1. Role of Economics in W&W Project and in Climate Change Projects Explain how land use patterns evolve over time Forecast future land use change Determine how different policies might produce different future land use patterns

2. How Do Different Approaches to Modeling Land Use Change Compare? Build-Out Analysis: Accepts Transportation Analysis Zone Small Area Population Forecasts Spreads Forecasted Population Change Over Space According to Zoned Densities Geostatistical Simulation (cellular automata) Landscape is Divided into Cells Transition Rules are Functions of State and Location of Cell and State of Neighbor

3. Economic Modeling Model is “process-based”, “mechanistic”, “behavioral” Parcel Owner Chooses Optimal Time and Density of Development Factors Taken Into Account that Affect Decision are: Value of parcel in undeveloped use Value of parcel in developed use Costs of converting parcel to developed use … and how these are changing over time…

4. Build-Out AnalysisGeostatistical Simulation (e.g. Sleuth) Economic Modeling Unit of Observation Transportation Analysis Zone Cell in landscapePrivately owned parcel of land Nature of Approach Accounting procedurePattern-basedProcess-based Nature of land use change process Deterministic process dictated by regulations Stochastic process with transition rules based on: “slope”, “spread”, “breed”, “dispersion”, “road gravity” coefficients Stochastic model of behavior of land owners (choosing optimal timing of development and optimal density of development) “Driving Forces” Current maximum density allowed by zoning State of current land cover Visible features of landscape (location, physical characteristics) Value in undeveloped use, Value in developed uses, and Conversion costs, All as functions of: Current land cover Physical, locational features Public goods provision Relevant regulations …

5. Build-Out Analysis Geostatistical Simulation (e.g. Sleuth) Economic Modeling Analytical Method GIS overlaysCellular automata models - simulate observed cell changes by calibrating set of 5 transition rule coefficients Discrete choice or hazard model analysis - tests hypotheses and produces parameter estimates for forecasting Treatment of interactions NoneInteractions between cell and neighboring cell important in “spread” rule Interactions important if surrounding land use affects value of land in particular use Treatment of stochastic nature of problem NoneForecasts are probabilistic (probability cell will be converted) Forecasts are probabilistic (probability parcel will be converted) Data usedCurrent zoning in GIS form Landsat data for at least 4 points in time; Road networks for 2 points in time Parcel level data including locations of parcels, GIS data on physical features, regulations, public goods, land cover, … Source of growth pressure information “Small area” population forecasts None, just matches pattern Economic model of housing starts as function of regional economic variables

6. Other modeling approaches fail to account for the fact that… you can’t predict future land use outcomes under varying policies. If you don’t know how policies affect individuals’ decisions… policies do not dictate outcomes; they provide incentives/disincentives or constraints on individuals’ decisions.

7. Examples of Growth Control Policies “Downzoning” (increasing the min. lot size or decreasing the maximum allowable density) Imposing open space and clustering requirements Restricting the provision of public utilities Instituting agricultural preservation programs Designating “Priority Funding Areas” Enforcing adequate public facilities moratoria None can be incorporated in current cellular automata models, but can be incorporated in models of economic decision making.

11. Tasks for Economics Component in Current Climate Change Project Produce 20-50 year land use change forecasts: Using the “build out” analysis approach Using the economic modeling approach – with and without Smart Growth policies Devise a means of translating probabilistic outcomes of models into forecast scenarios usable by other PI’s: Use Monte Carlo simulations to determine variability of resulting pattern due to inherent randomness of process.

12. Tasks for Economics Component in Proposed Climate Change Project Determine spatially-explicit scenarios, taking into account the following dynamic elements: growing population and changing demographics; changing land use policies; receding coastline due to sea level rise; adoption of climate change response policies (e.g. taxes on carbon emissions, subsidies for carbon sequestration)