Decision support system for evidence-based precautionary ecological planning

While using precedent knowledge is critical especially for ecological planning to minimize permanent adverse effect on the natural environment, there have been only few cases that apply case-based design or decision support system to ecological designs. A possible reason might be because the design context varies dramatically for different sites with diverse variables to consider. Despite the difficulties, ecological wisdom - a relatively newly suggested ecological planning and design strategy - suggests using evidence-based precedents for new ecological designs to avoid ecologically harmful designs. For the past 5 years, there has been ongoing research on ecological wisdom by notable scholars; however, there remains a gap between the concept and its applicability as a planning or design methodology even though one of the goals of ecological wisdom is to be made practical. In this research, we propose a computational framework for the implementation of evidence-based Precautionary Ecological Planning Assistant and apply to a design case. To accomplish this goal, we found design patterns from vernacular garden designs in relation to environmental factors. By identifying statistically significant ecological design patterns, we generated a list of rules that were then incorporated into a decision support system alerting the users that the performed space planning strategy has never been observed before in previous ecological designs. From this research process, we were able to confirm that the proposed computational framework supports ecological design process to be more data-driven and precautionary providing second thoughts to planners when planning for unconfirmed ecological design.

Automated summary

The use of case-based design or decision support systems in ecological designs is limited due to the significant variations in design contexts and variables. Ecological wisdom suggests using evidence-based precedents to avoid ecologically harmful designs, but there is a gap between the concept and its practicality. This research proposes a computational framework for a Precautionary Ecological Planning Assistant, which incorporates design patterns and rules derived from vernacular garden designs to provide data-driven and precautionary support for ecological designs.