Land use change (LUC) has gained attention as a core topic of global ecological
environment change research. The cellular automata (CA) model affects the global layout …

Urbanization processes have accelerated over recent decades, prompting efforts to model
land use change (LUC) patterns for decision support and urban planning. Cellular automata …

Land use change (LUC) exhibits obvious spatio-temporal dependency. Previous cellular
automata (CA)-based methods usually treated the LUC dynamics as Markov processes and …

Vector-based cellular automata (VCA) models have been applied in land use change
simulations at fine scales. However, the neighborhood effects of the driving factors are rarely …

Accurate land-use/-cover change (LUCC) simulation is of great significance to issues closely
related to regional planning and policy-making. Many models have been committed to …

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of
landscape types. Analyzing and simulating spatio-temporal dynamic features of urban …

The land use and land cover change (LUCC) process is crucial for climate and
environmental change studies. Cellular automata (CA) models based on machine learning …

Urban cellular automata (CA) models are broadly used in quantitative analyses and
predictions of urban land-use dynamics. However, most urban CA developed with …

Cellular automata (CA) models are in growing use for land-use change simulation and
future scenario prediction. It is necessary to conduct model assessment that reports the …

Rapid urban expansion has seriously threatened ecological security and the natural
environment on a global scale, thus, the simulation of dynamic urban expansion is a hot …