Land use and land cover change simulation enhanced by asynchronous communicating cellular automata

Abstract

Land use and land cover change (LUCC) modeling is crucial to urban planning and policy making. A well-used and effective paradigm for LUCC is the ANN-CA model which employs an artificial neural network (ANN) to calculate a transition probability over each land cell from various driving factors, and then uses a cellular automaton (CA) to evolve all cells consecutively to update their land usage and coverage according to the estimated probability distribution. This paper focuses on the effect of delays or perturbations possibly taking place between land cells on the LUCC modeling. To this end, a new ANN-CA model is proposed which adopts an asynchronous communicating cellular automaton (ACCA), rather than the conventional synchronous CA. Especially, the ACCA allows every cell to communicate with its neighbors independently at random times via a specific protocol, which offers a natural way to include stochastic delays in exchanging the current land usages between cells. As a result, every change of a cell's land use in the ACCA may not affect its neighbors immediately, but is subject to delays that might play an important role in modeling the practical LUCC. Numerical analysis of the new model are carried out over three regions of Chongqing city, China with different scales: Yongchuan District, Sanjiao Town, and Huangguashan Village, and experimental results demonstrate that the proposed ANN-ACCA model can achieve a higher accuracy for LUCC simulation as compared to conventional ANN-CA models.