Land Use Change Modelling in Developing Countries: Issues and Prospects

The growth of world population has been of serious concern in the last few decades. Of particular worry is how earth’s resources will match the concentration of human populations especially in developing countries. Associated with these are issues of urbanization, global warming and climate change which are also expected to have more impacts on poor peoples and places in developing countries. Responding to these issues has been problematic as we do not know expertly what will be the future scenarios especially in developing countries. It will be interesting to know the future trajectories of population growth, urbanization, urban land change (land use and land cover), and the socioeconomic conditions of developing countries. To this end various models have been evolved overtime for urban land use change forecasting but with more application in developed countries. How do we then make these urban change models more applicable to solving practical issues especially in developing countries? It is pertinent therefore to examine the current knowledge about these models; and to assess their usefulness, challenges and prospects in developing countries. It is against this backdrop that this paper by using extensive literature review examines urban land use change and modeling in developing countries. The historical developments of models was examined with the view to describing, classifying and characterizing the existing models, identifying the limitations to their adoption by decision makers, and suggesting ways to strengthen their relevance and applicability in developing countries. It concludes that models should be designed to clearly communicate their outputs to the practical users/policy decision makers. Besides, it suggests that since it may be difficult to calibrate models to have standard measurements or procedures, each region such as the developing countries should be treated in the context of its uniqueness with respect to urban dynamics, ecology and metabolism.