Transcript Modeling the Dynamics of Urban Development and the Effect

Modeling the Dynamics
of Urban Development
and the Effect of Public Policies
The Human Dimension of PRISM
Marina Alberti
Alan Borning
Paul Waddell
Outline of Talk
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Scope of the Human Dimension
The UrbanSim model system
Land cover change model
Current research agenda
Objectives for this Year
The Scope of the Human Dimension
• Inputs
– Starting conditions: inventories of land use, land cover,
real estate, business locations, and household locations
– Macro-economic and demographic trends
– Local infrastructure investments and regulations/pricing
(transportation, water, sewer)
– Land use policies (growth management, comprehensive
land use plans, environmental regulations)
• Outcomes
– Spatial patterns of land use and land cover change
– Spatial patterns of real estate development and prices
– Spatial patterns of business and household location
UrbanSim Modeling Approach
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Model choices of agents
Discrete choice models (multinomial logit)
Microsimulate individual agents
Dynamically simulate annual time steps
Model market interactions
Use very disaggregate spatial units (150 Meter
grid cells)
A 150 Meter Grid Cell in the Queen Anne
Neighborhood
Classification of Development Types
Current UrbanSim Components
External
Models
Travel Demand
Model System
0
User
Inputs
Scenario
Assumptions
Economic and
Demographic
Transition
2
Location
Choice
4
Land Price
6
Mobility
3
Real Estate
Development
5
SQL
Database
Travel Model
Outputs
Model
Coordinator
Control Totals
Macroeconomic
Model
0
User
Specified
Events
Accessibility
1
GIS
Factors Considered in Residential Location Model:
• Household Characteristics
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Income
Age
Presence of children
Number of workers
Number of Vehicles
• Housing Characteristics
– Cost
– Quality
– Density
• Neighborhood Characteristics
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Neighborhood housing density
Neighborhood commercial and industrial space
Neighborhood retail employment
Neighborhood land values
• Regional Accessibility to Employment by Transit and Auto for
– 0 car households
– 1 car households
– 2+ car households
All independent variables are endogenous in the model system
Factors Considered in Employment Location Model:
• Employment Characteristics
– Industry Sector
• Nonresidential Space Characteristics
– Cost
– Type of Space
– Density
• Local Characteristics
– Land values
– Agglomeration Economies: mix of jobs by sector
– Proximity to Freeways and Arterials
• Regional Accessibility to Population
All independent variables are endogenous in the model system
Factors Considered in Real Estate Development Model
• Site characteristics
– Existing development characteristics
– Land use plan
– Environmental constraints
• Urban design-scale
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Proximity to highway and arterials
Proximity to existing development
Neighborhood land use mix and property values
Recent development in neighborhood
• Regional
– Access to population and employment
– Travel time to CBD, airport
• Vacancy rates
All independent variables are endogenous in the model system
Factors Considered in Land Price Model
• Site characteristics
– Development type
– Land use plan
– Environmental constraints
• Regional accessibility
– Access to population and employment
• Urban design-scale
– Land use mix and density
– Proximity to highway and arterials
• Vacancy rates
All independent variables are endogenous in the model system
Assessment of Current Status
• Operational urban simulation system
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Open Source software at www.urbansim.org
Generic SQL Database for read/write
Interoperates with GIS
Version 2.0 now completed (complete re-engineering)
• Has been applied in Eugene-Springfield,
Honolulu, Salt Lake City, Houston now starting
• Puget Sound application to be supported by Puget
Sound Regional Council
Land Cover Change Model
• A new model component under development
• Predicts probability of 30 meter cell changing land
cover classification during a single year
• Separate model specifications for differing
conditions:
– Cells affected by land use change in immediate area
– Urban-rural fringe areas not immediately affected by
land use change event
– Urban (built up) areas not affected by land use change
– Rural (agricultural, forest) areas not affected by land
use change
Land Cover Change
The probability of transition of a pixel of initial land cover i at
time t having the same land cover class at time t+1 (j=0) or
changing to one of the other land cover classes (j = 1…J)
can be written as a multinomial logit:
(X 
'
Pij 
Where:
e
J
e
j
)
j
 1,...,
J
( X s )
'
s j
Pij is the probability of land cover at a given grid cell at time t
having the same cover class at time t+1 or changing to another
cover class.
j is a vector of estimated logit coefficients.
J is the number of land cover states
Table 1 Land Cover Classes
nd
Top Level Classes
2
Paved Urban
Broad Urban
Paved Urban >75%
Mixed Urban > 75%
Mixed Urban 25-75%
Mixed Urban <25%
Vegetation
Bare Soil
Clear Cut
W ater
Level Classification
Coniferous Forest
Deciduous Forest
G rass Shrub Crops
Final Classification
Paved Urban
Mixed Urban
Mixed Urban G rass
Mixed Urban Forest
Coniferous Forest
Deciduous Forest
G rass Shrub Crops
Bare Soil
Clear Cut
W ater
Independent Variables
Intensity of development event
Devtype transition 1…24
Specific attributes of site
Land cover
Slope of cell
Aspect of cell
Soil quality
Parcel ownership
Parcel size
Land value
Distance to critical areas
Distance to nearest road
Distance to water infrastructure
Distance to critical areas
Distance to nearest road
Distance to CBD
Distance to forest source area
Distance to nearest land cover transition
Distance to nearest development event
Restriction on minimum lot size
Continued….
Independent Variables
Spatial context of development
Built-up density
Road density
% High erodible soils
% of prime farmland
Mean patch size of land use/cover
Contagion of land use/cover
Dominant land use/cover
Transition to land cover
Residential units recently added
Commercial units recently added
Road capacity recently added
Change in mean patch size
Position on the urban gradient
Urban Growth Boundary
La n d C o v e r C h a n g e in K m 2
E n tir e Im a g e
9000
8000
7000
s q u a re k m
6000
5000
1991
4000
1999
3000
2000
1000
0
m ixe d
urb a n
7 .8 2 %
p a ve d
6 .7 1 %
fo re st
-8 .2 1 %
g ra ss
1 0 .1 4 %
b a re so il
1 8 .9 7 %
cle a r cut
2 6 .9 6 %
Current Research Projects
• National Science Foundation, Urban Research Initiative,
“Reusable Modeling Components for Simulating Land
Use, Transportation, and Land Cover,” Marina Alberti,
Alan Borning, Scott Rutherford, Paul Waddell, $439,357,
1999-2001.
• National Science Foundation, “The Impact of Urban
Patterns on Ecosystem Dynamics,” Marina Alberti, Derek
Booth, Kristina Hill, and John Marzluff, $424,977, 19992003.
Current Research Projects
• National Science Foundation, Information Technology
Research Initiative, “Interaction and Participation in
Integrated Land Use, Transportation, and Environmental
Modeling,” Alan Borning, Batya Friedman, Mark Gross,
David Notkin, Zoran Popovic, and Paul Waddell,
$3,500,000, 2001-2006.
• National Science Foundation, Digital Government
Program, “Software Architectures for Microsimulation of
Urban Development, Transportation, and Environmental
Impact,” Alan Borning, David Notkin, and Paul Waddell,
$600,000, 2001-2004.
Current Research Projects
• National Science Foundation, Biocomplexity Program,
“Modeling the Interactions between Real Estate
Development, Land Cover Change, and Bird Diversity,”
Marina Alberti, Mark Handcock, John Marzluff, Paul
Waddell, $1,128,818, 2001-2004.
• Federal Highway Administration, “Case Study on the
Application of UrbanSim to the Salt Lake City Region,”
Paul Waddell and Alan Borning, $150,000, 2002-2003.
• Puget Sound Regional Council, “Development of a Land
Use Model,” Paul Waddell, Alan Borning, Marina Alberti,
$150,000, 2002-2003.
Proposed Research Objectives for 2002-3
(funded by sources other than PRISM)
• Development of the data and calibration of the existing
UrbanSim model specification for the Central Puget Sound
region (King, Kitsap, Pierce, and Snohomish counties) –
pending funding from PSRC.
• Development of land cover classification and accuracy
assessment for Landsat images every two years from 1986
to 2001.
• Calibration and testing of the initial version of the land
cover change model for at least King County – pending
funding from King County DNR.
• Work on an indicators and evaluation component for
UrbanSim, to support a set of predefined indicators, and
flexibility to allow users to modify and add indicators.
PRISM-Specific Objectives
• Developing close collaboration with the Crystal Team, to
set up the protocols for coupling UrbanSim and Crystal,
jointly defining the specifications for a water demand
model, and implementing the model as a component within
the UrbanSim architecture.
• Developing close collaboration with the DHSVM Team to
set up the protocols for coupling UrbanSim and DHSVM
through the land cover change model and jointly defining
specifications to add the artificial drainage to the
hydrological model in urbanizing landscapes.
PRISM-Specific Objectives
• Expanding the scope of the UrbanSim Indicators and
Evaluation component to incorporate more environmental
indicators, with input from other PRISM teams. Some or
all of these additional indicators would come from other
PRISM model outputs, so this would also require setting
up protocols for passing the information from those models
to the indicator component.
• Restructuring and teaching an Introduction to Urban
Simulation course, scheduled for Spring 2003. It will
serve as a workshop and introduction to urban simulation
using UrbanSim, focusing on the application of the model
to the Puget Sound, and development of indicators and the
creation and evaluation of scenarios.