Modeling urban sprinkling with cellular automata

• Analysis of urban expansion in a sprinkling context through multi-density approach. The mismatch between and demographic decline is common phenomenon European Western areas. CA MLR to analyze the spatio-temporal relationships built up causative factors. forecast new involves classes low settlement density. This paper presents spatiotemporal analysis simulate project with coupled cellular automata (CA) multinomial logistic regression (MLR) model. Our case study, Basilicata region, south Italy, characterized by - literally "a small amount territory distributed scattered particles". region witnessing decoupled growth trend expansion. We applied approach based on for modeling simulation. From three regional building datasets (1989, 1998 2013) density maps were created used calibrate validate model future Built-up factors identified an 19 articles that compared discussed according their main features (methods, studies, drivers, urbanization dynamics growth). transition probability first period (1989–1998) was calibrated built-up multi-objective genetic algorithm (MOGA) neighborhood effects. 2013 pattern which actual map (validation). then our 2030. results 2030 show largest variations class 1 (low patches) correspond sprinkling.