UrbanVCA is a GeoAI-based software for the simulation and prediction of urban development and land-use change process by using vector-based cellular automata. UrbanVCA supports the simulation and prediction of both land use interchange and urban land use expansion processes within the city.
UrbanVCA has been well applied in the fields of land-parcel-based urban land-use change process analysis, urban planning and urban landscape optimization. The vector-based CA model is difficult to implement due to the high technical difficulty. Therefore, we have designed and developed the UrbanVCA system can be easily used by researchers and urban planners.
Besides, UrbanVCA provides new tools for the display, roaming, and input/output of spatial data. UrbanVCA also supports multi-rule mining models with both external import probabilities (e.g. by using deep learning), and multi-spatial variable processing.
Notably, we will also provide a brand-new tool VecLI for calculating and analyzing landscape indices supporting vector-based spatial data.