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

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.

(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.

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.

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.

MnDOT created area transportation partnerships (ATPs) to emphasize greater public involvement in the preparation of transportation plans and programs. There are eight ATPs in Minnesota (one for each MnDOT District area). The ATP Districts are also used to describe the locations and responsible district for construction projects identified in various MnDOT Annual Reports (ex. CHIP/STIP, Major Highway Projects Report.

The metropolitan planning area for each Metro Planning Area (MPO).

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

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

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

This dataset is a copy of the Minnesota Department of Public Safety State Patrol district boundaries. There are 11 state patrol districts, comprised of 59 station number sub-districts. With the exception of Hubbard, St Louis, and Todd County, the district boundaries follow county lines. District 2000 and District 4600 are specific to building perimeter and not spatially represented in this dataset.

The area for each Regional Development Org (RDO).

Check other metadata records in this package for more information on State Agency Administrative Boundaries.

The celebrated Kibble-Zurek mechanism (KZM) describes the scaling of physical quantities when external parameters sweep through a critical point. Boundaries are ubiquitous in real systems, and critical behaviors near the boundary have attracted extensive research. Different boundary universality classes, including ordinary, special, extraordinary, and surface transitions, have been identified. However, the driven critical dynamics near boundaries remains unexplored. Here, we systematically investigate the driven critical dynamics in various boundary universality classes of the Ising model in both two and three dimensions, and discover a wealth of dynamic scaling behaviors. We find that for heating dynamics in all boundary universality classes, as well as for cooling dynamics in special, extraordinary, and surface transitions, the dynamic scaling behaviors of the order parameter can be described by a normal generalization of the KZM, called boundary finite-time scaling (BFTS). In contrast, for cooling dynamics in ordinary transition, we discover an abnormal logarithmic scaling on the driving rate. Moreover, for the special transition, in addition to temper-ature driving, we also consider the driven dynamics by driving the surface couplings. For increasing the surface coupling across the special transition point along the line of the ordinary transition, the prerequisite of the KZM, which requires that the correlation length/time in the initial state to be short-ranged, breaks down. We develop a generalized BFTS for a nonequilibrium initial state characterized by the waiting time, or the “age”, of the boundary. Possible generalizations are also discussed.

The Minnesota Department of Transportation (MnDOT) divides the state into eight administrative zonal areas referred to as construction districts. The boundaries of these districts are used to determine which district is responsible for construction activities on trunk highways, and for reporting purposes. Construction Districts is a polygon feature class that represents an area that defines the portions of trunk highways and their junctions served by each of the eight districts.The Minnesota Department of Transportation (MnDOT) divides the state into eight administrative zonal areas called Construction Districts. Some of these Construction Districts have been further sub-divided into Maintenance SubDistricts, which may identify a region for operational or administrative purposes. Maintenance SubDistricts is a polygon feature class that represents this area, and defines the portions of trunk highways and their junctions served by each SubDistrict. They are derived from the SubDistrict attribute field from the Maintenance Subareas feature class.The Minnesota Department of Transportation (MnDOT) divides the state into eight administrative zonal areas call construction districts. Within each construction district, there are a varying number of maintenance subareas. These subareas represent which facility is responsible for maintenance activities on trunk highways, specifically winter maintenance. Note that summer maintenance activates may deviate substantially from these boundaries. Maintenance Subareas is a polygon feature class that represents the area, and defines the portions of trunk highways and their junctions served by each districts subarea.Check other metadata records in this package for more information on MnDOT Boundaries

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

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 feature class contains lands that make up the State Parks and State Trails in Florida as of October 1st, 2025

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

(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 dataset is a representation of the boundaries of the original claims (or water-righted places of use) sourced from Pine Creek and tributaries, as identified by the Sixth Judicial District Court in the Barlett Decree of 1931, as well as Duckwater and Currant Creek and tributaries, as identified by the Fifth Judicial District Court in the Duckwater Decree of 1909 and 1910 and the Currant Creek Decree of 1921. These data are intended to assist in identifying the general locations of water-righted areas and their associated claim numbers. This mapping project was initiated in 2024 to assist in determining historical pumpage estimates for the demonstration basins, Pine Valley (053) and Railroad Valley (173B), where groundwater rights may be supplemental to surface water for the Nevada Water Initiative, with the final result being a feature class identifying the locations of each claim for the Pine, Duckwater and Currant Creek Decrees. This feature class is available on the Nevada Division of Water Resources (NDWR) Open Data site: https://data-ndwr.hub.arcgis.com/datasets/NDWR::nevada-water-initiative-decree-boundaries/about. This GIS layer exists only as a guide and starting point to identify the approximate locations of the water-righted areas in comparison to modern place of use boundaries. Further research is required to determine if a particular place of use originally had decreed water rights and whether it has retained those rights. Please contact the Division of Water Resources for more information.In order to produce a GIS depiction of the claims, the decree maps when available were georeferenced to the most up-to-date version of the Public Land Survey System (PLSS) dataset. If decree maps were not available, places of use were mapped based on subdivision descriptions found within the decrees. Each claim was then digitized from the boundaries shown on the georeferenced map and attributed with the assigned claim number and linked with associated information for each claim as described in the decree.This layer is strictly a visual representation, and it is important to note that acreages listed in this dataset may not match the decree for each claim. Assumptions were made regarding claims in the Barlett Decree where acreages overlapped within a subdivision resulting in combined acreage amounts across multiple years of priority or land classifications. In some cases, claims were not mapped because boundaries were not shown for a given subdivision on the georeferenced map. Changes in the PLSS for Railroad Valley (173B) were incorporated when mapping the subdivisions for the Duckwater Decree, as the modern boundaries varied from the decreed descriptions.Authors: McCartin, C.R., and Vergin, T.N.Initial Release: May 22, 2024

Feature class that compares the elevations between sand dune crests (extracted from available LiDAR datasets from 2010 and 2013) with published FEMA Base Flood Elevations (BFEs) from preliminary FEMA DFIRMS (Panels issued in 2018 and 2019) in coastal York and Cumberland counties (up through Willard Beach in South Portland). Steps to create the dataset included:Shoreline structures from the most recent NOAA EVI LANDWARD_SHORETYPE feature class were extracted using the boundaries of York and Cumberland counties. This included 1B: Exposed, Solid Man-Made structures, 8B: Sheltered, Solid Man-Made Structures; 6B: Riprap, and 8C: Sheltered Riprap. This resulted in the creation of Cumberland_ESIL_Structures and York_ESIL_Structures. Note that ESIL uses the MHW line as the feature base.Shoreline structures from the work by Rice (2015) were extracted using the York and Cumberland county boundaries. This resulted in the creation of Cumberland_Rice_Structures and York_Rice_Structures.Additional feature classes for structures were created for York and Cumberland county structures that were missed. This was Slovinsky_York_Structures and Slovinsky_Cumberland_Structures. GoogleEarth imagery was inspected while additional structures were being added to the GIS. 2012 York and Cumberland County imagery was used as the basemap, and structures were classified as bulkheads, rip rap, or dunes (if known). Also, whether or not the structure was in contact with the 2015 HAT was noted.MEDEP was consulted to determine which permit data (both PBR and Individual Permit, IP, data) could be used to help determine where shoreline stabilization projects may have been conducted adjacent to or on coastal bluffs. A file was received for IP data and brought into GIS (DEP_Licensing_Points). This is a point file for shoreline stabilization permits under NRPA.Clip GISVIEW.MEDEP.Permit_By_Rule_Locations to the boundaries of the study area and output DEP_PBR_Points.Join GISVIEW.sde>GISVIEW.MEDEP.PBR_ACTIVITY to the DEP_PBR_Points using the PBR_ID Field. Then, export this file as DEP_PBR_Points2. Using the new ACTIVITY_DESC field, select only those activities that relate to shoreline stabilization projects:PBR_ACTIVITY ACTIVITY_DESC02 Act. Adjacent to a Protected Natural Resource04 Maint Repair & Replacement of Structure08 Shoreline StabilizationSelect by Attributes > PBR_ACTIVITY IN (‘02’, ‘04’, ‘08’) select only those activities likely to be related to shoreline stabilization, and export the selected data as a DEP_PBR_Points3. Then delete 1 and 2, and rename this final product as DEP_PBR_Points.Next, visually inspect the Licensing and PBR files using ArcMap 2012, 2013 imagery, along with Google Earth imagery to determine the extents of armoring along the shoreline.Using EVI and Rice data as indicators, manually inspect and digitize sections of the coastline that are armored. Classify the seaward shoreline type (beach, mudflat, channel, dune, etc.) and the armor type (wall or bulkhead). Bring in the HAT line and, using that and visual indicators, identify whether or not the armored sections are in contact with HAT. Use Google Earth at the same time as digitizing in order to help constrain areas. Merge digitized armoring into Cumberland_York_Merged.Bring the preliminary FEMA DFIRM data in and use “intersect” to assign the different flood zones and elevations to the digitized armored sections. This was done first for Cumberland, then for York Counties. Delete ancillary attributes, as needed. Resulting layer is Cumberland_Structure_FloodZones and York_Structure_FloodZones.Go to NOAA Digital Coast Data Layers and download newest LiDAR data for York and Cumberland county beach, dune, and just inland areas. This includes 2006 and newer topobathy data available from 2010 (entire coast), and selected areas from 2013 and 2014 (Wells, Scarborough, Kennebunk).Mosaic the 2006, 2010, 2013 and 2014 data (with 2013 and 2014 being the first dataset laying on top of the 2010 data) Mosaic this dataset into the sacobaydem_ftNAVD raster (this is from the MEGIS bare-earth model). This will cover almost all of the study area except for armor along several areas in York. Resulting in LidAR206_2010_2013_Mosaic.tif.Using the LiDAR data as a proxy, create a “seaward crest” line feature class which follows along the coast and extracts the approximate highest point (cliff, bank, dune) along the shoreline. This will be used to extract LiDAR data and compare with preliminary flood zone information. The line is called Dune_Crest.Using an added tool Points Along Line, create points at 5 m spacing along each of the armored shoreline feature lines and the dune crest lines. Call the outputs PointsonLines and PointsonDunes.Using Spatial Analyst, Extract LIDAR elevations to the points using the 2006_2010_2013 Mosaic first. Call this LidarPointsonLines1. Select those points which have NULL values, export as this LiDARPointsonLines2. Then rerun Extract Values to Points using just the selected data and the state MEGIS DEM. Convert RASTERVALU to feet by multiplying by 3.2808 (and rename as Elev_ft). Select by Attributes, find all NULL values, and in an edit session, delete them from LiDARPointsonLines. Then, merge the 2 datasets and call it LidarPointsonLines. Do the same above with dune lines and create LidarPointsonDunes.Next, use the Cumberland and York flood zone layers to intersect the points with the appropriate flood zone data. Create ….CumbFIRM and …YorkFIRM files for the dunes and lines.Select those points from the Dunes feature class that are within the X zone – these will NOT have an associated BFE for comparison with the Lidar data. Export the Dune Points as Cumberland_York_Dunes_XZone. Run NEAR and use the merged flood zone feature class (with only V, AE, and AO zones selected). Then, join the flood zone data to the feature class using FID (from the feature class) and OBJECTID (from the flood zone feature class). Export as Cumberland_York_Dunes_XZone_Flood. Delete ancillary columns of data, leaving the original FLD_ZONE (X), Elev_ft, NEAR_DIST (distance, in m, to the nearest flood zone), FLD_ZONE_1 (the near flood zone), and the STATIC_BFE_1 (the nearest static BFE).Do the same as above, except with the Structures file (Cumberland_York_Structures_Lidar_DFIRM_Merged), but also select those features that are within the X zone and the OPEN WATER. Export the points as Cumberland_York_Structures_XZone. Again, run the NEAR using the merged flood zone and only AE, VE, and AO zones selected. Export the file as Cumberland_York_Structures_XZone_Flood.Merge the above feature classes with the original feature classes. Add a field BFE_ELEV_COMPARE. Select all those features whose attributes have a VE or AE flood zone and use field calculator to calculate the difference between the Elev_ft and the BFE (subtracting the STATIC_BFE from Elev_ft). Positive values mean the maximum wall value is higher than the BFE, while negative values mean the max is below the BFE. Then, select the remaining values with switch selection. Calculate the same value but use the NEAR_STATIC_BFE value instead. Select by Attributes>FLD_ZONE=AO, and use the DEPTH value to enter into the above created fields as negative values. Delete ancilary attribute fields, leaving those listed in the _FINAL feature classes described above the process steps section.

A polygon feature class of municipal boundaries within Miami-Dade County, data includes the municipal codes and names.Updated: As Needed The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

This feature class contains boundaries for Colorado Regional Care Collaborative regions. A Regional Care Collaborative Organization (RCCO) connects Medicaid clients to Medicaid providers and helps clients find community and social services in their area. RCCOs help providers communicate with Medicaid clients and with each other, so Medicaid clients receive coordinated care. A RCCO will also help Medicaid clients get the right care when they are returning home form the hospital or a nursing facility, by providing the support needed for a quick recovery. RCCOs help with other changes, too, like moving from children's health services to adult health services.

This polygon feature class represents Mountain Goat Hunt Areas in Washington State. These boundaries are used to determine the areas where the Mountain Goat hunts listed in the "Washington's Big Game Hunting Seasons and Regulations" pamphlet will be carried out.

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.