SunSpot: A Spatial Decision Support Web-Application for Exploring Urban Solar Energy Potential

Abstract

The growing necessity for meaningful climate change response has encouraged the development of global warming mitigation and adaptation initiatives. Urban solar energy generation is one opportunity that has been investigated by numerous cities through various solar potential Web-applications. However, as solar feasibility can vary considerably across a small geographic area due to variations in local topography and feature shading, there is no one-size-fits-all solution to be implemented.

This thesis investigates how a Web-based spatial decision support system (SDSS) can enable non-experts to explore urban solar feasibility and, to a lesser extent, issues related to urban heat. First, a conceptual framework is developed that investigates the linkages between SDSS, Web technologies, public participation, volunteered geographic information, and existing green energy initiatives. This framework identifies the relevance between these fields of study as well as a number of opportunities for improving on past work and taking advantage of new technical capabilities. Second, in order to test the opportunities identified, SunSpot was developed. This Web-SDSS investigates rooftop solar feasibility as well as land cover and surface temperature dynamics relating to the urban heat-island effect in Toronto, Ontario, Canada. A number of solar resource datasets were developed in order to facilitate the decision making capabilities of SunSpot. This was done using a combination of different topographical data sources, atmospheric data, and a raster-based irradiance model called Solar Analyst. Third, a number of in-person workshops were conducted to obtain feedback on SunSpot’s usability and ability for users to understand the visual layers and results. Finally, this feedback was analyzed to identify the successes and challenges of SunSpot’s capabilities and design. This revealed a number of recommendations for further development of SunSpot, as well as opportunities for future research relating to the development of local scale solar resource data and the development of similar Web-SDSS applications.