Land use patterns in the built environment have emerged from a combination of basic principles, timing, and practicality. Basic location criteria, such as access and defense, drove historical land use decisions for centuries. In addition, pioneers that opened new areas to development often set land use patterns by virtue of being the first to arrive. Land use decisions have also been heavily influenced by practical needs, such as access to food, water, transportation, and trade routes. These influences, over time, have translated into the fabric of our communities that is visible today. These patterns, however, bear little influence based on land use suitability or resource efficiency. What if a new paradigm shifted the focus on land use patterns away from historical growth trends that are based on a combination of necessity and least resistance toward a pattern based on the conservation of natural resources?

The research focuses on the creation of a technique for the development of future land use scenarios based on land use suitability and resource efficiency indicators, such as energy and water use, fuel consumption, and greenhouse gas emissions. The methodology developed by the research expands upon the principles of GeoDesign by using land use suitability as the basis to compare and contrast scenarios of future development and the creation of a three dimensional visualization technique to ease the transfer of information from experts to decision-makers, stakeholders, and the public. This analysis utilizes the Principals of Sustainable Communities (PSC) criteria as the basis for identifying resource efficiency metrics and incorporates alternatives for future land use and employment scenarios based on proximal, network, economic, suitability, and conflict analyses. Conclusions drawn from the research can be used to influence decisions regarding infrastructure location, capacity, design, and cost by policy-makers and the development industry. Recommendations for future development of this model include incorporation of the 3-D capabilities developed by the research onto ESRI CityEngineRTM and virtual reality.