Abstract:
More than 900 million people or one third of world’s urban population live in either
slum or squatter settlements. In the past decades, international, national and local
development agencies have taken several policy actions to address this challenge.
Despite these policy efforts, slum‐free cities remain a distant goal for many
developing countries. It is thus important to investigate the empirical questions
related to slum formation for informed policymaking: (i) how do slums form and
expand? (ii) where and when are they formed? and (iii) what types of structural
changes and/or policy interventions could improve housing conditions for urban
poor? This dissertation integrates Discrete Event Simulation (DES), Agent‐Based
Modeling (ABM) and Geographic Information Systems (GIS) into a single simulation
framework, named Slumulation, to explore slum formation dynamics. Slumulation is
designed to serve as a decision support tool that could be useful for urban planners
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and policymakers to experiment with new policy ideas ex‐ante in a simulated
environment with minimal data requirement. The core of this framework is a linked
dynamic model operating at both micro and macro geographical and demographic
scales. Slumulation explores the collective effect of many interacting inhabitants of
slums as well as non‐slums and how their interactions with the spatial environment
of the city generate emergent structure of slums at the macro scale. Slumulation is
tested with a case study of Ahmedabad, a sixth largest city of India with 41% of its
population living in slums.
