Cluster development is the topic of much interest and debate for many stakeholders in the Greater Williamsburg Area. However, no specific regulation to implement cluster as a growth control strategy has been enforced. The cluster approach to rural housing focuses on developing less sensitive areas
Cluster development is the topic of much interest and debate for many stakeholders in the Greater Williamsburg Area. However, no specific regulation to implement cluster as a growth control strategy has been enforced. The cluster approach to rural housing focuses on developing less sensitive areas, while preserving farmland and other ecologically or visually valuable landscape features. This design principle suggests concentrating the density of a residential development on one portion of a site, complemented by reduced density and greater open space elsewhere.
We hypothesize that cluster housing is an effective strategy for development outside the Primary Service Area (PSA) in the Greater Williamsburg Area. To test our hypothesis, we developed and researched four objective questions. First, we analyzed whether cluster development was the most efficient way to control growth outside the Primary Service Area (PSA). Second, we reviewed different case studies to determine the positive and negative aspects of cluster housing and if rural cluster development should be supported. Third, understanding that the existence of open areas does not automatically ensure environmental preservation, we evaluated the most appropriate form and function of open space. Finally, we studied how to promote and ensure long-term open space preservation through policy enforcement.
As a follow-up to the policy analysis on cluster development, a water quality study was conducted in order to determine the effects of housing density with relation to conductivity levels. We sampled water from various BMP's to test the hypothesis that higher housing density will have greater negative effects on water quality. We tested BMP's adjacent to an even number of small, medium, and large lot sizes on two separate occasions. The water samples were analyzed based on conductivity levels with relation to lot size. Lot size was determined by using James City County's GIS information, and averaging the six most immediate lots to the sample site for each BMP. Preliminary result