Analysis of the spatiotemporal dynamics of urban sprawl using Shannon entropy and landscape metrics, Case study Bishoftu City, Oromia, Ethiopia

Abstract

Urban sprawl is considered as a particular kind of urban growth which comes up with a lot of negative effects. A complex of driving force such as social economic political physical and factor and their interaction cause urban sprawl. Bishoftu city is undergoing rapid changes in the last 3 decades especially in the last decade and needs assessing of urban sprawl and its causative factor. So, this study focuses on the assessing the spatiotemporal dynamic of urban sprawl in Bishoftu City from 1990 to 2022 using Shannon Entropy and landscape metrics. Landsat Satellite data was applied in this research ((TM, ETM+, and OLI/TIRS) for land use/land cover classification and accuracy assessment were applied in four study periods (1990, 2000, 2010 and 2022). Elevation data, major road data, water body data, city center data, health center and educational institute data were used to identify the driving forces of urban Sprawl. The study area is classified in to five classes; water body, bare land, built-up green area, and agricultural land covers. To identify the expansion of built-up areas within the study region, the classified land use/cover data was reclassified into built-up and non-built-up categories. The result showed that an increase in built-up area 1872.81ha, 2479.77ha, 3440.97ha and 4783.14ha in 1990, 2000, 2010 and 2022 respectively this indicate the sprawl pattern of the study area has increased from 1990 to 2022. After reclassified the image multi ring buffer analysis was made at an interval of 3km from the center of city for built-up area. This is used to determine the extent of urban sprawl using the Shannon entropy. The calculated value of Shannon entropy was 0.520, 0.758, 0.861and 0.945for 1990, 2000, 2010 and 2022 respectively. Approach the degree of dispersion or concentration of built up area’s development or sprawl was described in this study. FRAG STAS was used to quantify the landscape metrics of Bishoftu city finally; a logistic regression model in IBM SPSS Statistics 25 software was used to identify the driving forces of urban Sprawl from six selected variables. The model identified major roads as a major driver in all years and city centers as a second driver in the period 1990-2010. In the period 2010-2022, educational institutions and health centers emerged as the second-largest drivers.