Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics
Authored by Sara Saeedi
Date Published: 2018
DOI: 10.1016/j.jag.2018.02.012
Sponsors:
No sponsors listed
Platforms:
Java
Model Documentation:
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Mathematical description
Model Code URLs:
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Abstract
With the advancement of computational modeling and simulation (M\&S)
methods as well as data collection technologies, urban dynamics modeling
substantially improved over the last several decades. The complex urban
dynamics processes are most effectively modeled not at the macro-scale,
but following a bottom-up approach, by simulating the decisions of
individual entities, or residents. Agent-based modeling (ABM) provides
the key to a dynamic M\&S framework that is able to integrate
socioeconomic with environmental models, and to operate at both micro
and macro geographical scales. In this study, a multi-agent system is
proposed to simulate residential dynamics by considering spatiotemporal
land use changes. In the proposed ABM, macro-scale land use change
prediction is modeled by Artificial Neural Network (ANN) and deployed as
the agent environment and micro scale residential dynamics behaviors
autonomously implemented by household agents. These two levels of
simulation interacted and jointly promoted urbanization process in an
urban area of Tehran city in Iran. The model simulates the behavior of
individual households in finding ideal locations to dwell. The household
agents are divided into three main groups based on their income rank and
they are further classified into different categories based on a number
of attributes. These attributes determine the households' preferences
for finding new dwellings and change with time. The ABM environment is
represented by a land-use map in which the properties of the land
parcels change dynamically over the simulation time. The outputs of this
model are a set of maps showing the pattern of different groups of
households in the city. These patterns can be used by city planners to
find optimum locations for building new residential units or adding new
services to the city. The simulation results show that combining
macro-and micro-level simulation can give full play to the potential of
the ABM to understand the driving mechanism of urbanization and provide
decision-making support for urban management.
Tags
Agent-based modelling
Simulation
GIS
Land-use
Urban growth
Validation
Philippines
residential dynamics
Challenges
Cellular-automata
Regions
City
Land use land cover change
Simulation and modeling
Micro-scale simulation