Modeling and predicting urban growth of Nairobi City using cellular automata with geographical information systems

Abstract

Urban population is increasing in Africa's major cities at a much faster rate than in the rest of the world, leading to dramatic sprawl with associated undesirable environmental and social consequences. Using Nairobi as an example of a major African city, we studied urban growth and addressed the need for urban management tools that can provide perspective scenarios of urban growth. This paper describes land use/ cover changes and urban growth modeling for predicting the urban growth of Nairobi city using Cellular Automata (CA), which integrates biophysical factors with dynamic spatial modeling. The model was calibrated and tested using time series of urbanized areas derived from remote sensing imageries, and future growth projected out to 2030. The results show that Nairobi city is experiencing fast spatial expansion with simulated urban land taking up most of the available land within the city and the immediate surroundings. The predicated rapid growth of urban areas has led to an unsustainable sprawled urban growth that has caused major changes to the landscape and loss of vital resource lands. The results show the capability of urban growth modeling in addressing regional planning issues.