Simulating and predicting of urban expansion in Al Najaf city utilizing a Ca-Markov model

Abstract

Urban expansion is one of the notable issues that have effectively contributed to disrupt the ecosystem in recent decades. This research focused on the future prediction of urban expansion in the city of Najaf using the CA-Markov model. Satellite imagery captured by Landsat-5 (2010), Landsat-8 (2017) and Sentinel-2 (2020) were used to predict the urbanization of the study area for the years (2025, 2030 and 2035). The land use was classified into urban areas, agricultural areas and bare soil and water using the maximum likelihood classifier for the years (2010, 2017, and 2020). The accuracy of the land use classes was evaluated based on the overall accuracy index and the Kappa index. The overall accuracy was 91%, 94%, and 87% while the Kappa coefficients were around 88%, 91% and 83% for the land use maps for the years 2010, 2017 and 2020 respectively. A Markov chain model was applied to compute transition likelihood matrices for land use classes built on the CA-Markov model, and in light of this, a projected land use map for 2020 was constructed, and its accuracy was evaluated based on actual land use statistics for 2020 using Kapp indicators which all showed high accuracy. Then, the CA-Markov model was used to predict of urban expansion for the years 2025, 2030 and 2035 in.Najaf Governorate. The study results presented that the urban area of Najaf increased from 88.19 Km2 in 2010 to 213.70 Km2 in 2020. Urban areas for study region are expected to increase to 267.97 Km2 by 2025, 290.88 Km2 by 2030 and 302.90 Km2 by 2035. The results of the study indicate the necessity of adopting new methodologies for land use policy and improving urban planning and sustainability in Najaf governorate.