Abstract
Land development is a critical task for municipalities and local governments. It demands a carefully crafted plan that takes factors of various aspects into considerations, including economical, financial, environmental, and regulatory. The Cellular Automaton (CA) model and several variations have been proposed and utilized to facilitate urban and regional land development, but elements in the models that help to find patterns in land development history to guide future planning are still lacking. In this paper, we propose an extended CA model (ECADM) to address this problem. The new model is multi-faceted extension of the CA model to include more attributes and transition rules so that data mining techniques can be applied to find relationships among various components in land development.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
