Alternative energy sources are a necessity, as is the ability to analyze them. Photovoltaic (PV) potential is commonly studied over large areas, yet implementation is often desired at a local scale. To support research and tools developed to study PV potential in urban areas, this project analyzed remotely sensed data, specifically LiDAR (Light Detection and Ranging) and orthoimagery, to extract 3-dimensional building and vegetation features for use in existing modeling tools. LiDAR and orthoimagery will allow a more efficient and geo-referenced way for users to compute solar potential for individual or clusters of locations in their selected areas of interest. This project has tested different extraction tools and concepts, identifying those that can easily be incorporated into a Geographic Information System (GIS). Parameters of feature extraction were tailored to facilitate shading analysis and eliminate areas unsuitable for PV systems. Extraction of buildings and high vegetation, and creation of 3D models of usable areas were investigated. From this, a reliable workflow is being developed to serve as a tool for future use. The direction of this project is important to analysts desiring accurate, geo-referenced data for input into various models, but will specifically support the on-going research in inter-building shadowing effects for energy simulations and solar technology deployment.