Urban Expansion and Vegetation Cover Change in and Around Jimma Town Since 1990

Abstract

Urbanization is the renovation of rural society into an urban society as a result of socio-economic and political growth leading to foundation and expansion of urban agglomerations along with changing land use patterns. The main aims of this study was Investigating the extent of vegetation loss through urban expansion in and around Jimma Town over a 30 period of 6 years interval by using Geographic Information System (GIS) and Remote Sensing (RS) techniques. To achieve this objectives, Data was obtained from earth explorer (USGS) 6 years interval from1990 to 2020 of the study area. Downloaded image were extracted and each layer stacked together using the digital image-processing software ENVI 5.2. The Processed images were classified using supervised classification Algorithms into 5 hierarchical classes; Built-up area, Vegetation, Agricultural land, Grass land, and wetlands based on a modified classification scheme. Change analysis was also undertaken by applying post-classification change detection procedures. Accuracy of the image classification was assessed using error matrix, overall accuracy and kappa coefficient. The change analysis result revealed that the LULC have shown both positive and negative significant changes. Built-up were the top LULC that experienced positive change; whereas grass land, vegetation, agricultural land and wetlands have substantially declined. An important implication of the observed changes is that rapid urban expansion, compounded by poor urban planning is leading to enormous losses of key ecosystems such as wetlands and natural vegetation. The consequence of this rapid ecological degradation could potentially impact ecological functioning and environmental sustainability in and around Jimma city. Therefore, critical system thinking is required to address these complex problems in the study area and areas of rapid urbanization elsewhere in the country.

Keywords: Image classification, Land use/cover, Remote sensing, GIS, Change detection

DOI: 10.7176/JEES/11-16-02

Publication date:June 30^th 2021