This File Geodatabase download, (last updated September 25, 2024), contains all the feature classes within the Transportation Network. The City of Langley has compiled all the Transportation Network feature classes into one file geodatabase. File Geodatabase Feature Classes:Bicycle RoutesBridgesDisaster Response RoutesMediansRailwayRoadsSidewalksStreet Names

Complete Water Utility Network in file geodatabase format. Consume this dataset if you wish to download the entire Water Utility network dataset at once.

Abstract

This dataset was derived by the Bioregional Assessment Programme from the GEODATA TOPO 250K Series 3 dataset (GUID: a0650f18-518a-4b99-a553-44f82f28bb5f). 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 is a copy of the original Geodata Topo 250k Series 3 data, converted from Personal (Microsoft Access) Databases, to ESRI File Geodatabases. This was done to ensure .mdb lock files would not restrict map makers from using the topographic data in their cartographic products. The data and folders are structured the same as the original dataset.

Dataset History

A new file geodatabase schema was created in the same structure as the original .mdb data (including database and feature dataset names and projections). Feature Classes were then copied from the .mdb format to the .gdb format, using ArcCatalog 10.0.

Dataset Citation

Bioregional Assessment Programme (2014) GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb). Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/96ebf889-f726-4967-9964-714fb57d679b.

Dataset Ancestors

• Derived From GEODATA TOPO 250K Series 3

Description goes here.

This zip file contains geodatabases with raster mosaic datasets. The raster mosaic datasets consist of georeferenced tiff images of mineral potential maps, their associated metadata, and descriptive information about the images. These images are duplicates of the images found in the georeferenced tiff images zip file. There are four geodatabases containing the raster mosaic datasets, one for each of the four SaMiRA report areas: North-Central Montana; North-Central Idaho; Southwestern and South-Central Wyoming and Bear River Watershed; and Nevada Borderlands. The georeferenced images were clipped to the extent of the map and all explanatory text, gathered from map explanations or report text was imported into the raster mosaic dataset database as ‘Footprint’ layer attributes. The data compiled into the 'Footprint' layer tables contains the figure caption from the original map, online linkage to the source report when available, and information on the assessed commodities according to the legal definition of mineral resources—metallic, non-metallic, leasable non-fuel, leasable fuel, geothermal, paleontological, and saleable. To use the raster mosaic datasets in ArcMap, click on “add data”, double click on the [filename].gdb, and add the item titled [filename]_raster_mosaic. This will add all of the images within the geodatabase as part of the raster mosaic dataset. Once added to ArcMap, the raster mosaic dataset appears as a group of three layers under the mosaic dataset. The first item in the group is the ‘Boundary’, which contains a single polygon representing the extent of all images in the dataset. The second item is the ‘Footprint’, which contains polygons representing the extent of each individual image in the dataset. The ‘Footprint’ layer also contains the attribute table data associated with each of the images. The third item is the ‘Image’ layer and contains the images in the dataset. The images are overlapping and must be selected and locked, or queried in order to be viewed one at a time. Images can be selected from the attribute table, or can be selected using the direct select tool. When using the direct select tool, you will need to deselect the ‘overviews’ after clicking on an image or group of images. To do this, right click on the ‘Footprint’ layer and hover over ‘Selection’, then click ‘Reselect Only Primary Rasters’. To lock a selected image after selecting it, right-click on the ‘Footprint’ layer in the table of contents window and hover over ‘Selection’, then click ‘Lock To Selected Rasters’. Another way to view a single image is to run a definition query on the image. This is done by right clicking on the raster mosaic in the table of contents and opening the layer properties box. Then click on the ‘Definition Query’ tab and create a query for the desired image.

This File Geodatabase download, (last updated September 25, 2024), contains all the feature classes within the Storm Sewer Utility System. The City of Langley has compiled all the Storm Sewer feature classes into one file geodatabase for convenience. File Geodatabase Feature Classes:Catch BasinsHeadwallsInvertsLateralsMainsMains AnnotationManholesOffset LinesOffset TextService LinesService Text

This packaged data collection contains two sets of two additional model runs that used the same inputs and parameters as our primary model, with the exception being we implemented a "maximum corridor length" constraint that allowed us to identify and visualize the corridors as being well-connected (≤15km) or moderately connected (≤45km). This is based on an assumption that corridors longer than 45km are too long to sufficiently accommodate dispersal. One of these sets is based on a maximum corridor length that uses Euclidean (straight-line) distance, while the other set is based on a maximum corridor length that uses cost-weighted distance. These two sets of corridors can be compared against the full set of corridors from our primary model to identify the remaining corridors, which could be considered poorly connected. This package includes the following data layers: Corridors classified as well connected (≤15km) based on Cost-weighted Distance Corridors classified as moderately connected (≤45km) based on Cost-weighted Distance Corridors classified as well connected (≤15km) based on Euclidean Distance Corridors classified as moderately connected (≤45km) based on Euclidean Distance Please refer to the embedded metadata and the information in our full report for details on the development of these data layers. Packaged data are available in two formats: Geodatabase (.gdb): A related set of file geodatabase rasters and feature classes, packaged in an ESRI file geodatabase. ArcGIS Pro Map Package (.mpkx): The same data included in the geodatabase, presented as fully-symbolized layers in a map. Note that you must have ArcGIS Pro version 2.0 or greater to view. See Cross-References for links to individual datasets, which can be downloaded in raster GeoTIFF (.tif) format.

The Los Angeles County Storm Drain System is a geometric network model representing the storm drain infrastructure within Los Angeles County. The long term goal of this network is to seamlessly integrate the countywide drainage infrastructure, regardless of ownership or jurisdiction. Current uses by the Department of Public Works (DPW) include asset inventory, operational maintenance, and compliance with environmental regulations.

GIS DATA DOWNLOADS: (More information is in the table below)

File geodatabase: A limited set of feature classes comprise the majority of this geometric network. These nine feature classes are available in one file geodatabase (.gdb). ArcMap versions compatible with the .gdb are 10.1 and later. Read-only access is provided by the open-source software QGIS. Instructions on opening a .gdb file are available here, and a QGIS plugin can be downloaded here.

Acronyms and Definitions (pdf) are provided to better understand terms used.

ONLINE VIEWING: Use your PC’s browser to search for drains by street address or drain name and download engineering drawings. The Web Viewer link is: https://dpw.lacounty.gov/fcd/stormdrain/

MOBILE GIS: This storm drain system can also be viewed on mobile devices as well as your PC via ArcGIS Online. (As-built plans are not available with this mobile option.)

More About these Downloads All data added or updated by Public Works is contained in nine feature classes, with definitions listed below. The file geodatabase (.gdb) download contains these eleven feature classes without network connectivity. Feature classes include attributes with unabbreviated field names and domains.

ArcMap versions compatible with the .gdb are 10.1 and later.

Feature Class Download Description

CatchBasin In .gdb Catch basins collect urban runoff from gutters

Culvert In .gdb A relatively short conduit that conveys storm water runoff underneath a road or embankment. Typical materials include reinforced concrete pipe (RCP) and corrugated metal pipe (CMP). Typical shapes are circular, rectangular, elliptical, or arched.

ForceMain In .gdb Force mains carry stormwater uphill from pump stations into gravity mains and open channels.

GravityMain In .gdb Underground pipes and channels.

LateralLine In .gdb Laterals connect catch basins to underground gravity mains or open channels.

MaintenanceHole In .gdb The top opening to an underground gravity main used for inspection and maintenance.

NaturalDrainage In .gdb Streams and rivers that flow through natural creek beds

OpenChannel In .gdb Concrete lined stormwater channels.

PumpStation In .gdb Where terrain causes accumulation, lift stations are used to pump stormwater to where it can once again flow towards the ocean

Data Field Descriptions

Most of the feature classes in this storm drain geometric network share the same GIS table schema. Only the most critical attributes are listed here per LACFCD operations.

Attribute Description

ASBDATE The date the design plans were approved “as-built” or accepted as “final records”.

CROSS_SECTIN_SHAPE The cross-sectional shape of the pipe or channel. Examples include round, square, trapezoidal, arch, etc.

DIAMETER_HEIGHT The diameter of a round pipe or the height of an underground box or open channel.

DWGNO Drain Plan Drawing Number per LACFCD Nomenclature

EQNUM Asset No. assigned by the Department of Public Works’ (in Maximo Database).

MAINTAINED_BY Identifies, to the best of LAFCD’s knowledge, the agency responsible for maintaining the structure.

MOD_DATE Date the GIS features were last modified.

NAME Name of the individual drainage infrastructure.

OWNER Agency that owns the drainage infrastructure in question.

Q_DESIGN The peak storm water runoff used for the design of the drainage infrastructure.

SOFT_BOTTOM For open channels, indicates whether the channel invert is in its natural state (not lined).

SUBTYPE Most feature classes in this drainage geometric nature contain multiple subtypes.

UPDATED_BY The person who last updated the GIS feature.

WIDTH Width of a channel in feet.

Crowther_Nature_Files.zip This description pertains to the original download. Details on revised (newer) versions of the datasets are listed below. When more than one version of a file exists in Figshare, the original DOI will take users to the latest version, though each version technically has its own DOI. -- Two global maps (raster files) of tree density. These maps highlight how the number of trees varies across the world. One map was generated using biome-level models of tree density, and applied at the biome scale. The other map was generated using ecoregion-level models of tree density, and applied at the ecoregion scale. For this reason, transitions between biomes or between ecoregions may be unrealistically harsh, but large-scale estimates are robust (see Crowther et al 2015 and Glick et al 2016). At the outset, this study was intended to generate reliable estimates at broad spatial scales, which inherently comes at the cost of fine-scale precision. For this reason, country-scale (or larger) estimates are generally more robust than individual pixel-level estimates. Additionally, due to data limitations, estimates for Mangroves and Tropical coniferous forest (as identified by WWF and TNC) were generated using models constructed from Topical moist broadleaf forest data and Temperate coniferous forest data, respectively. Because we used ecological analogy, the estimates for these two biomes should be considered less reliable than those of other biomes . These two maps initially appeared in Crowther et al (2015), with the biome map being featured more prominently. Explicit publication of the data is associated with Glick et al (2016). As they are produced, updated versions of these datasets, as well as alternative formats, will be made available under Additional Versions (see below).

Methods: We collected over 420,000 ground-sources estimates of tree density from around the world. We then constructed linear regression models using vegetative, climatic, topographic, and anthropogenic variables to produce forest tree density estimates for all locations globally. All modeling was done in R. Mapping was done using R and ArcGIS 10.1.

Viewing Instructions: Load the files into an appropriate geographic information system (GIS). For the original download (ArcGIS geodatabase files), load the files into ArcGIS to view or export the data to other formats. Because these datasets are large and have a unique coordinate system that is not read by many GIS, we suggest loading them into an ArcGIS dataframe whose coordinate system matches that of the data (see File Format). For GeoTiff files (see Additional Versions), load them into any compatible GIS or image management program.

Comments: The original download provides a zipped folder that contains (1) an ArcGIS File Geodatabase (.gdb) containing one raster file for each of the two global models of tree density – one based on biomes and one based on ecoregions; (2) a layer file (.lyr) for each of the global models with the symbology used for each respective model in Crowther et al (2015); and an ArcGIS Map Document (.mxd) that contains the layers and symbology for each map in the paper. The data is delivered in the Goode homolosine interrupted projected coordinate system that was used to compute biome, ecoregion, and global estimates of the number and density of trees presented in Crowther et al (2015). To obtain maps like those presented in the official publication, raster files will need to be reprojected to the Eckert III projected coordinate system. Details on subsequent revisions and alternative file formats are list below under Additional Versions.----------

Additional Versions: Crowther_Nature_Files_Revision_01.zip contains tree density predictions for small islands that are not included in the data available in the original dataset. These predictions were not taken into consideration in production of maps and figures presented in Crowther et al (2015), with the exception of the values presented in Supplemental Table 2. The file structure follows that of the original data and includes both biome- and ecoregion-level models.

Crowther_Nature_Files_Revision_01_WGS84_GeoTiff.zip contains Revision_01 of the biome-level model, but stored in WGS84 and GeoTiff format. This file was produced by reprojecting the original Goode homolosine files to WGS84 using nearest neighbor resampling in ArcMap. All areal computations presented in the manuscript were computed using the Goode homolosine projection. This means that comparable computations made with projected versions of this WGS84 data are likely to differ (substantially at greater latitudes) as a product of the resampling. Included in this .zip file are the primary .tif and its visualization support files.

References:

Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., Smith, J. R., Hintler, G., Duguid, M. C., Amatulli, G., Tuanmu, M. N., Jetz, W., Salas, C., Stam, C., Piotto, D., Tavani, R., Green, S., Bruce, G., Williams, S. J., Wiser, S. K., Huber, M. O., Hengeveld, G. M., Nabuurs, G. J., Tikhonova, E., Borchardt, P., Li, C. F., Powrie, L. W., Fischer, M., Hemp, A., Homeier, J., Cho, P., Vibrans, A. C., Umunay, P. M., Piao, S. L., Rowe, C. W., Ashton, M. S., Crane, P. R., and Bradford, M. A. 2015. Mapping tree density at a global scale. Nature, 525(7568): 201-205. DOI: http://doi.org/10.1038/nature14967Glick, H. B., Bettigole, C. B., Maynard, D. S., Covey, K. R., Smith, J. R., and Crowther, T. W. 2016. Spatially explicit models of global tree density. Scientific Data, 3(160069), doi:10.1038/sdata.2016.69.

Abstract This dataset and its metadata statement were developed for the Bioregional Assessment Programme and are presented here as originally supplied. The dataset was created by the Bioregional Assessment Programme for use in cartographic outputs in Gippsland Basin bioregion product 1.2. The processes undertaken to produce this dataset are described in the History field in this metadata statement. This dataset has been superseded by Cartographic masks for map products GIP 120 v03. Purpose Cart…Show full descriptionAbstract This dataset and its metadata statement were developed for the Bioregional Assessment Programme and are presented here as originally supplied. The dataset was created by the Bioregional Assessment Programme for use in cartographic outputs in Gippsland Basin bioregion product 1.2. The processes undertaken to produce this dataset are described in the History field in this metadata statement. This dataset has been superseded by Cartographic masks for map products GIP 120 v03. Purpose Cartographic masks for map products GIP_120, used for clear annotation and masking unwanted features from report maps. Dataset History Rectangular polygon shapefile masks were created around selected feature labels from the following datasets: GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb) - GUID: 96ebf889-f726-4967-9964-714fb57d679b Victoria Mining Licences - 13 May 2015 - GUID: c9c1dff4-01c7-4669-a033-d8a9f674cd5a A shapefile was created for the use of masking data to highlight text. Method: * A new polygon shapefile was created with no content * The shapefile was then populated in an ArcMap editing session by digitizing polygons which surround text. * ArcMAP's Advanced Drawing Option was then used to mask data behind text. Dataset Citation Bioregional Assessment Programme (XXXX) Cartographic masks for map products GIP 120 v02. Bioregional Assessment Derived Dataset. Viewed 05 October 2018, http://data.bioregionalassessments.gov.au/dataset/39945fcc-d1a7-49c4-a011-ca595c42ec51. Dataset Ancestors Derived From GEODATA TOPO 250K Series 3 Derived From GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb) Derived From Victoria Mining Licences - 13 May 2015

This package contains principal facts for new gravity data collected September - November 2017 in support of the Fallon FORGE project. Also included are rock core density and magnetic susceptibility data for key core intervals, used in modeling 2D and 3D gravity inversions.

Individual metadata summaries are provided as .pdf within each attached archive. A total of 903 gravity stations were read on the FORGE project over the course of 25 production days. The stations were read along lines or on a grid with station spacings varying from 100 meters to 2 kilometers. This archive contains a geodatabase (.gdb) file, an xml file, and a csv file containing the processed gravity data. Also included is a report summarizing the gravity survey.

Abstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are 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. Cartographic masks for map products GIP_120, used for clear annotation and masking unwanted features from report maps. Dataset History Rectangular polygon shapefile masks were created around …Show full descriptionAbstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are 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. Cartographic masks for map products GIP_120, used for clear annotation and masking unwanted features from report maps. Dataset History Rectangular polygon shapefile masks were created around selected feature labels from the following datasets: GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb) - GUID: 96ebf889-f726-4967-9964-714fb57d679b Victoria Mining Licences - 13 May 2015 - GUID: c9c1dff4-01c7-4669-a033-d8a9f674cd5a Dataset Citation Bioregional Assessment Programme (XXXX) Cartographic masks for map products GIP 120 v03. Bioregional Assessment Derived Dataset. Viewed 30 September 2016, http://data.bioregionalassessments.gov.au/dataset/8d21fb97-a9bd-4deb-8d7b-a49265217a8f. Dataset Ancestors Derived From Victoria Mining Licences - 13 May 2015 Derived From GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb) Derived From GEODATA TOPO 250K Series 3

This .zip file contains a file geodatabase of the stormwater management assets for the City of Harrisonburg, Virginia. Layers included are stormwater feature manholes, pipes, pipe structures, drop inlets, Best Management Practices (points), low-lying areas, farm ponds and BMP areas, and ditches.This file is updated monthly.

Summary:

The files available here include a spatial data layer that represents the output of an analysis of opportunity for additional tree canopy in New York City (NYC) that considers factors that influence where trees can be planted and where canopy can grow, 'practical canopy,' as well as summaries of this data layer by NYC Borough, Community District, City Council District, and Neighborhood Tabulation Area. Links to a preprint and peer-reviewed paper describing the methods and context for this work are available below. The practical canopy layer is the result of a spatial model, and is thus an approximation based on available data and assumptions. See the associated materials for full discussion of limits and potential uses of this work.

If you do not find what you are looking for here, contact Michael Treglia, Lead Scientist with The Nature Conservancy in New York, Cities Program, at michael.treglia@tnc.org.

Terms of Use

© The Nature Conservancy. This material is provided as-is, without warranty under a Creative Commons Attribution-NonCommercial-ShareAlike License as set forth in our Conservation Gateway Terms of Use (available at: http://conservationgateway.org/Pages/Terms-of-Use.aspx)

If using these data, please cite the both the peer-reviewed paper and this set of data, based on the following recommended citations:

Treglia, M. L., Piland, N. C., Leu, K., Van Slooten, A., & Maxwell, E. N. (2022). Understanding opportunities for urban forest expansion to inform goals: working toward a virtuous cycle in New York City. Frontiers in Sustainable Cities. 4:944823. doi: 10.3389/frsc.2022.944823

Treglia, M. L., Piland, N. C., Leu, K., Van Slooten, A., & Maxwell, E. N. (2022). Practical Canopy for New York City—Data Layer and Summarized Results [Data set]. Zenodo. doi: 10.5281/zenodo.6547492

The manuscript for this work is also available in a preprint, with the following citation:

Treglia, M. L., Piland, N. C., Leu, K., Van Slooten, A., & Maxwell, E. N. (2022). Understanding opportunities for urban forest expansion to inform goals: working toward a virtuous cycle in New York City. Preprints. 2022060106. doi: 10.20944/preprints202206.0106.v1

Contents

nyc_practicalcanopy_datalayer.zip - Zipped folder with the practical canopy data layer that resulted from the work described in the associated preprint, as both GeoPackage (.gpkg) and Esri File Geodatabase (.gdb) files, with Data Dictionary files in .docx and .html formats. Both the .gpkg and .gdb files are zipped within the .zip file to save space, such that users may uncompress the format they prefer to use. The uncompressed .gdb file is nearly 3 gb; the uncompressed .gpkg file is about 10 gb.

nyc_practicalcanopy_summary_results.zip - Zipped folder summarized results of the practical canopy analysis by NYC Borough, Community District, City Council District, and Neighborhood Tabulation Area. Data are available as non-spatial .csv files and as both GeoPackage (.gpkg) and Esri File Geodatabase (.gdb) files; Data Dictionaries are included in both .docx and .html formats.

Download Amherst GIS 2009 Topo data in the following formats:ESRI File Geodatabase (.gdb)ESRI Shapefile (.shp)AutoCAD DWGAutoCAD DXFMicrostation DGNRaster (image) layers can be downloaded in several different formats as well.Available topography data includes the following large datasets which are best extracted over small areas:Elevation PointsElevation Contour Text Annotations1' Interval Elevation ContoursElevation Model Image (8' pixels)Hillshading Image (8' pixels)The extent of this data includes the entire project area of the Amherst April 2009 LiDAR flight, including all of Amherst as well as portions of Hadley, Sunderland, Leverett, Shutesbury, Pelham & Belchertown. The LiDAR data can be downloaded as tiles via the Amherst Orthophoto & LiDAR Data Download App.

Abstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are 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. The dataset contains dam locations stored as points for all subregions of the Bioregional Assessment Programme. ## Purpose Initially to illustrate dam localities on a number of Northern Inland Catchments bioregion map elements. Can be applied across all bioregions. ## Dataset History Dam centroids (points) have been derived from the Geoscience Australia GEODATA TOPO 250K Series 3 - Infrastructure/DamWalls layer using the ESRI ArcTools\Data Management\Feature To Point tool. The original attributes of the input features have been maintained in the output feature class. ## Dataset Citation Bioregional Assessment Programme (2014) Dams of the Bioregional Assessment subregions. Bioregional Assessment Derived Dataset. Viewed 11 April 2016, http://data.bioregionalassessments.gov.au/dataset/2ba9cbdd-136d-491e-a46c-e3cedab8ea88. ## Dataset Ancestors * Derived From GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb) * Derived From GEODATA TOPO 250K Series 3

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are 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.

The dataset includes two shapefiles consisting of point and polygon locations of selected dams in the Sydney Basin Bioregion. The data were used to show the locations of these dams in maps. Polygon data were used to create points, as described in the History field, that could be shown and labelled in maps for context.

Purpose

For display on report map images

Dataset History

Selected Dam wall (line) features were taken from the 1:250k topographic data Infrastucture theme (see lineage) and converted to a line midpoint (ArcGIS feature conversion polyline to point). Two of the dams needed to be displayed were not found in the 1:250k topographic data. Medway Dam location spatial co-ordinates were sourced from the 2010 Gazetteer (see lineage). Bundanoon dam location was ascertained from Google Earth imagery. Point features for both these dams were manually edited in and appended to the 1:250k topographic data derived dam location data.

Dataset Citation

Bioregional Assessment Programme (2015) SSB Storages Point Locations V01. Bioregional Assessment Derived Dataset. Viewed 14 June 2018, http://data.bioregionalassessments.gov.au/dataset/39b3ca3a-e421-4c68-9499-50c2e9ab2334.

Dataset Ancestors

• Derived From Gazetteer of Australia 2010

• Derived From GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)

• Derived From GEODATA TOPO 250K Series 3

The framework of the Cordilleran orogen of northwestern North America is commonly depicted as a 'collage' of terranes - crustal blocks containing records of a variety of geodynamic environments including continental fragments, pieces of island arc crust and oceanic crust. The series of maps available here are derived from a GIS compilation of terranes based on the map first published by Colpron et al. (2007) and more recently revised by Nelson et al. (2013). These maps are presented here in digital formats including ArcGIS file geodatabase (.gdb), shapefiles (.shp and related files), Google Earth (.kmz), as well as graphic files (.pdf). The GIS data includes terrane polygons and selected major Late Cretaceous and Tertiary strike-slip faults. Graphic PDF files derived from the GIS compilation were prepared for the Northern Cordillera (Alaska, Yukon and BC), the Canadian Cordillera (BC and Yukon), Yukon, and British Columbia. These maps are intended for page-size display (~1:5,000,000 and smaller). Polygons are accurate to ~1 km for Yukon and BC, ~5 km for Alaska. More detailed geological data are available from both BCGC, USGS and YGS websites. Descriptions of the terranes, their tectonic evolution and metallogeny can be found in Colpron et al. (2007), Nelson and Colpron (2007), Colpron and Nelson (2009), Nelson et al. (2013) and references therein. The terrane map project is a collaborative effort of the BC Geological Survey and the Yukon Geological Survey. Distributed from GeoYukon by the Government of Yukon . Discover more digital map data and interactive maps from Yukon's digital map data collection. For more information: geomatics.help@yukon.ca

Metadata Portal Metadata Information

Abstract The dataset was derived by the Bioregional Assessment Programme from the GEODATA TOPO 250K Series 3 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. A clip to the boundary of the NIC bioregion of the original Geodata Topo 250k Series 3 data. Further information can be found at http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_a05f7892-ecbd-7506-e044-00144fdd4fa6/GEODATA+TOPO+250K+Series+3+%28Packaged+-+Shape+file+format%29 ## Dataset History These data have been derived from the TOPO 250K Series 3 data by clipping the data to the external boundary of the Northern Inland Catchments bioregion using the ESRI ArcGIS Analysis Clip tool. Further information can be found at http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_a05f7892-ecbd-7506-e044-00144fdd4fa6/GEODATA+TOPO+250K+Series+3+%28Packaged+-+Shape+file+format%29 ## Dataset Citation Bioregional Assessment Programme (XXXX) Northern Inland Catchments bioregion GEODATA TOPO 250K Series 3. Bioregional Assessment Derived Dataset. Viewed 10 December 2018, http://data.bioregionalassessments.gov.au/dataset/3bd6389b-be36-4e91-bc20-131e18f209c2. ## Dataset Ancestors * Derived From Natural Resource Management (NRM) Regions 2010 * Derived From Bioregional Assessment areas v03 * Derived From Bioregional Assessment areas v01 * Derived From Bioregional Assessment areas v02 * Derived From GEODATA TOPO 250K Series 3 * Derived From NSW Catchment Management Authority Boundaries 20130917 * Derived From Geological Provinces - Full Extent * Derived From GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)