Dialog for Gateway FuturesDialog for Gateway Futures::A Progress ReportA Progress ReportDialog for Gateway FuturesDialog for Gateway Futures::A Progress ReportA Progress Report

Dr. Brian Deal

University of Illinois

Gateway LEAM (gLEAM)Gateway LEAM (gLEAM)Gateway LEAM (gLEAM)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

Project HistoryProject HistoryProject HistoryProject 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

SummarySummarySummarySummary

Modeling Data Land-use allocation Land-use drivers Impact models

Other achievements

ModelingModelingModelingModeling

EconomicModel

Households,Jobs

SME

Land use (T)GIS MapsImpacts

SOCIAL MODEL

UTILITIES

SPONTANEOUS

NEIGHBORS

DEM

GROWTH TRENDS

PRICE

PLANNING MAP

TRANSPORTATION MODEL

SOCIAL MODEL

UTILITIES

SPONTANEOUS

NEIGHBORS

DEM

GROWTH TRENDS

PRICE

PLANNING MAP

TRANSPORTATION MODEL

SOCIAL MODEL

UTILITIES

SPONTANEOUS

NEIGHBORS

DEM

GROWTH TRENDS

PRICE

PLANNING MAP

TRANSPORTATION MODEL

Cell-based Drivers (Stella)

Land use(T+1)

Impacts

Regional Driver

DevelopmentProbability

DevelopmentProbability

Calibration WeightingCalibration Weighting

DataDataDataData

Current land-cover data Illinois only Missouri currently not

available

SummarySummarySummarySummary

Modeling Data Land-use allocation Land-use drivers Impact models

Other achievements

Land-Use AllocationLand-Use AllocationLand-Use AllocationLand-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

Regional EconomyRegional EconomyRegional EconomyRegional Economy

Regional economy captured in a two-part model a nine-sector input-output model an econometric model

Man

FG

SLG

Srv

FIRE

RTd

WTd

TCPU

Con

ExtExtractive

Construction

TCPU

Wholesale Trade

Retail Trade

FIRE

Services

State and Local Government

Federal Government

Manufacturing

Buyers Sellers

ManFG

SLG

Srv

FIRE

RTd

WTd

TCPU

Con

ExtExtractive

Construction

TCPU

Wholesale Trade

Retail Trade

FIRE

Services

State and Local Government

Federal Government

Manufacturing

Buyers Sellers

Regional EconomyRegional EconomyRegional EconomyRegional Economy

Regional economy captured in a two-part model a nine-sector input-output model an econometric model

More precise estimates of regional growth

Regional EconomyRegional EconomyRegional EconomyRegional Economy

0.073117,8371,730,4521,612,6150.084117,4101,507,0801,389,670Total, All Industries

0.0496,529138,767132,2380.0904,77058,05053,280SLG

-0.076-3,52942,80546,334-0.058-1,00016,28017,280Federal Government

0.10657,466598,938541,4720.14069,120562,300493,180Services

0.0263,544140,410136,8660.0675,62089,26083,640FIRE

0.09625,909295,283269,3740.10926,220265,930239,710Retail Trade

0.0765,95084,66378,7130.0382,74075,50072,760Wholesale Trade

0.10810,875112,004101,129-0.001-60101,730101,790TCPU

-0.013-2,392182,943185,335-0.044-8,140175,250183,390Manufacturing

0.13713,093108,47695,3830.20715,53090,66075,130Construction

0.01539326,16425,7710.2312,26012,0609,800Extractive

ChangeChangeProjectedActualChangeChangeProjectedEstimatedIndustry

%Gross20102000%Gross20102000

LEAMMERIC

0.073117,8371,730,4521,612,6150.084117,4101,507,0801,389,670Total, All Industries

0.0496,529138,767132,2380.0904,77058,05053,280SLG

-0.076-3,52942,80546,334-0.058-1,00016,28017,280Federal Government

0.10657,466598,938541,4720.14069,120562,300493,180Services

0.0263,544140,410136,8660.0675,62089,26083,640FIRE

0.09625,909295,283269,3740.10926,220265,930239,710Retail Trade

0.0765,95084,66378,7130.0382,74075,50072,760Wholesale Trade

0.10810,875112,004101,129-0.001-60101,730101,790TCPU

-0.013-2,392182,943185,335-0.044-8,140175,250183,390Manufacturing

0.13713,093108,47695,3830.20715,53090,66075,130Construction

0.01539326,16425,7710.2312,26012,0609,800Extractive

ChangeChangeProjectedActualChangeChangeProjectedEstimatedIndustry

%Gross20102000%Gross20102000

LEAMMERIC

(Missouri Economic Research and Information CenterMissouri Department of Economic Research)

Regional EconomyRegional EconomyRegional EconomyRegional Economy

-4.2272,799,3422,681,0022030

-3.1352,752,314-4.3182,786,3672,666,0392025

-1.7832,697,986-3.9352,758,4342,649,8892020

-0.3672,638,658-3.3362,719,7012,628,9632015

0.8642,582,637-2.3032,666,3682,604,9512010

1.3252,541,951-1.2462,608,1422,575,6432005

% DifferenceModified LRTP% DifferenceCensusLEAM

-4.2272,799,3422,681,0022030

-3.1352,752,314-4.3182,786,3672,666,0392025

-1.7832,697,986-3.9352,758,4342,649,8892020

-0.3672,638,658-3.3362,719,7012,628,9632015

0.8642,582,637-2.3032,666,3682,604,9512010

1.3252,541,951-1.2462,608,1422,575,6432005

% DifferenceModified LRTP% DifferenceCensusLEAM

Regional EconomyRegional EconomyRegional EconomyRegional Economy

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

Regional EconomyRegional EconomyRegional EconomyRegional EconomyInvestment of $30 millions in Construction Sector in 3 years

0

50

100

150

200

250

2001 2006 2011 2016 2021 2026

Ext

ra J

ob

s C

reat

ed

RSrvEmp

RConEmp

RManEmp

RFirEmp

RTpuEmp

RRtdEmp

RWtdEmp

RSlgEmp

RFedEmp

Residential UseResidential UseResidential UseResidential 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

Residential UseResidential UseResidential UseResidential Use

Open SpaceOpen SpaceOpen SpaceOpen 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

Total Open Space

Population

Desired Level of Service

Actual Levelof Service

Level of Service

Gap

Build New Open Space

Delay

Population Growth

Total Open Space

Population

Desired Level of Service

Actual Levelof Service

Level of Service

Gap

Build New Open Space

Delay

Population Growth

Open SpaceOpen SpaceOpen SpaceOpen Space

SummarySummarySummarySummary

Modeling Data Land-use allocation Land-use drivers Impact models

Other achievements

Land-use DriversLand-use DriversLand-use DriversLand-use Drivers

Drivers determine where in the region new land uses locate

New drivers added to localize the model Social factors Proximity Highway congestion

Social FactorsSocial FactorsSocial FactorsSocial 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

0 0.2 0.4 0.6 0.8 1

0-.025

.025-.05

.05-.1

.1-.15

.15-.2

.2-120% to 100%

15% to 20%

10% to 15%

5% to 10%

2.5% to 5%

0% to 2.5%

Development Likelihood

VacancyRate

0 0.2 0.4 0.6 0.8 1

0-.025

.025-.05

.05-.1

.1-.15

.15-.2

.2-1

Development Likelihood

> $70k

$60k to $70k

$50k to $60k

$40k to $50k

$30k to $40k

$0k to $30k

HouseholdIncome

Social FactorsSocial FactorsSocial FactorsSocial 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

Significance shown with filter of p=.001after 999 random permutations

High Tract, High Neighbors

Low Tract, Low Neighbors

Low Tract, High Neighbors

High Tract, Low Neighbors

Significance shown with filter of p=.001after 999 random permutations

High Tract, High Neighbors

Low Tract, Low Neighbors

Low Tract, High Neighbors

High Tract, Low Neighbors

Significance shown with filter of p=.001after 999 random permutations

High Tract, High Neighbors

Low Tract, Low Neighbors

Low Tract, High Neighbors

High Tract, Low Neighbors

Significance shown with filter of p=.001after 999 random permutations

High Tract, High Neighbors

Low Tract, Low Neighbors

Low Tract, High Neighbors

High Tract, Low Neighbors

1990

2000

ProximityProximityProximityProximity

Employment Centers Shopping Centers Health Centers Cultural Centers

Highway CongestionHighway CongestionHighway CongestionHighway 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

SummarySummarySummarySummary

Modeling Data Land-use allocation Land-use drivers Impact models

Other achievements

Impact ModelsImpact ModelsImpact ModelsImpact 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

Traffic VolumeTraffic VolumeTraffic VolumeTraffic Volume

Uses a simplified version of the four-step model

2000

2025

Congested Vehicle Sheds

Uncongested Vehicle Sheds

Fiscal ImpactsFiscal ImpactsFiscal ImpactsFiscal 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

Belleville, ILBelleville, ILBelleville, ILBelleville, IL

TotalWhat If? From To Change % Amount Expenditure50% increase in population density 848 1272 People/Sq.Km ($113) -17.3% $542 ($6,521,868)50% increase in number of households 17,603 26,405 Units $27 4.1% $682 $1,122,62550% increase in per-capita sales tax collected $154 $231 $/Person $46 7.0% $701 $1,911,900

Change Per-Capita Expenditure

Without Annexation

With Annexation Difference

Population 59,861 64,963 5,102Households 24,640 26,550 1,910Per Capita Sales Tax $142 $156 $14Per Capita Expenditure $562 $605 $43Total Expenditure $33,641,882 $39,302,615 $5,660,733

AnnexedLand

Water QualityWater QualityWater QualityWater 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

SummarySummarySummarySummary

Modeling Data Land-use allocation Land-use drivers Impact models

Other achievements

Other AchievementsOther AchievementsOther AchievementsOther Achievements

Local Community Engagement Madison County; City of Edwardsville, IL City of Mascoutah, IL

Secure Web site Project management Data exchange with local agencies

ConclusionConclusionConclusionConclusion

Next steps Continued localization

For example, dynamic social model, brownfields

Enhanced impacts For example, fiscal impacts on the margin, water quantity

Scenario runs