The Heat Energy Assessment Technologies (HEAT) project uses high-resolution airborne thermal imagery, GIS cadastral data, and Geographic Object-Based Image Analysis (GEOBIA) to allow the citizens of Calgary, Alberta, Canada to visualize the amount and location of waste heat leaving their houses, communities, and the city. This information is presented to them in an interactive and multi-scale Geoweb application with three energy efficiency feedback solutions: (i) HEAT Scores, (ii) Hot Spots, and (iii) Estimated Savings – that help residents reduce their greenhouse gas emissions and save their money. To ensure the accuracy of these measures, the correct emissivity of roof materials needs to be known. However, roof material information is not readily available in the Canadian public domain. To overcome this challenge, a new and unique Volunteered Geographic Information (VGI) system was developed using Google Street View and Google Satellite data that engages citizens to classify the roof materials of single dwelling residences in a simple and intuitive manner. Since data credibility, quality, and accuracy are major concerns when using VGI, a private Multiple Listing Services (MLS) dataset was used for cross-verification. Results show that from May-November 2013, 1,244 volunteers from 85 cities and 14 countries classified 1,815 roofs in the study area. Additional analysis reveals (i) a 72% match between the VGI and MLS data, and (ii) in the majority of cases, roofs with greater than, or equal to 5 contributions have the same material defined in both datasets. These results demonstrate that citizens are engaged in correctly classifying the roof materials of houses, and implementing changes to the HEAT VGI system based on feedback from volunteers can further improve data quality and increase participation. Furthermore, to the best of author’s knowledge, this is the first time that Google Street View has been used for classifying roof materials, or has been implemented in the domain of VGI. By building on the lessons learned and the success of this research, we suggest that similar VGI systems may be implemented to create new geo-information in support of urban energy efficiency.