Abstract:
Africa’s urban population growth has been especially rapid, averaging about 5%
per year over the past two decades. As a result, many urban areas have experienced dramatic
growth that is seriously outstripping the capacity of most cities to provide adequate services for
their residents. Although population growth and urbanization rates in Africa have slowed
recently due to a number of factors including HIV/AIDS, urban growth is still expected to double
by 2030, leading to dramatic sprawl with serious environmental and social consequences. Using
Nairobi as an example of a rapidly urbanizing African city, we studied the dynamics of land use
and land cover change using satellite data and addressed the need for models and urban management tools that can guide sustainable urban planning policies. Cellular Automata, which integrate biophysical factors with dynamic spatial modeling, are used in this study. The model was
calibrated and tested using time series of urbanized areas derived from land use/cover maps,
produced from remotely sensed imagery, with future urban growth projected to 2030. Model
assessment results showed high levels of accuracy, indicating that simulation findings were realistic, thereby confirming the effectiveness of the model. Results further showed that the model is
a useful and effective tool to foresee the spatial consequences of planning policies in the context
of many African cities. The forecast for Nairobi showed unsustainable sprawl. [Key words:
urban growth, Cellular Automata, African cities, Nairobi.]
