Illiana Corridor Tier I & II EIS

    Market

  • Economic Development
  • Local Governments
  • State Agencies

    Services

  • Engineering
  • Environmental
  • Geospatial
  • GIS
  • Roadways + Interchanges
  • Traffic + Safety
  • Transportation

    Locations

  • Will and Kankakee Counties, Illinois and Lake County, Indiana

The Illinois Department of Transportation, Indiana Department of Transportation, and the Federal Highway Administration were the joint lead agencies for the evaluation of a transportation corridor connecting Interstate 55 in Illinois to Interstate 65 in Indiana: The Illiana Corridor.

The Illiana Corridor evaluation was a tiered Environmental Impact Statement (EIS). The Tier One EIS evaluated potential corridors to determine the alternative that overall had the best balance of avoiding social and environmental impacts, providing transportation benefits, and incorporating community goals. Over 100 alternative concepts were developed for the Illiana study. Through stakeholder involvement, resource agency coordination, and evaluations that included Geographic Information Systems (GIS) analysis, the number of alternatives was reduced to three build alternatives, in addition to a no-action alternative. The build alternatives ranged in length from 47 miles to 51 miles and were compared to each other based on key evaluation factors, including:

  • Socioeconomic Impacts
  • Travel Performance
  • Environmental Impacts
  • Construction Impacts
  • Community Land Use Compatibility
  • Stakeholder and Resource Agency Input

HR Green served as a sub-consultant to Parsons Brinckerhoff, Inc. for the Tier One EIS and the Tier Two EIS. The four main roles served by HR Green for Tier One included data collection, conceptual level design and cost analysis, public involvement, and environmental analysis. GIS was central to the data collection and environmental analysis components.

The Tier One EIS process required a tremendous amount of data collection so the various disciplines could thoroughly evaluate the project alternatives. Much of this was spatial data that was organized into a GIS Database. HR Green was responsible for obtaining a wide variety of data from the various governing bodies and intermodal centers within Will County, Illinois. That data included zoning maps, land use plans, transportation improvement plans, traffic impact studies, and GIS datasets to name a few. In addition, HR Green was tasked with the collection of traffic data at over 40 locations throughout the study area. The traffic data was used to calibrate and verify the travel demand model.

HR Green was also responsible for the socio-economic analysis and the agricultural analysis for the Illiana Corridor Tier One and Tier Two EIS. These analyses were informed by future impacts calculations made by running a custom GIS model designed by HR Green GIS staff. This model calculated possible future impacts on different socioeconomic and agricultural criteria as delineated by data compiled in the GIS database from resource agencies and environmental field surveys. The model was run to compare potential future impacts from the three build alternatives, the no-build alternative, as well as several interchange options at IL-53. Based on the three main alternatives evaluated, one of the major differences was the higher number of impacts on the built environment (relocations) for the northern alternative compared to the higher agricultural impacts for the two southern alternatives.

The GIS model was re-run numerous times over the course of the Tier Two analysis as changes were made to alternative geometry or as updated socioeconomic and agricultural data was integrated into the database. The GIS model provided a systematic and reproducible approach that was not only defensible, as all the logic was documented, but also far more efficient and less susceptible to human error than a less integrated or piecemeal approach. The GIS model increased the productivity of the Tier Two effort significantly and made it possible to meet tight project deadlines with data-driven analysis.

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