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Data format: File Geodatabase Raster Dataset File or table name: Freeway Coordinate system: Albers Conical Equal Area Theme keywords: Freeway, wildlife, road, transportation, habitat, connectivity, focal species, resistance |
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Abstract:
This is a derived layer that was compiled from portions of the U.S. Census TIGER Roads, Washington State DNR GIS Transportation Data Layer, and British Columbia Roads. This combination of road types includes TIGER Interstate highways distinguished by the presence of interchanges. They have multiple lanes of traffic, and opposing lanes are separated by a median strip (TIGER field CFCC2 = “A1”). It also includes visually matched DNR roads for which Road Class = “Primary”). Finally, it includes B.C. Digital Road Atlas roads for which ROAD_CLASS = “freeway”, with the exception of a few roads identified by the Modeling Team as belonging in the Major Highway category. Though traffic volumes at any particular location along these highways can vary considerably, these road types tend to carry the highest traffic volumes and are designed for relatively high speeds. Annual Average Daily Traffic Volumes are almost always above 2000 vehicles and commonly exceed 25,000 vehicles. Examples include Interstate 5 (I-5), I-405, I-82, I-90, and I-182. |
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Metadata elements shown with blue text are defined in the Federal Geographic Data Committee's (FGDC) Content Standard for Digital Geospatial Metadata (CSDGM). Elements shown with green text are defined in the ESRI Profile of the CSDGM. Elements shown with a green asterisk (*) will be automatically updated by ArcCatalog. ArcCatalog adds hints indicating which FGDC elements are mandatory; these are shown with gray text.
This is a derived layer that was compiled from portions of the U.S. Census TIGER Roads, Washington State DNR GIS Transportation Data Layer, and British Columbia Roads. This combination of road types includes TIGER Interstate highways distinguished by the presence of interchanges. They have multiple lanes of traffic, and opposing lanes are separated by a median strip (TIGER field CFCC2 = “A1”). It also includes visually matched DNR roads for which Road Class = “Primary”). Finally, it includes B.C. Digital Road Atlas roads for which ROAD_CLASS = “freeway”, with the exception of a few roads identified by the Modeling Team as belonging in the Major Highway category. Though traffic volumes at any particular location along these highways can vary considerably, these road types tend to carry the highest traffic volumes and are designed for relatively high speeds. Annual Average Daily Traffic Volumes are almost always above 2000 vehicles and commonly exceed 25,000 vehicles. Examples include Interstate 5 (I-5), I-405, I-82, I-90, and I-182.
Roads data were used in models to represent landscape features offering varying levels of resistance to wildlife movements. The ultimate goal was to identify connected networks of wildlife habitat that offer the best conditions for wildlife survival and connectedness.
This GIS dataset is part of a suite of wildlife habitat connectivity data produced by the Washington Wildlife Habitat Connectivity Working Group (WHCWG). The WHCWG is a voluntary public-private partnership between state and federal agencies, universities, tribes, and non-governmental organizations. The WHCWG is co-led by the Washington Department of Fish and Wildlife (WDFW) and the Washington Department of Transportation (WSDOT). The statewide analysis quantifies current connectivity patterns for Washington State and adjacent areas in British Columbia, Idaho, Oregon and a small portion of Montana. Available WHCWG raster data include model base layers, resistance, cost-weighted distance, landscape integrity networks, focal species networks, and focal species guild networks. Grid cell size is 100meters x 100meters. Habitat concentration areas, landscape integrity core areas, and linkage maps reside in raster and vector format. Project background can be found in the report: Washington Wildlife Habitat Connectivity Working Group (WHCWG). 2010. Washington Connected Landscapes Project: Statewide Analysis. Washington Departments of Fish and Wildlife, and Transportation, Olympia, WA. Online linkage: http://www.waconnected.org Distance to Road - Road effects are characterized for each road type within each of four distance bands: Centerline, 0-500 meters, 500-1000 meters, and >1000 meters. Centerline road effects can include both behavioral avoidance and injury or mortality. Other distance bands can cause behavioral avoidance that varies by species. The causes of behavioral avoidance can include noise, odors, the presence of people, and a variety of visual cues. Disturbance effects are expected to diminish with distance, depending on the species and its behavior/vulnerabilities. The USA and British Columbia transportation vector data sets were merged into a single layer. Each road type was extracted and converted to 100-meter cell raster. For each raster road type, a raster buffer was generated using Euclidean distance from the raster line. Euclidean distances 0 to 500 meters, 500 to 1000 meters, and greater than 1000 meters were assigned to classes 3, 2, and 1 respectively (Appendix B). Class 4 was assigned to the raster road "centerline" from which Euclidean distances were measured The final raster buffers are uniform for straight line segments and form true buffer distances from the center raster line. However as the transportation lines become more sinuous, raster representation of buffer distances become more variable. The Euclidean distance procedure provided an expedient GIS methodology to build zones around the large number of transportation lines.
See WHCWG (2010) report Appendix C
The Washington Wildlife Habitat Connectivity Working Group (WHCWG) produced these data which represent a regional analysis that portrays conditions at a regional scale. Applying these data at finer, more local scales is likely to increase uncertainty in terms of accuracy and applicability for local land use decisions. However, for the scale at which they were developed, these products are state-of-the-art, peer-reviewed representations of landscape variables and connected habitat networks. Despite this, the WHCWG makes no guarantee concerning the content, accuracy, completeness, or the results obtained from queries or use of WHCWG data, other than those for which the data was developed and its intended use. The WHCWG shall not be held liable for improper or incorrect use of the data described and/or contained herein. The WHCWG model input data were obtained from a wide range of state and federal jurisdictions in the USA, as well as from Canadian federal and provincial levels of government. The WHCWG expended great effort to compile the best GIS data within constraints imposed by data development costs, available compilation sources, and available staff resources. Inherent in any data set used to develop graphical representations, are limitations of accuracy as determined by, among others, the source, scale and resolution of the data. The products and data from this statewide analysis convey a wealth of information relevant to conservation of Washington's wildlife and though they represent the state of the art, they rely on imperfect data, knowledge, and assumptions. We strongly suggest that readers thoroughly understand our methods and the limitations of those methods prior to applying our results. The data user should note Chapters 2 and 4 and appendices in the WHCWG December 2010 final report for further details. Online linkage to final report: http://www.waconnected.org
600 Capitol Way N
Washington's Wildlife Habitat Connectivity Working Group (WHCWG)
Source scale denominators for the three input data sources were 20000, 24000, and 100000.
Selected B.C. Digital Road Atlas roads for which ROAD_CLASS = "freeway". with the exception of a few roads identified by the Modeling Team as belonging in the Major Highway category. Merged with selected TIGER roads for which CFCC2 = "A1", and with Washington DNR roads for which Road Class = "Primary". Ran the Euclidean Distance function on the merged vector lines, then ran Reclass on the resulting raster to group distances into: 4: Centerline; 3: 0 to 500 meters from centerline; 2: >500 to 1000 meters from centerline; and 1: >1000 meters from centerline.
Metadata imported.
Internal feature number.
ESRI
Distance Range from Freeway centerline
Road Centerline
Distance from centerline is >0 meters and <= 500 meters
Distance from centerline is >500 meters and <= 1000 meters
Distance from centerline is >1000 meters
600 Capitol Way N