Modeling urban sprinkling with cellular automata

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

Automated summary

This paper proposes a spatiotemporal analysis method for simulating and predicting urban expansion using cellular automata (CA) and multinomial logistic regression (MLR) model. Through analyzing regional building datasets and identifying causative factors, the study reveals a decoupled growth pattern between demographic trend and urban expansion in the Basilicata region of Italy. The results show the largest variations in low density builtup patches, corresponding to urban sprinkling, in the forecasted urban expansion for 2030.