Spatio-Temporal analysis of urban growth and its future trends of District Peshawar using CA Markov and SLEUTH Model

Abstract

Land use change and urban expansion are spatially variable and dynamic processes caused by human activities, which causes a significant impact on the urban landscape because of the conversion of natural environment to build environment. In developed countries, strict implementation of zoning regulations results in planned urban growth, however, it is the opposite in the developing countries which expand haphazardly. Pakistan being a developing country, also faces rapid urbanization related issues in many urban areas. District Peshawar is one of these where the urban growth rate is about 14%. It is felt important to track urban growth to address the problems that may arise in future. This study focused on mapping of the Spatiotemporal urban expansion from 1990 to 2021 using Landsat 5 and 8 data. The results show that that the urban area of district Peshawar increased from 50.5 sq km to 260 sq km i.e., about 20.23% of the total district’s area. The urban area increases at the cost of vegetative and open land. The further comparison and analysis revealed that out of 260 sq km 147 sq km increase was within the allowable zones while 113sq km was in zones restricted settlements. The research also focused on the future prediction of urban growth trends using CA Markov Chain Model and SLEUTH (Slope, Land use, Urban, Excluded area/land, Transportation, Hill shade) for year 2039. Both models were calibrated and validated using urban extents mapped from 2000 and 2010 remotely sensed data. Simulated urban growth and its comparison with image based urban revealed that CA-MC model over predicted the urban area by 20.50 sq km while the Sleuth model over predicted by about 7.3 sq km area. The performance of Sleuth model was the better in terms of estimating the urban growth. The future simulation using CA Markov and the Sleuth models show that in 2039, the urban area will be about 418 and 476 sq km, respectively. These findings can help the relevant authorities in better monitoring management and formulating policies for the future sustainable urban expansion.