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 …

Cellular automata (CA) is a classical method for studying land use change. However,
homogeneous transformation rules have commonly been used to conduct simulations in the …

Spatial Simulation is a spatially explicit, bottom-up modelling approach that includes
individual-based models and cellular automata. While spatial heterogeneity and individual …

Modelling urban land use change is of profound concern to environmental scientists who
have found cellular automata models very attractive for simulating urban dynamics. The …

We develop a new geographical cellular automata (CA) modeling framework, named
UrbanCA, through reconstructing the essential CA structure and incorporating nonspatial …

The urban problems have clearly incorporated into the global sustainable development
agenda and the scientific urban expansion model has won credibility for urban research and …

Optimization of cellular automata (CA) using swarm intelligence is an effective approach to
establish optimal models for urban growth modeling. This study builds a new CA model (CA …

Cellular automata (CA) has proved to be effective and efficient in conducting urban
expansion simulation. The generation of cell transition rules is a crucial step for a CA model …

For urban growth modeling, assessment metrics derived from cell-by-cell comparisons are
mainly related to the size of the study area and the urban growth rate. Non-urban areas …

While many publications predict future urban scenarios, few have deliberated the impact of
issued urban planning on scenario prediction. We propose a planning-constrained model …