Sustainability and livability in transportation, as the concepts referring to the capability to maintain the well being of transportation systems, have been widely accepted as the critical principles to quality of life and health of communities. Different from the traditional objectives that look at the short-term effects of planning and operation decisions, sustainability focuses on the productiveness and efficiency of transportation systems over time, and pay special attention on the linkages of transportation to economic competitiveness, social development and environmental protection. As the recognition of this critical role, the recent years have witnessed increasing efforts in developing guidelines and principles to incorporate sustainability and livability objectives into transportation decision making. Despite these efforts, it is often found challenging to apply them to transportation practices due to the lack of appropriate assessment tools for transforming these abstract concepts to quantitative metrics. In this context, this study is intended to develop a GIS-based performance measurement system to evaluate the effectiveness of transportation developments in meeting sustainability and livability goals. This system will take advantage of remote sensing technologies and transportation information systems, and integrate land use, transportation and socio-economic data to form an input database. Based on it, a comprehensive list of sustainability and livability performance measures will be suggested for different types of applications. The database, the data analysis modules and the resulting performance measures will be integrated to form a GIS-based prototype performance measurement system for New York State to monitor the health of transportation systems over space and time.

The project team is uniquely qualified to conduct this study because it has all the expertise, management capabilities, critical skill set, and relevant project experience to meet and exceed the expectations of the UTRC Project Panel. The team will be led by Dr. Qian Wang who has extensive experience in performance measurement, land use modeling and travel demand forecasting. She will be responsible for the development of the GIS-based system and the team management. Dr. Le Wang, an expert on advanced remote sensing technologies and GIS, has extensive experience with remote sensing, data mining and forecasting of land use and cover changes in urban areas. Dr. Le Wang will therefore co-lead the tasks related to the remote sensing data processing and the development of the assessment database. The team will be rounded out by two highly motivated graduate students.