Modeling urban growth in Kigali city Rwanda

The rapid demographic and uncontrolled spatial transformation have overloaded the capability of most cities management in developing countries. The growth of cities, if governed and supported by well informed policies, decision makers and stakeholders can help to address these challenges. Having a good understanding of the key drivers of the city's growth has proven to be a key instrument to manage urban growth. The study explores the capability of Logistic Regression model to identify the main drivers of Kigali city growth and to predict the future pattern of the city in next 26 years. Three scenarios were built, i.e. urban growth model for expansion (normal growth) and two densification (zoning implication) i.e. strict and moderate scenarios. LRMs regression and probability maps for the three scenario models were evaluated by means of Kappa statistic, ROC value and the percentage of 2014 built-up land cover predicted. These scenarios allowed predicting the future pattern of the city in 2025 and 2040. The results indicated that new urban developments in Kigali city will tend to be close to the existing urban areas, further from the CBD and wetlands but on low slope sites. The results from the study can help city urban planners and decision makers to describe the future urban environment, leading to an improved understanding in the urban planning and management of the city.