Urban regions worldwide revert to scenario-based simulations to understand and cope with
uncertain land-use changes and future land-use demands. Whereas scenarios account for a …

Urban land use/land cover (LULC) classification has long been a hotspot for remote sensing
applications. With high spatio-temporal resolution and multispectral, the recently launched …

Amidst the rapid urbanization process, substantial transformations have emerged within
ecosystem services, exerting profound ramifications on the sustainability of ecosystems …

Vector cellular automata (VCA) are effective models for cadastral-scale land use change
modeling, leveraging fine spatial granularity information from cadastral plot data. The …

In recent years, the delicate balance between economic development and ecological
environment protection in ecologically fragile arid areas has gradually become apparent …

Since urban growth results from frequent spatial interaction between urban units, adequate
representation of spatial interaction is important for urban growth modeling. Among urban …

Deep learning models have been extensively employed to simulate dynamic Land Use
Changes (LUC) at the regional level. However, existing studies were found to be limited by …

Modeling and predicting land use/cover change (LUCC) and identifying its drivers have
been a focus of research over the past few decades. In order to solve the problem of land …

Spatio-temporal modeling of parcel-level land development dynamics is essential to
maintain sustainable urban growth. Modeling parcel-level urban development controlling …

Open spaces (OSs) in urban areas play a vital role in providing space for habitat
conservation and recreation, improving the mental health of urbanites. OSs consist of …