Prospective Slum Policies: Conceptualization and Implementation of a Proposed Informal Settlement Growth Model

This paper provides an improved methodology for analyzing the dynamics of slums in Developing Countries (DC). In particular, it demonstrates how Geographic Information Systems (GIS) and Cellular Automata (CA) can be integrated to model, simulate, predict and dynamically visualize the growth of slums, and thus will improve future planning practices in DC. The paper first examines factors that contribute to the existence and spread of informal settlements (IS). It then assesses past and current slum policies to conclude that they are failing to contain the rapid expansion of slums. It is argued that weaknesses of these policies include on the one hand, planning instruments that are often rigid, inappropriate and outdated, inherited from former colonial powers. On the other hand, urban planners often overlook future spatial extension of slum areas. This paper also explains how factors underpinning emergence and growth of slums are accommodated within an Informal Settlement Growth Model (ISGM) that loosely couples a GIS with a CA model. In this way it is demonstrated how a VISUAL BASIC macro can be linked with GIS to design a flexible and generic modeling environment. Here, the ISGM is applied to simulate and predict the growth of IS in Yaoundé, Cameroon with slum allocation accuracy of up to 73%. In doing so, the model tests various mechanisms that motivate slums’ growth, such as proximity to roads, rivers, market places, existing informal settlements, cultural and ethnic groups. By integrating physical, socio-cultural and economic factors that underpin slums growth, the ISGM provides a much stronger practical framework to achieve slum reduction. Finally, the paper demonstrates how such spatio-temporal simulation and visualization of urban dynamics are critical for the appraisal of the past, present and probable future location of slums. Moreover, it is argued that dynamic visualization via movies can provide new insight into the emergence and growth of IS. The ISGM is also evaluated in terms of sensitivity, reliability, validity and usability, for which it generally scores highly. The paper concludes that the proposed model can potentially enhance decision-making processes in urban planning, informed prospective slum policies and help predict the likelihood of slum emergence and growth, which will eventually improve the quality of life within developing countries’ urban areas.