Reliable forecasts on the impacts of global change on the land surface are vital to inform the
actions of policy and decision makers to mitigate consequences and secure livelihoods …

Urban sprawl is a typical geographic dynamic process with spatial heterogeneity and
nonlinearity. However, current studies usually focus on only one of them to extract urban …

The present study represents the novel methodology for quantitative evaluation of the
coordinated relationships (CR) between BRTS and land use under transit-oriented …

Cellular automata (CA) model has powerful spatial analysis capabilities and easy coupling
with other models. However, the coupling based on single model and CA model is difficult to …

This paper presents a spatial autoregressive (SAR) method-based cellular automata
(termed SAR-CA) model to simulate coastal land use change, by incorporating spatial …

The world's coastal regions are experiencing rapid urbanization coupled with increased risk
of ecological damage and storm surge related to global climate and sea level rising. This …

The cellular automata (CA) model is the predominant method for predicting land use and
land cover (LULC) changes. The accuracy of this model critically depends on well-defined …

Dynamic urban growth is affected by various driving factors which are important for building
cellular automata (CA) models. Two categories of urban‐growth drivers (ie, proximity and …

The neighborhood effect, a pivotal element within the realm of Geographic Cellular
Automata (GCA) modeling, has garnered significant attention in research. However, no …

The aim of the paper is to analyze and compare the form and land use structure of Euro-
Mediterranean cities by estimating spatial metrics and to present a way of using these …