Application of geospatial techniques and binary logistic regression model for analyzing driving factors of urban...

Understanding the drivers of urban growth and spatiotemporal land use change is important for rational land use and sustainable urban development. Based on the land use data, GIS data of explanatory variables, experts' knowledge and field observation, the study used a binary logistic regression model (BLRM) to analyze factors that drive rapid urban growth in Bahir Dar city, Ethiopia, using the LOGISTICREG module in IDRISI Selva software. Nine factors were used to reflect the influence of proximity and physical factors on urban growth from 1984 to 2019. This model helped in quantifying and identifying the factors of urban growth, which includes topography (slope, elevation and aspect) and accessibility (Dis. to the main road, Dis. to international airport, Dis. to CBD, Dis. to existing built-up area, Dis. to forest land and Dis. to water body). Furthermore, urban growth probability maps were created based on LRM results, revealing that the biggest urban growth would occur around existing built-up areas along the main roads and near Bahir Dar international airport. The Relative Operating Characteristic (ROC) values of 0.85, 0.90 and 0.93 and PCP values of 96.72 %, 98.46 % and 98.51 % indicate the urban growth probability maps are valid and BLRM had an ideal ability to predict urban growth. So, the study highlighted the relation between urban growth and its drivers in Bahir Dar, giving a decision making framework for better land use management and resource allocation.