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

This paper presents an improved methodology for analyzing slum dynamics in Developing Countries using Geographic Information Systems (GIS) and Cellular Automata (CA). It examines factors contributing to informal settlements and assesses past and current slum policies, highlighting their failures to contain slum expansion. The paper introduces an Informal Settlement Growth Model (ISGM) that integrates GIS with CA to simulate, predict, and visualize slum growth, applied to Yaoundé, Cameroon with up to 73% accuracy. The model incorporates physical, socio-cultural, and economic factors, offering a practical framework for slum reduction and enhancing urban planning decision-making processes.

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Quick Facts
Report location: source
Language: English
Publisher:

University Of Melbourne

Authors: Phd, Remy Sietchiping
Geographic focus: Developing Countries, Yaoundé Cameroon, Global

Methods

The research method involves integrating Geographic Information Systems (GIS) and Cellular Automata (CA) to create the Informal Settlement Growth Model (ISGM). This model simulates and predicts the growth of informal settlements by incorporating various physical, socio-cultural, and economic factors. The methodology includes examining existing slum policies, identifying key factors contributing to slum growth, and applying the ISGM to Yaoundé, Cameroon. The model's accuracy is evaluated, and its outputs are used for dynamic visualization of urban dynamics.

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Key Insights

The research introduces a methodology integrating GIS and CA to model slum dynamics, providing a detailed examination of factors leading to informal settlements and the inefficacy of existing slum policies. It proposes the ISGM, which simulates and predicts the growth of informal settlements with high accuracy, using the example of Yaoundé, Cameroon. The model considers proximity to roads, rivers, markets, and cultural groups, and is evaluated for sensitivity, reliability, validity, and usability. The ISGM's dynamic visualization capabilities are highlighted as critical for appraising past, present, and future slum locations, potentially informing urban planning and policy-making in developing countries.

(Generated with the help of GPT-4)

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Last modified: 2024/06/17 15:49 by elizabethherfel