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Modeling and prediction of expected informal growth in the Greater Cairo Region, Egypt

Author

Listed:
  • Ibrahim Mohamed Badwi

    (Beni-Suef University, Egypt)

  • Mohamed M El_Barmelgy
  • Ahmed Salah El_Din Ouf

Abstract

Informal settlement growth is a vital challenge for developing countries, which requires monitoring and assessment by urban planners and city managers. Rural migration to urban areas leads to the unplanned expansion that grows within and beyond the city’s official boundaries. Although informal housing (IH) is growing fast, very little attention is oriented toward exploring tools and procedures for predicting its future expansion. Many studies have shown that informal housing is widespread and represents one of the most dominant features of urbanization in Egypt. Modern simulation and modeling technologies provide new methodologies to explore the complexity of urban growth. As a result, many planning models were developed and successfully used to simulate the spread of planned settlements in developed nations. However, the implementation of these models rarely achieves realistic simulation in the case of unplanned growth due to the developer’s field of study and the available resources. The main objective is to simulate the expected informal housing by modeling its causative land use factors in the Greater Cairo Region. This paper develops a predictive model that anticipates the spatial distribution of unplanned growth and where informal housing is likely to occur over a period based on known growth factors. The proposed Informal Housing Growth Model derives its principles from cellular automata and geographic information system technologies. This model uses a multi-criteria concept, including parameters and conditions related to informal growth, and can be adapted to other growth factors.

Suggested Citation

  • Ibrahim Mohamed Badwi & Mohamed M El_Barmelgy & Ahmed Salah El_Din Ouf, 2022. "Modeling and prediction of expected informal growth in the Greater Cairo Region, Egypt," Environment and Planning B, , vol. 49(2), pages 427-446, February.
  • Handle: RePEc:sae:envirb:v:49:y:2022:i:2:p:427-446
    DOI: 10.1177/23998083211002207
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