Using LiDAR Data in ArcGIS to Characterize Rooftop Suitability for Photovoltaic Systems: A Proof of Concept for Louisville, KY
The identification of suitable areas within cities for photovoltaic (PV) systems is becoming increasingly important as society moves towards renewable energy sources. Creating tools to do this that are easy to use and widely applicable will be an important step in easing this transition. This study created a Geographic Information System (GIS) model in ESRI’s ArcGIS which aggregates two existing GIS models to produce an automated method for the identification of residential rooftops suitable to host productive PV systems in Louisville, KY. The model used LiDAR data to first create building footprints, then eliminate unsuitable areas within those building perimeters using four criterion. These elimination factors were: aspect, slope, area and sun exposure. Aspect was applied first, then slope and shading restrictions were included. Lastly, a minimum rooftop segment area was enforced. The resulting areas were further broken down into 4 levels of suitability, ranked from most to least preferable. The workflow was developed on a suburban land area first then applied to an urban, downtown location in Louisville, KY. The model found 30% of suburban residential rooftop areas suitable, but only registered about 10% suitability in the downtown region. When compared to aerial imagery, the majority of suitable rooftops appeared to have very simple geometry. More complex areas were classified as unsuitable, primarily due to having too many differing aspects in a small region, or a large number of small areas. The lower proportion of suitable rooftops seen in the downtown area (compared to suburban) is thought to be a result of increased shade cast by nearby, taller buildings. The findings, assumptions, strengths and weaknesses of this model are also explored in this report.