Focus Filtering Unsuitable Locations About the Authors Andrea Chaves currently works as a business technology analyst at Deloitte Consulting LLP in Denver, Colorado. She earned a bachelor's degree in industrial engineering, a master's degree in management with emphasis in finance, and a master's in industrial engineering, all from the University of Arizona, Tucson. In 2008, she was a recipient of the Wayne Wymore Award for excellence in systems and industrial engineering and was named outstanding senior for her graduating class. During her graduate studies at the University of Arizona, she worked as a teaching and research assistant in areas such as production planning, forecasting, and optimization; probability and statistics; and systems engineering. In her spare time, she enjoys triathlons. A. Terry Bahill is a professor of systems engineering at the University of Arizona, Tucson. He received his doctorate in electrical engineering and computer science from the University of California, Berkeley. Bahill has worked with BAE Systems; Hughes Missile Systems; Sandia Laboratories in Albuquerque, New Mexico; Lockheed Martin Tactical Defense Systems; Boeing Information, Space and Defense Systems; the Idaho National Engineering and Environmental Laboratory; and Raytheon Missile Systems. For these companies, he presented seminars on systems engineering, worked on system development teams, and helped them describe their systems engineering process. He is a fellow of the Institute of Electrical and Electronics Engineers (IEEE), of Raytheon, and of the International Council on Systems Engineering (INCOSE) and the Founding Chair Emeritus of the INCOSE Fellows Selection Committee. He holds a U.S. patent for the Bat Chooser, a system that computes the ideal bat weight for individual baseball and softball batters. He received the Sandia National Laboratories Gold President's Quality Award. In this digital elevation model (DEM) derived from LiDAR data, the university's campus is the brightest area in the image and has the highest buildings. Lowerelevation areas are shown in black. A binary ground raster was generated to identify locations on building rooftops. Any cell with an elevation greater than or equal to the bare earth elevation plus five feet was given a value of 1 and shown in green. All other cells were assigned 0 and shown in purple. To find sites that were south facing, a raster was generated from the georeferenced DEM. Cells with south, southeast, southwest, or flat aspects were assigned a value of 1 and shown in blue. To find areas with a slope of 35 degrees or less, all cells with a slope less than or equal to 35 degrees were assigned a value of 1 and shown in blue. All binary rasters were combined into a final raster that assigns a value of 1 to the cells that meet all the requirements and 0 for those that do not to find all feasible locations. In the final output raster, suitable areas are shown in green. The output generated using the five masks was used as input for the Raster To polygon tool that generated suitability polygons. These polygons were symbolized based on the theoretical number of solar panels that could fit in each polygon. www.esri.com ArcUser Fall 2010 27