urban planning by simulation of population growth cirano iochpe flavio rech wagner marcia aparecida...
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Urban Planning by Simulation of Population Growth
Cirano IochpeFlavio Rech WagnerMarcia Aparecida da Silva AlmeidaGuillermo Nudelmann HessAndré Dias Bastos
GEOINFO 20046th Brazilian Symposium on Geoinformatics
Outline
• Related work
• Introduction
• The System•The beginning •Functions and functionalities•The architecture•Tools and technologies•The covering map•Modelling
Outline
• Related work
• Introduction
• The System
• Next Steps
• Last considerations
•The beginning •Functions and functionalities•The architecture•Tools and technologies•The covering map•Modelling
Introduction
• InterSIG Project• Main goal: to integrate a set of algorithms,
techniques, tools, data models, and protocols into an Internet based system that supports both access and manipulation of geographic data
Introduction
• Simulation Subsystem of Geographic Scenarios:
• Fase 3 of the InterSIG Project• Main Goal: to offer a web based simulation system
that can be remotely used by municipalities to support urban planning activities
• Focused on urban growth• Partners• Data availability
Related Work
• A number of systems has been proposed to address urban growth simulation• Most of them are not available on the Internet• Most of them are dependent on specific GIS
platforms and data formats• UrbanSim• Uplan
The InterSIG Simulation Subsystem - The Beginning
• Partnership: Porto Alegre City Hall• Project: “Planning the Future of the Lomba do
Pinheiro District” • Availability of geographic data
• Hidrology, declivity, population,
infrastructure
• Public resources – schools,
public health centers,
kinder gardens, squares
The InterSIG Simulation Subsystem - The Beginning
• Partnership: Porto Alegre City Hall• Project: “Planning the Future of the Lomba do
Pinheiro District” • Needs
• Visualize covering or influence area of a public resource
• Simulate inclusion of new resources
• Simulate increasing the population and its consequence to the
covering area of public resources
The InterSIG Simulation Subsystem - The Beginning
• Visualizing influence zone of a public resource
The InterSIG Simulation Subsystem - The Beginning
• Porto Alegre City Hall• Rules about public resources
• Declivity < 25%• Each type of public resource has a specific range of
influence given no geographic obstacles are provided• Each instance of public resource has a maximum
number of citizens which it can serve at any time
The System
• Functions and functionalities• Accessible through the Web• Upload of geographic scenarios by the user• Upload of simulation rule sets by the user• Generation of covering maps• Simulation of the evolution of influence areas during
a time interval
The System Architecture
GML / SHPGeographic data
XMLrules
usuáriousuário
Geographic scenariomanager
(wrapper)
GeotoolsAPI
SimulationCovering
map
SimuladorEngine
Covering
InterfaceWEB
Rules manager(Wrapper)
Cellularautomata
Area (map)Neighbourhood (map)StateTransition Rules
Files(shp, gml)
ProgramaFiles(Java)
Rulesfiles(xml)
MetadataDBMS
Tools and Technologies
• Tools and technologies• JSP/Servlets to interface• GeoTools to handle geographic information• GML, XML and Shapefiles to exchange data• An owner simulator kernel in Java• SVG to visualize maps
The covering map algorithm
SchoolDarn Canal Stream Lake River Declivity
Generate buffer zone
Generate hidrology layer
Generate appropriated geographical zones
Generate influence zones
Sectors
Covering Map
The covering map algorithm
Modeling – The Major Difficulty
• Find a urban growth population model• Just rules are not enough to build the system• Population is distributed following a
growth/distribution model• Each urban area can have a different model• How to obtain a generic (basic) model?
• Dynamic modeling
Finding a Model
• Main approaches in dynamic modeling of urban growth• Cellular automata• Heuristic methods• Neural networks
Finding a Model
• Spatial Dynamic Modeling• Simulation of urban
land use changes• Claudia Almeida’s
(INPE) phD tesis• Empirical probabilistc
methods
Finding a Model
• Spatial Dynamic Modeling• Simulation of urban land use changes
• Bayes theorem
• How about Bayesian Networks?• At first glance, it can be used to obtain a model
directly from a database
Finding a Model
• Bayesian networks
• Qualitative aspect• Variables and their relationships (nodes and edges)
• Quantitive aspect• Intensity degree of relationship between variables
(probabilities)
P(Xa) P(Xd|Xa)
P(Xb|Xa) P(Xc|Xb,Xd)
Finding a Model
• Bayesian networks
Visit Asia?(A)
Tuberculosis?(T)
Lung cancer?(C)
(T) or (C)?(O)
Bronchisis?(B)
Smooker?(S)
X-ray+(X)
Dispnesis(D)
Finding a Model – Next steps
• Steps to build a Bayesian Network• To obtain variables• To obtain a causal relationship between
variables• From the database
• To obtain condicional probabilities tables• Through bayesian learning methods
Conclusions
• To build a generic tool in terms of modeling is a quite dificult task
• To have the possibility of developing a new technique evolving dynamic modeling is quite interesting
• Next step is to continue investigating Bayesian Networks as the possible solution of our problem