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Statewide Land-Use Allocation Model for Florida. Stephen Lawe, John Lobb & Kevin Hathaway Resource Systems Group. Presentation Outline. 1. Land Use Allocation Model (LUAM) Implementation & Overview 2. Data on Land Use Patterns Challenges of Estimation 3. Model Structure & Calibration
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Statewide Land-Use Allocation Model for Florida Stephen Lawe, John Lobb & Kevin HathawayResource Systems Group
Presentation Outline 1. Land Use Allocation Model (LUAM) • Implementation & Overview 2. Data on Land Use Patterns • Challenges of Estimation 3. Model Structure & Calibration 4. Results - Sensitivity to Accessibility
LUAM Process – Turnpike Integrated Model Structure Land Use Allocation Model (LUAM) Described in this presentation 5-year lag Auto Trip Table Truck Trip Table As described in a presentation by Songer, et al. on Wednesday and Adler, et al. on Thursday Auto Toll-Free Trips Truck Toll Trips Truck Toll-Free Trips Auto Toll Trips Network Volumes and Travel Times
Written in C++ and integrated with transportation models: Currently integrated into Florida’s Turnpike Enterprise State Model Built to integrate into MPO models Allocates housing and employment growth at TAZ-level Growth total inputs at user-defined geography State, County, MPO, other. LUAM Model runs in 2-4 minutes LUAM Process – Model Fundamentals St Petersburg
LUAM Process – Model Development Plan • Goal: Incremental improvements while always having a model that supports analysis • 4-step process • Estimate and calibrate model using aggregate town & county trends • Re-estimate statewide model with parcel-level data from selected counties • Complete statewide model estimation with parcel-level data for all counties in state • Continue to refine input data and policy control hooks
Legal & Physical Constraints Florida - Calibrated Parameters Generate Travel Impedance Matrix Land Use Data – Overview of Process Total Land Available Base Year Zonal Land Use • Households • Employment Determine Remaining Developable Land Accessibility and Overall Attractiveness Future Growth Increment Allocate new Increment of Land Use • Households • Employment TAZ Land Use Forecasts Forecasting Analysis Procedures • Households • Employment 5 Year Dynamic Land Use Lag
Land Use Data – Development History (parcel level) Fort Myers Cape Coral
Land Use Data – Urban Growth Boundaries (legal constraints)
ἀ + β1x1 + β2x2 +…+ βkxk e Pij = Pr(Yij = 1 | Xij) = ἀ + β1x1 + β2x2 +…+ βkxk 1 + e 2. How many houses & emp. will build on the consumed land? Tobit Model Estimates: Densityij = amount of land use j in TAZ i Densityij = β1x1 + β2x2 +…+ βkxk + ε Model Structure – Two Stage Logit / Linear 1. What percent of the available land is consumed? Logit Model Estimates: Pij = Probability of TAZ i, land use j, being developed
Model Structure – Calibration Results (Residential Growth 1980 - 2005) Observed Growth Modeled Growth Pearson’s Correlation TAZ= .58 ZIP = .81
Statewide Application – 2015 households • Run model and look for outliers • Run without controlling and compare to county control totals • Correlation of .93 with 2015 medium BEBR growth totals • Bureau of Economic and Business Research
Model Sensitivity Test - Accessibility • Approximate Population to Employment Ratio • Cape Coral: 3 pop to 1 emp • Fort Myers: 1 pop to 2 emp • Doubling of bridge capacity during 1990s • Large subsequent observed increase in development in Cape Coral • Population increase by 75% between ’95 – ’05 • Twice the rate of growth in ’80s and ’90s • Modeled removal of new bridge capacity • Population increase by 55% between ’95 – ’05 (as compared to 75% with the bridges)
Summary and Conclusions • FL TSM v1 completed in 2006, has been used for major planning applications (Doherty, Fennessy & Songer, Wednesday presentation – Session 17) • Land-use model built on a high-quality, maintained statewide GIS database • Simplified initial model structure supports focus on critical data quality and maintenance issues • Work is continuing on estimating one set of land-use models for the State • Statewide Land Use Model creates growth forecasts in a consistent manner which is important to the Florida’s Turnpike Enterprise