Urbanisation is a key aspect of land use change (LUC), and accurately modelling of urban
LUC is crucial for sustainable development. Cellular automata (CA) are widely used in LUC …

In this article, the principles of the gray model and BP neural network model are analyzed,
and the characteristics of land‐use change and spatial and temporal distribution are studied …

The rise of Geographic Information Systems (GIS) technologies has been producing
powerful tools for spatial data processing, management, analysis, modeling, and …

Land use modelling is essential to understanding future land use and change dynamics.
Analyses of land use and change using Cellular Automata (CA) have been frequent in the …

Urbanization and climate change are critical challenges in the 21st century. Flooding by
extreme weather events and human activities can lead to catastrophic impacts in fast …

To examine the effects of historical land-use change and static land-use state on the
modeling, we established three cellular automata (CA) models using the spatial …

Urban growth has accelerated significantly in recent decades, categorized into two spatial
patterns: adjacent and outlying growth. Traditional Cellular Automata (CA)-based models …

While many published studies have explored the impact of spatial heterogeneity on land-
use change, few have focused on regional differences in land-use transition rules caused by …

Effectively resolving environmental problems often involves not only technical solutions but
also examining and potentially reforming the political and institutional frameworks that …

Cellular automata (CA) have been prevalently used for the simulation of urban land change.
However, how to effectively learn the spatial-temporal dynamics of urban development from …