and that the line was true to the original catch basin delineation. In addition, DEP staff applied a simplification process to the boundaries. Because of the slowness in speed and performance due to the amount of vertices, the simplify line tool was used to reduce the amount of vertices, resulting in an increase in drawing and processing speeds. Again, staff checked the result to ensure that accuracy was not compromised. Sections of basin edges were also snapped to reservoir spillway edges and top-of-dam lines in the "NHDLine" and Auxiliary "breakline" feature classes where appropriate. This work was performed on the subbasin product first, and then all other basin related products were created. These were the steps used:Convert NYCsubbasin1m to arcsRun “simplify line” tool (Bend Simplify, 5m) on arcsConvert arcs result to polygonsRun repair geometryCreate basin1m (and related product) from subbasins1mIAGT/RACNE methodology: A single vector line feature class was directly derived from the 1m DEM, then manually reviewed. Polygonal feature classes were then derived from the line feature class, with a topology requirement to achieve polygonal closure and no non-hydrologic polygons. Lines were produced by TauDEM flow analysis of Reference DEM (1 m, version 0). Segment review was performed using 0.5 m interval contours and 2012 Hydrographic and Topographic Breaklines as guidelines. Vector process boundaries are the raster boundaries above plus those corresponding to areas downstream of the reservoirs that drain the corresponding WBD 8-d HU. See "2D Breakline Features and Hydrography Compilation Standard and Protocol" for details on the hydrography used in the review.

This is a MD iMAP hosted service layer. Find more information at http://imap.maryland.gov. userdata and unzip the LayerFiles.zip folder.Data from the four SSURGO tables were assembled into the single table included in each map package. Data from the component table were aggregated using a dominant component model (listed below under Component Table - Dominant Component) or a weighted average model (listed below under Component Table - Weighted Average) using custom Python scripts. The the Mapunit table - the MUAGATTAT table and the processed Component table data were joined to the Mapunit Feature Class. Field aliases were added and indexes calculated. A field named Map Symbol was created and populated with random integers from 1-10 for symbolizing the soil units in the map package.For documentation of the SSURGO dataset see:http://soildatamart.nrcs.usda.gov/SSURGOMetadata.aspxFor documentation of the Watershed Boundary Dataset see: http://www.nrcs.usda.gov/wps/portal/nrcs/main/national/water/watersheds/datasetThe map packages contain the following attributes in the Map Units layer:Mapunit Feature Class:Survey AreaSpatial VersionMapunit SymbolMapunit KeyNational Mapunit SymbolMapunit Table:Mapunit NameMapunit KindFarmland ClassHighly Erodible Lands Classification - Wind and WaterHighly Erodible Lands Classification - WaterHighly Erodible Lands Classification - WindInterpretive FocusIntensity of MappingLegend KeyMapunit SequenceIowa Corn Suitability RatingLegend Table:Project ScaleTabular VersionMUAGGATT Table:Slope Gradient - Dominant ComponentSlope Gradient - Weighted AverageBedrock Depth - MinimumWater Table Depth - Annual MinimumWater Table Depth - April to June MinimumFlooding Frequency - Dominant ConditionFlooding Frequency - MaximumPonding Frequency - PresenceAvailable Water Storage 0-25 cm - Weighted AverageAvailable Water Storage 0-50 cm - Weighted AverageAvailable Water Storage 0-100 cm - Weighted AverageAvailable Water Storage 0-150 cm - Weighted AverageDrainage Class - Dominant ConditionDrainage Class - WettestHydrologic Group - Dominant ConditionIrrigated Capability Class - Dominant ConditionIrrigated Capability Class - Proportion of Mapunit with Dominant ConditionNon-Irrigated Capability Class - Dominant ConditionNon-Irrigated Capability Class - Proportion of Mapunit with Dominant ConditionRating for Buildings without Basements - Dominant ConditionRating for Buildings with Basements - Dominant ConditionRating for Buildings with Basements - Least LimitingRating for Buildings with Basements - Most LimitingRating for Septic Tank Absorption Fields - Dominant ConditionRating for Septic Tank Absorption Fields - Least LimitingRating for Septic Tank Absorption Fields - Most LimitingRating for Sewage Lagoons - Dominant ConditionRating for Sewage Lagoons - Dominant ComponentRating for Roads and Streets - Dominant ConditionRating for Sand Source - Dominant ConditionRating for Sand Source - Most ProbableRating for Paths and Trails - Dominant ConditionRating for Paths and Trails - Weighted AverageErosion Hazard of Forest Roads and Trails - Dominant ComponentHydric Classification - PresenceRating for Manure and Food Processing Waste - Weighted AverageComponent Table - Weighted Average:Mean Annual Air Temperature - High Value Mean Annual Air Temperature - Low Value Mean Annual Air Temperature - Representative Value Albedo - High Value Albedo - Low Value Albedo - Representative Value Slope - High Value Slope - Low Value Slope - Representative Value Slope Length - High Value Slope Length - Low Value Slope Length - Representative Value Elevation - High Value Elevation - Low Value Elevation - Representative Value Mean Annual Precipitation - High Value Mean Annual Precipitation - Low Value Mean Annual Precipitation - Representative Value Days between Last and First Frost - High Value Days between Last and First Frost - Low Value Days between Last and First Frost - Representative Value Crop Production Index Range Forage Annual Potential Production - High Value Range Forage Annual Potential Production - Low Value Range Forage Annual Potential Production - Representative Value Initial Subsidence - High Value Initial Subsidence - Low Value Initial Subsidence - Representative Value Total Subsidence - High ValueTotal Subsidence - Low Value Total Subsidence - Representative Value Component Table - Dominant Component:Component KeyComponent Percentage - Low ValueComponent Percentage - Representative ValueComponent Percentage - High ValueComponent NameComponent KindOther Criteria Used to Identify ComponentsCriteria Used to Identify Components at the Local LevelRunoffSoil Loss Tolerance FactorWind Erodibility IndexWind Erodibility GroupErosion ClassEarth Cover 1Earth Cover 2Hydric ConditionAspect Range - Counter Clockwise LimitAspect - Representative ValueAspect Range - Clockwise LimitGeomorphic DescriptionNon-Irrigated Capability SubclassNon-Irrigated Unit Capability ClassIrrigated Capability SubclassIrrigated Unit Capability ClassConservation Tree Shrub GroupForage Suitability GroupGrain Wildlife HabitatGrass Wildlife HabitatHerbaceous Wildlife HabitatShrub Wildlife HabitatConifer Wildlife HabitatHardwood Wildlife HabitatWetland Wildlife HabitatShallow Water Wildlife HabitatRangeland Wildlife HabitatOpenland Wildlife HabitatWoodland Wildlife HabitatWetland Wildlife HabitatSoil Slip PotentialSusceptibility to Frost HeavingConcrete CorrosionSteel CorrosionTaxonomic Class NameOrderSuborderGreat GroupSubgroupParticle SizeParticle Size ModifierCation Exchange Activity ClassCarbonate ReactionTemperature ClassMoisture SubclassSoil Temperature RegimeEdition of Keys to Soil Taxonomy Used to Classify SoilThe U.S. Department of Agriculture - Natural Resources Conservation Service - should be acknowledged as the data source in products derived from these data. This data set is not designed for use as a primary regulatory tool in permitting or citing decisions - but may be used as a reference source. This is public information and may be interpreted by organizations - agencies - units of government - or others based on needs; however - they are responsible for the appropriate application. Federal - State - or local regulatory bodies are not to reassign to the Natural Resources Conservation Service any authority for the decisions that they make. The Natural Resources Conservation Service will not perform any evaluations of these maps for purposes related solely to State or local regulatory programs. Photographic or digital enlargement of these maps to scales greater than at which they were originally mapped can cause misinterpretation of the data. If enlarged - maps do not show the small areas of contrasting soils that could have been shown at a larger scale. The depicted soil boundaries - interpretations - and analysis derived from them do not eliminate the need for onsite sampling - testing - and detailed study of specific sites for intensive uses. Thus - these data and their interpretations are intended for planning purposes only. Digital data files are periodically updated. Files are dated - and users are responsible for obtaining the latest version of the data.The attribute accuracy is tested by manual comparison of the source with hard copy plots and/or symbolized display of the map data on an interactive computer graphic system. Selected attributes that cannot be visually verified on plots or on screen are interactively queried and verified on screen. In addition - the attributes are tested against a master set of valid attributes. All attribute data conform to the attribute codes in the signed classification and correlation document and amendment(s). Last Updated: Feature Service Layer Link: https://mdgeodata.md.gov/imap/rest/services/Geoscientific/MD_SSURGOSoils/MapServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

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.

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.

This data set is one of many developed in support of The High Plains Groundwater Availability Project and the U.S. Geological Survey Data Series Report: Geodatabase Compilation of Hydrogeologic, Remote Sensing, and Water-Budget-Component data for the High Plains aquifer, 2011 (DS 777). The creation of the model grid is an important first step in developing a groundwater-flow model, because all model inputs including properties, wells, and boundary conditions are assigned to the model cells. The northern High Plains groundwater-flow model boundary feature dataset contains three feature classes; the model grid cells for the northern High Plains groundwater-flow model in both polygon (cell) and point (centroid) format and the external boundary of the model. The model grid contains 449,175 cells, 565 rows and 795 columns. Each cell is 1,000 feet per side. The model grid is not rotated. The external boundary includes the active and inactive areas of the model. The projection for the model grid and all feature classes in all geodatabases for this study are Albers Equal-Area Conic coordinate system, North American Datum1983.

The pathway representation consists of segments and intersection elements. A segment is a linear graphic element that represents a continuous physical travel path terminated by path end (dead end) or physical intersection with other travel paths. Segments have one street name, one address range and one set of segment characteristics. A segment may have none or multiple alias street names. Segment types included are Freeways, Highways, Streets, Alleys (named only), Railroads, Walkways, and Bike lanes. SNDSEG_PV is a linear feature class representing the SND Segment Feature, with attributes for Street name, Address Range, Alias Street name and segment Characteristics objects. Part of the Address Range and all of Street name objects are logically shared with the Discrete Address Point-Master Address File layer. Appropriate uses include: Cartography - Used to depict the City's transportation network location and connections, typically on smaller scaled maps or images where a single line representation is appropriate. Used to depict specific classifications of roadway use, also typically at smaller scales. Used to label transportation network feature names typically on larger scaled maps. Used to label address ranges with associated transportation network features typically on larger scaled maps. Geocode reference - Used as a source for derived reference data for address validation and theoretical address location Address Range data repository - This data store is the City's address range repository defining address ranges in association with transportation network features. Polygon boundary reference - Used to define various area boundaries is other feature classes where coincident with the transportation network. Does not contain polygon features. Address based extracts - Used to create flat-file extracts typically indexed by address with reference to business data typically associated with transportation network features. Thematic linear location reference - By providing unique, stable identifiers for each linear feature, thematic data is associated to specific transportation network features via these identifiers. Thematic intersection location reference - By providing unique, stable identifiers for each intersection feature, thematic data is associated to specific transportation network features via these identifiers. Network route tracing - Used as source for derived reference data used to determine point to point travel paths or determine optimal stop allocation along a travel path. Topological connections with segments - Used to provide a specific definition of location for each transportation network feature. Also provides a specific definition of connection between each transportation network feature. (defines where the streets are and the relationship between them ie. 4th Ave is west of 5th Ave and 4th Ave does intersect with Cherry St) Event location reference - Used as source for derived reference data used to locate event and linear referencing.Data source is TRANSPO.SNDSEG_PV. Updated weekly.

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

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

WBDHU6: This geospatial dataset represents the 3rd level (6-digit) hydrologic unit boundaries of the Watershed Boundary Dataset (WBD) layer for Washington. It was created by dissolving boundaries from the finer resolution hydrologic units to create these broader boundaries. See metadata for the wbd_wa_poly feature class for a more complete description of the WBD. USGS Federal Standards and Procedures for the National Watershed Boundary Dataset (WBD) located here: http://pubs.usgs.gov/tm/11/a3/pdf/tm11-a3.pdf