An analysis of LULC change detection using remotely sensed data; A Case study of Bauchi City

Abstract

Bauchi is one of the cities in the north eastern part of Nigeria that has witnessed tremendous expansion as a result of rapid urbanization. For the past decade, the city has been known to be relatively small both in size and population. But today, Bauchi is one of the fastest growing cities in northern Nigeria. Therefore, it is paramount to detect the nature and magnitude of these changes in order to determine its direction of future expansion. To achieve that, Remotely Sensed data from Landsat 7 ETM+ and Landsat 8 were utilized for the purpose of LULC change detection in Bauchi city. Landsat 7 image of 2003 and Landsat 8 image of 2013 were obtained for the purpose of the study. Three change detection algorithms were used to detect areas of change. They include supervised, unsupervised and post classification comparison. While the unsupervised classification was found to be less effective, the supervised classification produced good results with overall accuracies of 93.5% and 89.7% for the 2003 and 2013 respectively. Finally, "from-to" change was obtained using the post classification comparism.