Predicting Land Use/Land Cover Changes in the Lesser Zab River Catchment/Iraq through CA-Markov Synergy Model

Abstract

Land use/land cover is one of the utmost dynamic constituents of the atmosphere that has been altering abnormally from the time after the industrial revolution at different measures. A good understanding of the drive and strength of environments needs regular monitoring and quantifying for land use/land cover alterations. The current research targets to predict the prospect of land use/land cover (LU/LC) alterations; for the Lesser Zab catchment in the Northern part of Iraq, applying the synergy Cellular Automata-Markov simulation. The Maximum Likelihood method classified three sequential years of Landsat images (1999, 2010, and 2021). Then, three LU/LC images, with numerous class classifications, were created, and an alteration identification examination; was performed. With the categorized (1999–2010) and (2010–2021) LU/LC maps in the hybrid model, the corresponded LU/LC maps; for 2021 and 2041; were modelled, and the classified 2021 LU/LC maps; were considered to validate the model output 2021. In that order, agreement accuracy between the classified and the modelled images was Kno = 0.864, Klocation = 0.854, and Kstandard = 0.785. Prospect likelihoods validate that between 2021 and 2041, the urban area would rise by 78% (from 1118 to 5200 km2). However, bare lands/light, agricultural lands, water bodies, bare lands/dark, and forest lands would decrease by 3% (from 6983 to 6736 km2), 12% (from 7992 to 7036 km2), 15% (from 141.03 to 119.86 km2), 30% (from 7 to 4 km2), and 76% (from 3810 to 904 km2), correspondingly. This study’s conclusions are priceless for policymakers, urban managers, and ecological researchers.