Land use changes in developing countries generally
occur in the form of new building construction in the
peripheral areas of cities mostly for residential
purposes. This fast pace of urban development has
thrust to the fore a number of research initiatives that
make use of new applications for modeling such
phenomenon. In this study, urban expansion is
examined in Kaduna, Nigeria, using a hybrid model
that combines Cellular Automata (CA) techniques
and Markov chain analysis with logistic regression.
Land use change between 1990 and 2001 was
analyzed and the results showed huge conversion of
green areas and open lands to built-up areas.
Environmental variables dealing with urban
expansion were evaluated to determine their
influence on urban expansion and operationalized to
develop transition potential sub-models. A transition
potential map is then derived from the transition
potential sub-model which was employed to simulate
future urban growth. The model was subsequently
evaluated and validated using ROC statistics and the
results were found to be acceptable.