1. Dialog for Gateway Futures : A Progress Report Dr. Brian Deal University of Illinois

2. Gateway LEAM (gLEAM)  Objective  Identify long-range land-use change and impacts of different demographic and economic trends, public policy and investment choices.  Generate a collection of scenarios and not a single prediction  Why?  Inform and enhance Long-range Transportation Plan, Gateway Blueprint, and local planning

3. Project History  Successful Proof-of-Concept  Completed December 2003  Produced three simulations of land-use change  Connected with local transportation model  Used as the basis for public dialog  Localizing of LEAM under way  More detailed local data  Additional local drivers and detailed impacts  Scenario runs

4. SummarySummary  Modeling  Data  Land-use allocation  Land-use drivers  Impact models  Other achievements

5. ModelingModeling

6. DataData  Current land-cover data  Illinois only  Missouri currently not available

7. SummarySummary  Modeling  Data  Land-use allocation  Land-use drivers  Impact models  Other achievements

8. Land-Use Allocation  How much land will be consumed by different land uses? Can this be made specific to different parts of the region?  Regional economy  Residential uses  Open space uses

9. Regional Economy  Regional economy captured in a two-part model  a nine-sector input-output model  an econometric model

10. Regional Economy  Regional economy captured in a two-part model  a nine-sector input-output model  an econometric model  More precise estimates of regional growth

11. Regional Economy (Missouri Economic Research and Information Center Missouri Department of Economic Research)

12. Regional Economy

13.  Regional economy captured in a two-part model  a nine-sector input-output model  an econometric model  More precise estimates of regional growth  Scenarios developed  Investment in road projects  An investment of $30 m multiplies to $45 m  Impact is diluted in the long run  Changes in proportion of workers living in the region  Stopping current decline could add $25 million to Gross Regional Product

14. Regional Economy

15. Residential Use  Previous assumption: Intensity of use uniform across the region  Census data show  Population density is not uniform across the region  Household size has been declining  Future simulations will use household size varying across time and space

16. Residential Use

17. Open Space  Allocation and location of open space differs from residential and commercial uses  Allocation: Uses a measure, such as Level of Service (LoS), to compute new land needed for open space  Location: Uses a different set of drivers to affect where new open space is located

18. Open Space

19. SummarySummary  Modeling  Data  Land-use allocation  Land-use drivers  Impact models  Other achievements

20. Land-use Drivers  Drivers determine where in the region new land uses locate  New drivers added to localize the model  Social factors  Proximity  Highway congestion

21. Social Factors  Census data show key social drivers of land- use change in the region are  vacancy rates  Income  rental rate  proportion of residents without vehicles

23. Social Factors  Census data also show  Poverty is clustered in and around the central city, affluence is clustered around the fringes  Disparity between rich and poor is increasing  This can be used to model dynamic effects of social conditions

24. 1990 2000

25. ProximityProximity  Employment Centers  Shopping Centers  Health Centers  Cultural Centers

26. Highway Congestion  Proximity measures are affected by highway congestion  Use measured vehicle counts from year 2000  Compute proportion of highway capacity  Estimate speed on highway  Recompute proximity measures

28. SummarySummary  Modeling  Data  Land-use allocation  Land-use drivers  Impact models  Other achievements

29. Impact Models  Impact models allow assessing consequences of land-use change  We have implemented  Traffic volume  Fiscal impacts  Water quality impacts  These are first-order approximations and not precise estimates

30. Traffic Volume  Uses a simplified version of the four-step model

31. 2000 2025 Congested Vehicle Sheds Uncongested Vehicle Sheds

32. Fiscal Impacts  Analysis of 73 municipalities in the Metro East show per-capita expenditure  Decreases with increasing population density  Increases with increasing city size  Increase with increasing per-capita sales tax collected

33. Belleville, IL

34. Annexed Land

35. Water Quality  Many models of water quality are available  We used L-THIA (US EPA) to compute pollutant loading for  total nitrogen (TN)  total suspended particles (TSP)  total phosphorous (TP)  Pollutant loading responds to quantity of growth

37. SummarySummary  Modeling  Data  Land-use allocation  Land-use drivers  Impact models  Other achievements

38. Other Achievements  Local Community Engagement  Madison County; City of Edwardsville, IL  City of Mascoutah, IL  Secure Web site  Project management  Data exchange with local agencies

39. ConclusionConclusion  Next steps  Continued localization  For example, dynamic social model, brownfields  Enhanced impacts  For example, fiscal impacts on the margin, water quantity  Scenario runs