AbstractCoastline for Antarctica created from various mapping and remote sensing sources, consisting of the following coast types: ice coastline, rock coastline, grounding line, ice shelf and front, ice rumple, and rock against ice shelf. Covering all land and ice shelves south of 60°S. Suitable for topographic mapping and analysis. This dataset has been generalised from the high resolution vector polyline. Medium resolution versions of ADD data are suitable for scales smaller than 1:1,000,000, although certain regions will appear more detailed than others due to variable data availability and coastline characteristics.Changes in v7.10 include updates to the coastline of Alexander Island and surrounding islands, and the ice shelf fronts of the Wilkins and Brunt ice shelves.Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research.Further information and useful linksMap projection: WGS84 Antarctic Polar Stereographic, EPSG 3031. Note: by default, opening this layer in the Map Viewer will display the data in Web Mercator. To display this layer in its native projection use an Antarctic basemap.The currency of this dataset is November 2024 and will be reviewed every 6 months. This feature layer will always reflect the most recent version.For more information on, and access to other Antarctic Digital Database (ADD) datasets, refer to the SCAR ADD data catalogue.A related high resolution dataset is also published via Living Atlas, as well medium and high resolution polygon datasets.For background information on the ADD project, please see the British Antarctic Survey ADD project page.LineageDataset compiled from a variety of Antarctic map and satellite image sources. The dataset was created using ArcGIS and QGIS GIS software programmes and has been checked for basic topography and geometry checks, but does not contain strict topology. Quality varies across the dataset and certain areas where high resolution source data were available are suitable for large scale maps whereas other areas are only suitable for smaller scales. Each line has attributes detailing the source which can give the user further indications of its suitability for specific uses. Attributes also give information including 'surface' (e.g. grounding line, ice coastline, ice shelf front) and revision date. Compiled from sources ranging in time from 1990s-2024 - individual lines contain exact source dates. This medium resolution version has been generalised from the high resolution version. All areas <0.1km² not intersecting anything else were deleted and the ‘simplify’ tool was used in ArcGIS with the ‘retain critical points’ algorithm and a smoothing tolerance of 50 m.CitationGerrish, L., Ireland, L., Fretwell, P., & Cooper, P. (2024). Medium resolution vector polylines of the Antarctic coastline (Version 7.10) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/bc81931c-4e8e-439a-b3c9-d3d1fdb109dfIf using for a graphic or if short on space, please cite as 'data from the SCAR Antarctic Digital Database, 2024'

Data as of March 8, 2013. These boundary lines were derived from the World Vector Shoreline dataset and match up with the 2013 detailed LSIB polygons.

The 1:250,000 scale World Vector Shoreline (WVS) coastline data is generally shifted by several hundred meters to over a km. To simplify the polygons, the ArcGIS Simplify Polygon tool was used, using the Bend Simplify algorithm with a maximum allowable offset of 3 miles. Topology was then corrected for any errors produced by the simplification process. For convenience, the dataset is broken out into regions: (1) Africa, (2) Asia and Russia, (3) Europe and Southwest Asia, (4) North America, (5) Oceania, and (6) South America. In the zip file, there is also a global dataset (approximately 24 MBs) that includes all the data.

There are no restrictions on use of this public domain data. This dataset will be updated as needed and is current as of March 08, 2013.

The County_Gen feature class is a generalized spatial representation of the United States Counties and equivalent governmental units. The data are an extract of the Census codes and boundaries from the following Census FTP site: ftp://ftp2.census.gov/geo/tiger/TIGER2015/. Since the Census data do not include the coastline detail, the coastal boundaries have been included through a spatial erase using the Census Hydrography data from the Census FTP site: ftp://ftp2.census.gov/geo/tiger/TIGER2015/AREAWATER/. After erasing the coastline, the data was generalized using the ESRI Simplify Polygon function. The County_Gen feature class is a US Forest Service Standard Reference Dataset and is the preferred spatial representation of counties. This feature class should be used for small-scale cartographic products. The purpose of the generalized County_Gen dataset is to improve map display and drawing performance in both ArcGIS applications and ArcGIS Server map services. To satisfy both performance improvement and geometry representation, the following parameters and geoprocessing method were used. Simplify the input features using the Douglas-Peucker simplification algorithm with a specified maximum offset tolerance of 375 meters. The output features will contain a subset of the original input vertices. Min scale refers to what scale the layer turns off when zooming out. Max scale refers to the scale the layer turns off at when zooming in. Min scale: 0, no minimum scale set, Max Scale: 1:4622325.

This feature class is a derivative of the 2012 planimetric water layer. It was Generalized using the Cartographic Generalization tool, Simplify Polygon with the Bend Simplify option and a Minimal Allowable Offset tolerance of 5 feet. A collection of vector polygon features for water bodies within the Urban Development Boundary (UDB) and outside the UDB, approximately 938 square miles. The planimetric layer for Miami-Dade County was previously updated in 2007 by Woolpert. Aerial Cartographics of America's update is comprised of two individual updates: inside the UDB (542 square miles) performed using a on-screen/2D digitizing of the 2012 orthophotography captured by PhotoScience; and outside of the UDB (396 square miles) using on-screen/2D digitizing of the 2012 orthophotography captured by PhotoScience. Personnel that collected this data are either photogrammetrists trained in stereo collection or editors trained in ortho-photography based collection. Items included in the feature class: WATER BODIES (Polygons) Water lines and water under the bridge. Definition of particular fields in the Water feature class: Water = {0,1} where 0 = Feature does not represent water; 1 = Water feature. Type = {'', 'B'} where B = Water under the bridge. Possible combinations of these fields are: 0,''; 1,'';1, 'B'Updated: Biennially The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

The classification raster has been postprocessed by majority filtering and converted to polygons with simplification using Wang-Muller algorithm with tolerance of 2 meters.

This polygon feature contains geographic and attribute information for the purpose of depicting Comprehensive Plan Areas within the City of SeaTac, Washington. The data was compiled from existing comprehensive plan information and King County parcel data.This data layer is a reflection of the comprehensive plan that indicates how the City wants to grow and function in the future. The source document contains broad statements of community goals and policies, as well as specific steps for achieving them. The City of SeaTac Comprehensive Plan serves as a "blueprint" for how SeaTac can achieve its vision for itself over the next 20 to 26 years. The Comprehensive Plan will provide the legal basis for future zoning and other implementation measures.City of SeaTac Comprehensive Plan as prepared and adopted by the SeaTac City Council.Last amended in June 23, 2015 (Ord. 15-1009).The change to Angle Lake District Area Boundary was adopted on July 9th, 2015 (Ord. 15-1010).The Washington Growth management Act (GMA) mandates that cities in high growth areas, like Puget Sound region, prepare and adopt comprehensive plans that are consistent with the GMA. The content was last modified in Dec 2013. Boundaries were updated based on parcel data from 02/13/2015, to reflect changes in ROWs and Parcel line, etc. Comprehensive plan boundaries have been adjusted to line up with King County Assessor parcel lines that were improved in 2006 and 2007. Slivers and gaps will appear if this comprehensive plan layer is overlaid with historical parcel, zoning, or comprehensive plan layers. The geometry of this data derives from KC parcel data which is updated quarterly. Then it was intersected with the existing Comprehensive Plan data to transfer the attribute.Incorporated in February 1990, the City of SeaTac is located in the Pacific Northwest, approximately midway between the cities of Seattle and Tacoma in the State of Washington. SeaTac is a vibrant community, economically strong, environmentally sensitive, and people-oriented. The City boundaries surround the Seattle-Tacoma International Airport, (approximately 3 square miles in area) which is owned and operated by the Port of Seattle. For additional information regarding the City of SeaTac, its people, or services, please visit https://www.seatacwa.gov. For additional information regarding City GIS data or maps, please visit https://www.seatacwa.gov/our-city/maps-and-gis.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

This dataset was sourced from the Queensland Department of Natural Resources and Mines in 2012. Information provided by the Department describes the dataset as follows:

This data was originally provided on DVD and contains the converted shapefiles, layer files, raster images and project .mxd files used on the Queensland geology and structural framework map. The maps were done in ArcGIS 9.3.1 and the data stored in file geodatabases, topology created and validated. This provides greater data quality by performing topological validation on the feature's spatial relationships. For the purposes of the DVD, shapefiles were created from the file geodatabases and for MapInfo users MapInfo .tab and .wor files. The shapefiles on the DVD are a revision of the 1975 Queensland geology data, and are both are available for display, query and download on the department's online GIS application.

The Queensland geology map is a digital representation of the distribution or extent of geological units within Queensland. In the GIS, polygons have a range of attributes including unit name, type of unit, age, lithological description, dominant rock type, and an abbreviated symbol for use in labelling the polygons. The lines in this dataset are a digital representation of the position of the boundaries of geological units and other linear features such as faults and folds. The lines are attributed with a description of the type of line represented. Approximately 2000 rock units were grouped into the 250 map units in this data set. The digital data was generalised and simplified from the Department's detailed geological data and was captured at 1:500 000 scale for output at 1:2 000 000 scale.

In the ESRI version, a layer file is provided which presents the units in the colours and patterns used on the printed hard copy map. For Map Info users, a simplified colour palette is provided without patterns. However a georeferenced image of the hard copy map is included and can be displayed as a background in both Arc Map and Map Info.

The geological framework of Queensland is classified by structural or tectonic unit (provinces and basins) in which the rocks formed. These are referred to as basins (or in some cases troughs and depressions) where the original form and structure are still apparent. Provinces (and subprovinces) are generally older basins that have been strongly tectonised and/or metamorphosed so that the original basin extent and form are no longer preserved. Note that intrusive and some related volcanic rocks that overlap these provinces and basins have not been included in this classification. The map was compiled using boundaries modified and generalised from the 1:2 000 000 Queensland Geology map (2012). Outlines of subsurface basins are also shown and these are based on data and published interpretations from petroleum exploration and geophysical surveys (seismic, gravity and magnetics).

For the structural framework dataset, two versions are provided. In QLD_STRUCTURAL_FRAMEWORK, polygons are tagged with the name of the surface structural unit, and names of underlying units are imbedded in a text string in the HIERARCHY field. In QLD_STRUCTURAL_FRAMEWORK_MULTI_POLYS, the data is structured into a series of overlapping, multi-part polygons, one for each structural unit. Two layer files are provided with the ESRI data, one where units are symbolised by name. Because the dataset has been designed for units display in the order of superposition, this layer file assigns colours to the units that occur at the surface with concealed units being left uncoloured. Another layer file symbolises them by the orogen of which they are part. A similar set of palettes has been provided for Map Info.

Dataset History

Details on the source data can be found in the xml file associated with data layer.

Data in this release

*ESRI.shp and MapInfo .tab files of rock unit polygons and lines with associated layer attributes of Queensland geology

*ESRI.shp and MapInfo .tab files of structural unit polygons and lines with associated layer attributes of structural framework

*ArcMap .mxd and .lyr files and MapInfo .wor files containing symbology

*Georeferenced Queensland geology map, gravity and magnetic images

*Queensland geology map, structural framework and schematic diagram PDF files

*Data supplied in geographical coordinates (latitude/longitude) based on Geocentric Datum of Australia - GDA94

Accessing the data

Programs exist for the viewing and manipulation of the digital spatial data contained on this DVD. Accessing the digital datasets will require GIS software. The following GIS viewers can be downloaded from the internet. ESRI ArcExplorer can be found by a search of www.esriaustralia.com.au and MapInfo ProViewer by a search on www.pbinsight.com.au collectively ("the websites").

Metadata

Metadata is contained in .htm files placed in the root folder of each vector data folder. For ArcMap users metadata for viewing in ArcCatalog is held in an .xml file with each shapefile within the ESRI Shapefile folders.

Disclaimer

The State of Queensland is not responsible for the privacy practices or the content of the websites and makes no statements, representations, or warranties about the content or accuracy or completeness of, any information or products contained on the websites.

Despite our best efforts, the State of Queensland makes no warranties that the information or products available on the websites are free from infection by computer viruses or other contamination.

The State of Queensland disclaims all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages and costs you might incur as a result of accessing the websites or using the products available on the websites in any way, and for any reason.

The State of Queensland has included the websites in this document as an information source only. The State of Queensland does not promote or endorse the websites or the programs contained on them in any way.

WARNING: The Queensland Government and the Department of Natural Resources and Mines accept no liability for and give no undertakings, guarantees or warranties concerning the accuracy, completeness or fitness for the purposes of the information provided. The consumer must take all responsible steps to protect the data from unauthorised use, reproduction, distribution or publication by other parties.

Please view the 'readme.html' and 'licence.html' file for further, more complete information

Dataset Citation

Geological Survey of Queensland (2012) Queensland geology and structural framework - GIS data July 2012. Bioregional Assessment Source Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/69da6301-04c1-4993-93c1-4673f3e22762.

The LAS data set was originally classified according to 4 classes (ground, water, bridge overpass, and noise), with the rest of the data being unclassified. That left some classes to be derived and classified, of which one—the building/ structure class—was considered necessary for this project. In theory, deriving a building/structure layer is relatively straightforward: the building reflectance response should be unclassified, single-reflectance response points, whereas the vegetation, also unclassified, should yield a multiple-reflectance response as the beam bounces back through the canopy. Following this idea, we created a Digital Surface Model (DSM) from the single-response, unclassified LAS point cloud. We then subtracted these DSMs from the Bare Earth DEMs to create a difference image, which ideally should represent only buildings. Unfortunately, many trees were included in this “buildings” layer, due possibly to the sparse canopy that is characteristic of trees found in southwestern forests and possibly to the presence of fairly recent burn scars that include a number of standing dead trees and snags. In an attempt to remove the clutter of false positives due to trees, we developed a Normalized Difference Vegetation Index (NDVI) from the NAIP imagery acquired over the area in the same year. The NDVI is an image-processing technique that uses the reflective information found in the red (Red) and near-infrared (NIR) wavelengths to enhance the “green” vegetative response over other, non-vegetated surface features (Eq. 1). NDVI = (NIR−Red)/(NIR+Red) [Eq. 1]. This provides a floating-point image of values from -1 to 1, with numbers above 0 representing increasing vegetative cover. We further modified the NDVI equation to create an 8-bit image (Eq. 2). NDVImod = (NDVI+1)*100 [Eq. 2]. This 8-bit image had all positive integer values, where values above 100 indicated increasing vegetative cover. We used the generated NDVI image, in particular values above 109, to mask out many of the false anomalies. In addition, all heights less than 6 feet were masked out, as this was considered a minimum height for most buildings. We added 1 to values in the resulting image so that all values, even the zeroes, would be counted. Then values were clumped to produce an image of individually coded raster polygons. We eliminated all clusters smaller than 32 square meters (345 square feet) from the clumped image, ran a 3x3 majority filter to remove relict edges, and ran a 3x3 morphological close filter to remove holes in the raster polygons. We completed the raster processing in ERDAS IMAGINE and then converted the data set to a polygon layer in ESRI ArcGIS, as is and without using the ‘simplify polygon’ option. This was cleaned up further using the simplify buildings module with a minimum spacing of 2 meters. Once this was completed, the polygon layer was edited using the NAIP imagery and DSM Shaded Relief imagery as a background by a heads-up digitizing at a 1:3,000 scale (the approximate base resolution of the LiDAR data). The building/structure layer contained more than 44,612 identified structures.

Park Boundaries: A simplified polygon layer of California State Parks Boundaries, providing Unit name, subtype and other attributes. California State Park Boundaries are for reference and not for official or legal property boundary determination. Current as of July 29, 2024.

A Lake Champlain subset of the VHDCARTO dataset--which is a simplified cartographic-purpose version of the local resolution Vermont Hydrography Dataset (VHD).The full VHDCARTO dataset is composed of two layers--a line layer and a polygon layer.

This feature class is a derivative of the 2012 planimetric water layer. It was Generalized using the Cartographic Generalization tool, Simplify Polygon with the Bend Simplify option and a Minimal Allowable Offset tolerance of 5 feet. Additionally the land feature(s) was removed. A collection of vector polygon features for water bodies within the Urban Development Boundary (UDB) and outside the UDB, approximately 938 square miles. The planimetric layer for Miami-Dade County was previously updated in 2007 by Woolpert. Aerial Cartographics of America's update is comprised of two individual updates: inside the UDB (542 square miles) performed using a on-screen/2D digitizing of the 2012 orthophotography captured by PhotoScience; and outside of the UDB (396 square miles) using on-screen/2D digitizing of the 2012 orthophotography captured by PhotoScience. Personnel that collected this data are either photogrammetrists trained in stereo collection or editors trained in ortho-photography based collection. Items included in the feature class: WATER BODIES (Polygons) Water lines and water under the bridge. Definition of particular fields in the Water feature class: Water = {0,1} where 0 = Feature does not represent water; 1 = Water feature. Type = 'C' = canal, 'L' = Lake and 'B' = BayUpdated: Biennially The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

This layer contains both Consolidated Municipal Service Managers (CMSM) & District Social Services Administration Boards (DSABS) based on the 2013 municipal boundary. This layer was built on the full 2013 municipal boundaries: Districts, Single tiers, and Sault Ste Marie Planning Board.The Consolidated Municipal Service Managers (CMSM) and District Social Services Administration Boards (DSSAB) are members of the Ontario Municipal Social Service Association (OMSSA). CMSM is an organization responsible for funding, planning, managing, and delivering human services including learning and child care, employment and income supports, and housing and homelessness prevention programs within specified region in Ontario. There are 47 CMSMs in Ontario that were created as a result of the consolidation of municipal service management that began in 1998. These are primarily made up of upper tier municipalities in southern Ontario and District Social Service Administration Boards (DSSABs) in northern Ontario. Note Indian Reserves were not included in the creation of the boundary. See http://www.e-laws.gov.on.ca/html/regs/english/elaws_regs_980278_e.htm for DSSAB definitions See http://www.e-laws.gov.on.ca/html/regs/english/elaws_regs_980136_e.htm for CMSM definitionsThe original shapefile was compressed using the “Simplify by Polygon (Cartography)” tool with the following specifications applied: Simplification Algorithm: Bend SimplifyReference Baseline: 1.5 KilometersAs a result, there will be some distortion along the shorelines. Please note, this dataset is a modified version of the original Consolidated Municipal Service Manager (CMSM) and District Social Service Administration Board (DSSAB) Boundary File. There are 47 CMSM/DSSAB’s in Ontario, but the original dataset contains 76 map features. This is due to some boundaries consisting of both mainland areas and islands areas. In the modified version there are 47 CMSM/DSSAB boundaries and 47 map features. If an area has both a Land and Island extent, they are displayed as one area with the extent being land. The CMSM of Grey has a different Municipal Service Offices (MSO) for the Land and Island extents. In this dataset, the Land MSO is used.

This dataset is a modified version of the FWS developed data depicting “Highly Important Landscapes”, as outlined in Memorandum FWS/AES/058711 and provided to the Wildlife Habitat Spatial analysis Lab on October 29th 2014. Other names and acronyms used to refer to this dataset have included: Areas of Significance (AoSs - name of GIS data set provided by FWS), Strongholds (FWS), and Sagebrush Focal Areas (SFAs - BLM). The BLM will refer to these data as Sagebrush Focal Areas (SFAs). Data were provided as a series of ArcGIS map packages which, when extracted, contained several datasets each. Based on the recommendation of the FWS Geographer/Ecologist (email communication, see data originator for contact information) the dataset called “Outiline_AreasofSignificance” was utilized as the source for subsequent analysis and refinement. Metadata was not provided by the FWS for this dataset. For detailed information regarding the dataset’s creation refer to Memorandum FWS/AES/058711 or contact the FWS directly. Several operations and modifications were made to this source data, as outlined in the “Description” and “Process Step” sections of this metadata file. Generally: The source data was named by the Wildlife Habitat Spatial Analysis Lab to identify polygons as described (but not identified in the GIS) in the FWS memorandum. The Nevada/California EIS modified portions within their decision space in concert with local FWS personnel and provided the modified data back to the Wildlife Habitat Spatial Analysis Lab. Gaps around Nevada State borders, introduced by the NVCA edits, were then closed as was a large gap between the southern Idaho & southeast Oregon present in the original dataset. Features with an area below 40 acres were then identified and, based on FWS guidance, either removed or retained. Finally, guidance from BLM WO resulted in the removal of additional areas, primarily non-habitat with BLM surface or subsurface management authority. Data were then provided to each EIS for use in FEIS development. Based on guidance from WO, SFAs were to be limited to BLM decision space (surface/sub-surface management areas) within PHMA. Each EIS was asked to provide the limited SFA dataset back to the National Operations Center to ensure consistent representation and analysis. Returned SFA data, modified by each individual EIS, was then consolidated at the BLM’s National Operations Center retaining the three standardized fields contained in this dataset.Several Modifications from the original FWS dataset have been made. Below is a summary of each modification.1. The data as received from FWS: 16,514,163 acres & 1 record.2. Edited to name SFAs by Wildlife Habitat Spatial Analysis Lab:Upon receipt of the “Outiline_AreasofSignificance” dataset from the FWS, a copy was made and the one existing & unnamed record was exploded in an edit session within ArcMap. A text field, “AoS_Name”, was added. Using the maps provided with Memorandum FWS/AES/058711, polygons were manually selected and the “AoS_Name” field was calculated to match the names as illustrated. Once all polygons in the exploded dataset were appropriately named, the dataset was dissolved, resulting in one record representing each of the seven SFAs identified in the memorandum.3. The NVCA EIS made modifications in concert with local FWS staff. Metadata and detailed change descriptions were not returned with the modified data. Contact Leisa Wesch, GIS Specialist, BLM Nevada State Office, 775-861-6421, lwesch@blm.gov, for details.4. Once the data was returned to the Wildlife Habitat Spatial Analysis Lab from the NVCA EIS, gaps surrounding the State of NV were closed. These gaps were introduced by the NVCA edits, exacerbated by them, or existed in the data as provided by the FWS. The gap closing was performed in an edit session by either extending each polygon towards each other or by creating a new polygon, which covered the gap, and merging it with the existing features. In addition to the gaps around state boundaries, a large area between the S. Idaho and S.E. Oregon SFAs was filled in. To accomplish this, ADPP habitat (current as of January 2015) and BLM GSSP SMA data were used to create a new polygon representing PHMA and BLM management that connected the two existing SFAs.5. In an effort to simplify the FWS dataset, features whose areas were less than 40 acres were identified and FWS was consulted for guidance on possible removal. To do so, features from #4 above were exploded once again in an ArcMap edit session. Features whose areas were less than forty acres were selected and exported (770 total features). This dataset was provided to the FWS and then returned with specific guidance on inclusion/exclusion via email by Lara Juliusson (lara_juliusson@fws.gov). The specific guidance was:a. Remove all features whose area is less than 10 acresb. Remove features identified as slivers (the thinness ratio was calculated and slivers identified by Lara Juliusson according to https://tereshenkov.wordpress.com/2014/04/08/fighting-sliver-polygons-in-arcgis-thinness-ratio/) and whose area was less than 20 acres.c. Remove features with areas less than 20 acres NOT identified as slivers and NOT adjacent to other features.d. Keep the remainder of features identified as less than 40 acres.To accomplish “a” and “b”, above, a simple selection was applied to the dataset representing features less than 40 acres. The select by _location tool was used, set to select identical, to select these features from the dataset created in step 4 above. The records count was confirmed as matching between the two data sets and then these features were deleted. To accomplish “c” above, a field (“AdjacentSH”, added by FWS but not calculated) was calculated to identify features touching or intersecting other features. A series of selections was used: first to select records 6. Based on direction from the BLM Washington Office, the portion of the Upper Missouri River Breaks National Monument (UMRBNM) that was included in the FWS SFA dataset was removed. The BLM NOC GSSP NLCS dataset was used to erase these areas from #5 above. Resulting sliver polygons were also removed and geometry was repaired.7. In addition to removing UMRBNM, the BLM Washington Office also directed the removal of Non-ADPP habitat within the SFAs, on BLM managed lands, falling outside of Designated Wilderness’ & Wilderness Study Areas. An exception was the retention of the Donkey Hills ACEC and adjacent BLM lands. The BLM NOC GSSP NLCS datasets were used in conjunction with a dataset containing all ADPP habitat, BLM SMA and BLM sub-surface management unioned into one file to identify and delete these areas.8. The resulting dataset, after steps 2 – 8 above were completed, was dissolved to the SFA name field yielding this feature class with one record per SFA area.9. Data were provided to each EIS for use in FEIS allocation decision data development.10. Data were subset to BLM decision space (surface/sub-surface) within PHMA by each EIS and returned to the NOC.11. Due to variations in field names and values, three standardized fields were created and calculated by the NOC:a. SFA Name – The name of the SFA.b. Subsurface – Binary “Yes” or “No” to indicated federal subsurface estate.c. SMA – Represents BLM, USFS, other federal and non-federal surface management 12. The consolidated data (with standardized field names and values) were dissolved on the three fields illustrated above and geometry was repaired, resulting in this dataset.

(Link to Metadata) VHDCARTO is a simplified version of the local resolution Vermont Hydrography Dataset (VHD) that has been enriched with stream perenniality, e.g., "intermittent" vs. "perennial", as well as, Strahler stream order attribution for the single linear feature class only. The primary means of accessing this information cartographically is via the FCODE and STREAM_ORDER fields, respectively. See the Entity and Attribution Information section for details. NOTE! Perenniality data does not exist for stream reaches contained within, or intersected by, Essex or Caledonia counties, thus the FCODE "46000" in these areas. The absence of Soil SUrvey GeOgraphic (SSURGO) database information in these areas precluded the computation of perenniality. These areas will be processed at some future date. For information on the FCODE symbol for attribution or analysis see the following document https://www.usgs.gov/national-hydrography/national-hydrography-dataset (NHDFlowline). A two dimensional feature class for lakes, ponds and larger streams is also included in VHDCARTO. Both layers are derived from the latest National Hydrography Dataset (NHD) data. The NHD is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that make up the nation's surface water drainage system. For information on the science behind computing perenniality attribution please refer to the following U.S. Geological Survey Scientific Investigative Report (SIR) # 2006-5217 - https://pubs.usgs.gov/sir/2006/5217/pdf/SIR2006-5217_report.pdf

Topicality: august 2017Projection: New Zealand Transverse Mercator (NZTM)Updates April 2020: Clipped to coastline, added Ministry of Health codes (See data tab)This layer contains the District Health Board boundaries. District Health Boards are responsible for providing or buying Government funded health care services for the population of a specific geographical area. District Health Boards have existed since 1 January 2001. The amalgamation of Otago and Southland into the Southern District Health Board in 2010 reduced the number of District Health Boards from 21 to 20 (excluding 'Area outside District Health Board')The official dataset can be found on https://datafinder.stats.govt.nz.This layer contains the following attributes (see data tab):District Health Board codeDistrict Health Board nameThree digit codeFour digit codeChar codeHPI code (Health Provider Index)The layer is further generalised and clipped to the coastline by Eagle Technology for improved performance on the web, therefore it doesn't fully represent the official boundaries.The data is generalized using the tool Simplify Polygon using the Retain critical points (Dougla-Peucker) algorithm with a simplification tolerance of 10m.The data is clipped using the LINZ NZ Coastlines and Islands Polygons - Topo 1:50k layerIf you have any questions or comments about the content, please let us now at livingatlas@eagle.co.nz.

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple the Queensland geology and structural framework dataset. The source dataset is identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

This dataset contains a polygon shapefile of the Belyando Basin province boundary. The Belyando Basin underlies the eastern margin of the Galilee subregion. Extracted from the QLD Geology and Structural Framework of 2012 - the abstract of which is below.

The data on this DVD contains the converted shapefiles, layer files, raster images and project .mxd files used on the Queensland geology and structural framework map. The maps were done in ArcGIS 9.3.1 and the data stored in file geodatabases, topology created and validated. This provides greater data quality by performing topological validation on the feature's spatial relationships. For the purposes of the DVD, shapefiles were created from the file geodatabases and for MapInfo users MapInfo .tab and .wor files. The shapefiles on the DVD are a revision of the 1975 Queensland geology data, and are both are available for display, query and download on the department's online GIS application.

The Queensland geology map is a digital representation of the distribution or extent of geological units within Queensland. In the GIS, polygons have a range of attributes including unit name, type of unit, age, lithological description, dominant rock type, and an abbreviated symbol for use in labelling the polygons. The lines in this dataset are a digital representation of the position of the boundaries of geological units and other linear features such as faults and folds. The lines are attributed with a description of the type of line represented. Approximately 2000 rock units were grouped into the 250 map units in this data set. The digital data was generalised and simplified from the Department's detailed geological data and was captured at 1:500 000 scale for output at 1:2 000 000 scale.

The geological framework of Queensland is classified by structural or tectonic unit (provinces and basins) in which the rocks formed. These are referred to as basins (or in some cases troughs and depressions) where the original form and structure are still apparent. Provinces (and subprovinces) are generally older basins that have been strongly tectonised and/or metamorphosed so that the original basin extent and form are no longer preserved. Note that intrusive and some related volcanic rocks that overlap these provinces and basins have not been included in this classification. The map was compiled using boundaries modified and generalised from the 1:2 000 000 Queensland Geology map (2012). Outlines of subsurface basins are also shown and these are based on data and published interpretations from petroleum exploration and geophysical surveys (seismic, gravity and magnetics).

For the structural framework dataset, two versions are provided. In QLD_STRUCTURAL_FRAMEWORK, polygons are tagged with the name of the surface structural unit, and names of underlying units are imbedded in a text string in the HIERARCHY field. In QLD_STRUCTURAL_FRAMEWORK_MULTI_POLYS, the data is structured into a series of overlapping, multi-part polygons, one for each structural unit. Two layer files are provided with the ESRI data, one where units are symbolised by name. Because the dataset has been designed for units display in the order of superposition, this layer file assigns colours to the units that occur at the surface with concealed units being left uncoloured. Another layer file symbolises them by the orogen of which they are part. A similar set of palettes has been provided for Map Info.

Purpose

This dataset provides a single, merged representation of the Belyando Basin as interpreted by the QLD Geology and Structural Framework of 2012

Dataset History

This dataset has been extracted directly from the QLD Geology and Structural Framework: QLD_STRUCTURAL_FRAMEWORK.shp.

1. Features with the following 'Heirarchy' attributes were selected and extracted:

a) Galilee Basin>Drummond Basin>Belyando Basin>Thomson Orogen

b) Eromanga Basin>Galilee Basin>Drummond Basin>Belyando Basin>Thomson Orogen

c) Drummond Basin>Belyando Basin>Thomson Orogen

d) Galilee Basin>Drummond Basin>Belyando Basin>Thomson Orogen

1. Features were merged together to produce the Belyando Basin province.

The lineage of the QLD Geology and Structural Framework is below:

Data in this release

*ESRI.shp and MapInfo .tab files of rock unit polygons and lines with associated layer attributes of Queensland geology

*ESRI.shp and MapInfo .tab files of structural unit polygons and lines with associated layer attributes of structural framework

*ArcMap .mxd and .lyr files and MapInfo .wor files containing symbology

*Georeferenced Queensland geology map, gravity and magnetic images

*Queensland geology map, structural framework and schematic diagram PDF files

*Data supplied in geographical coordinates (latitude/longitude) based on Geocentric Datum of Australia - GDA94

Accessing the data

Programs exist for the viewing and manipulation of the digital spatial data contained on this DVD. Accessing the digital datasets will require GIS software. The following GIS viewers can be downloaded from the internet. ESRI ArcExplorer can be found by a search of www.esriaustralia.com.au and MapInfo ProViewer by a search on www.pbinsight.com.au collectively ("the websites").

Metadata

Metadata is contained in .htm files placed in the root folder of each vector data folder. For ArcMap users metadata for viewing in ArcCatalog is held in an .xml file with each shapefile within the ESRI Shapefile folders.

Disclaimer

The State of Queensland is not responsible for the privacy practices or the content of the websites and makes no statements, representations, or warranties about the content or accuracy or completeness of, any information or products contained on the websites.

Despite our best efforts, the State of Queensland makes no warranties that the information or products available on the websites are free from infection by computer viruses or other contamination.

The State of Queensland disclaims all responsibility and all liability (including without limitation, liability in negligence) for all expenses, losses, damages and costs you might incur as a result of accessing the websites or using the products available on the websites in any way, and for any reason.

The State of Queensland has included the websites in this document as an information source only. The State of Queensland does not promote or endorse the websites or the programs contained on them in any way.

WARNING: The Queensland Government and the Department of Natural Resources and Mines accept no liability for and give no undertakings, guarantees or warranties concerning the accuracy, completeness or fitness for the purposes of the information provided. The consumer must take all responsible steps to protect the data from unauthorised use, reproduction, distribution or publication by other parties.

Dataset Citation

Bioregional Assessment Programme (XXXX) Belyando Basin Boundary - QLD Structural Framework. Bioregional Assessment Derived Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/4add856a-eb40-4bb2-bd41-f89788884782.

Dataset Ancestors

• Derived From Queensland geology and structural framework - GIS data July 2012

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

AbstractCoastline for Antarctica created from various mapping and remote sensing sources, provided as polygons with ‘land’, ‘ice shelf’, ‘ice tongue’ or ‘rumple’ attribute. Covering all land and ice shelves south of 60°S. Suitable for topographic mapping and analysis. This dataset has been generalised from the high resolution vector polygons. Medium resolution versions of ADD data are suitable for scales smaller than 1:1,000,000, although certain regions will appear more detailed than others due to variable data availability and coastline characteristics.Changes in v7.10 include updates to the coastline of Alexander Island and surrounding islands, and the ice shelf fronts of the Wilkins and Brunt ice shelves.Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research.Further information and useful linksMap projection: WGS84 Antarctic Polar Stereographic, EPSG 3031. Note: by default, opening this layer in the Map Viewer will display the data in Web Mercator. To display this layer in its native projection use an Antarctic basemap.The currency of this dataset is November 2024 and will be reviewed every 6 months. This feature layer will always reflect the most recent version.For more information on, and access to other Antarctic Digital Database (ADD) datasets, refer to the SCAR ADD data catalogue.A related high resolution dataset is also published via Living Atlas, as well medium and high resolution line datasets.For background information on the ADD project, please see the British Antarctic Survey ADD project page.LineageDataset compiled from a variety of Antarctic map and satellite image sources. The dataset was created using ArcGIS and QGIS GIS software programmes and has been checked for basic topography and geometry checks, but does not contain strict topology. Quality varies across the dataset and certain areas where high resolution source data were available are suitable for large scale maps whereas other areas are only suitable for smaller scales. Each polygon contains a ‘surface’ attribute with either ‘land’, ‘ice shelf’, ‘ice tongue’ or ‘rumple’. Details of when and how each line was created can be found in the attributes of the high or medium resolution polyline coastline dataset. Data sources range in time from 1990s-2024 - individual lines contain exact source dates. This medium resolution version has been generalised from the high resolution version. All polygons <0.1km² not intersecting anything else were deleted and the ‘simplify’ tool was used in ArcGIS with the ‘retain critical points’ algorithm and a smoothing tolerance of 50 m.CitationGerrish, L., Ireland, L., Fretwell, P., & Cooper, P. (2024). Medium resolution vector polygons of the Antarctic coastline (Version 7.10) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/93ac35af-9ec7-4594-9aaa-0760a2b289d5If using for a graphic or if short on space, please cite as 'data from the SCAR Antarctic Digital Database, 2024'

Data has been created from hosted feature service (https://mapping.gw.govt.nz/arcgis/rest/services/GW/NRPMap_P_operative/MapServer). It has been shared to the Open Data Portal. Map of lowland areas for category 2 surface waterbodies in the Wellington region for the management of rivers and streams in productive rural lowland areas.This feature class is derived from the New Zealand Land Resource Inventory (NZLRI) and the Land Cover Database v4 (2012), both produced by Landcare Research - Manaaki Whenua.In particular it is based on the land use capability layer which makes an assessment of the productive capability of land areas based on the underlying geology, soil type, slope angle, erosion susceptibility and vegetative cover.Slope classes A, B & C (under 16 deg) and soil classes 1-4 (arable land) were classified for inclusion in the area. Slope classes D,E, F & G (over 16 deg) and soil classes 5-8 (non-arable land) were excluded.It was created by first eliminating discrete polygons with slope classes below 15 degrees, occurring within broader areas above 16 degrees, using the dissolve tool. Likewise, islands of land over 16 degrees smaller than 15 km2sitting within lowland areas under 16 degrees were eliminated. Then complex, crenulated areas were rounded off with the simplify and smooth polygon tool. The whole delineation was then checked for accuracy and aligned where necessary to conform to slopes under 16 degrees with arable soils classes four and under.