This study highlights the importance of integrated urban-rural land-use planning system in a rapidly developing region, Falavarjan Township, Iran. It also analyses the effect of various urban growth policies on land surface temperature (LST). In doing so, this paper combines several modeling methods including LST map generation algorithm, urbanization suitability mapping, and scenario-based analysis of future circumstances through cellular automata (CA)-Markov modeling and regression analyses. The potential impact of various urban growth policies including historical growth, extensive growth and rural development on LST values of interior urban environments are quantified and compared. These scenarios are introduced to the CA-Markov model by generating several urbanization suitability layers insisting on various urban-rural planning perspectives. In addition, linear, quadratic and logarithmic regression models were also developed to measure the relationship between LST values and urban patches areas. The results demonstrated that logarithmic regression model yields stronger relationships (R2 = 0.35, p < 0.01) such that the model is capable of predicting LST values over temporal scales. By coupling the results derived from CA-Markov model and temporal estimation of LST values, an integrated urban-rural land-use planning system is developed. The findings of this study can effectively assist land managers in central Iran to adopt a sustainable planning strategy in a highly developing region.
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