Abstract
Land-use modelling and spatial scenarios have gained attention as a means to meet the challenge of reducing uncertainty in spatial planning and decision making. Many of the recent modelling efforts incorporate cellular automata to accomplish spatially explicit land-use-change modelling. Spatial interaction between neighbouring land uses is an important component in urban cellular automata. Nevertheless, this component is often calibrated through trial-and-error estimation. The aim of this project has been to develop an empirically derived landscape metric supporting cellular-automata-based land-use modelling. Through access to very detailed urban land-use data it has been possible to derive neighbourhood rules empirically, and test their sensitivity to the land-use classification applied, the regional variability of the rules, and their time variance. The developed methodology can be implemented easily and thus used as a much needed replacement for the various trial-and-error approaches that are often applied in land-use modelling.
Sign-in/Register to access full text options 
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.
