ABSTRACT A majority of research on Spatial Multicriteria Analysis (SMCA) has been
spatially implicit. Typically, SMCA uses conventional (aspatial) multicriteria methods for …

Eighty percent of big data are associated with spatial information, and thus are Big Spatial
Data (BSD). BSD provides new and great opportunities to rework problems in urban and …

Understanding the spatial scale sensitivity of cellular automata is crucial for improving the
accuracy of land use change simulation. We propose a framework based on a response …

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 …

Designing, implementing, and applying agent-based models (ABMs) requires a structured
approach, part of which is a comprehensive analysis of the output to input variability in the …

Land-use change is a typical geographic evolutionary process characterized by spatial
heterogeneity. As such, the driving factors, conversion rules, and rate of change vary for …

Although the neighborhood of the cellular automata (CA) model has been studied in detail,
there is a contradiction in the selection of the neighborhood size that has not been revealed …

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 …

Cellular automata (CA) are bottom-up models that have been widely applied to simulate
urban growth and project future urban scenarios. Conventional CA models commonly use a …

China has implemented a strict policy of cropland balance to reduce the impacts of built-up
land expansion on food production. However, this policy only alleviates the quantitative loss …