Customer Stories

TRANSFORMING THE WAY THE WORLD WORKS These growth opportunities have brought challenges to service providers. With hard costs at a negligible rate, solar companies and financiers face fierce competition to attract and acquire customers–the so-called "soft costs" of turning the solar curious into solar consumers. Because lead generation and customer acquisition costs can run as high as 50 percent of the total cost of completing an installation, companies have been in need of innovative and efficient ways to enable potential clients to easily assess their solar potential and then purchase a system. Geostellar, an online solar marketplace, saw this challenge as an opportunity to use geospatial technological advancements to help the whole solar-curious chain become smarter about solar. Geostellar has created a customized, real-time system that allows users to assess their property's solar potential, analyze financing options and local service providers, and then chose the most favorable solar option in a few mouse clicks. CHALLENGE To achieve its mission to provide an on-demand, e-commerce system that could provide customized solar analytics, Geostellar first needed to have building vectors, the crucial data layer that would enable it to create precise maps and 3D models of all 3,143 counties in the US. Those foundational layers would then allow its system to map any rooftop's solar potential in real-time. With millions of building footprints to map nationwide, a manual process of identifying and delineating buildings would not be feasible. Geostellar required an image analysis system that would almost completely automate the land classification process. And since each environment would present unique classification challenges, the solution needed the intelligence to quickly and accurately distinguish different structures from vegetative types and map out only buildings. In addition, although Geostellar would predominantly use LiDAR imagery for extracting buildings, not every county in the US has LiDAR data available. So the company also required a flexible system that could easily ingest and accurately classify imagery of variable quality. overview eCognition is driven by rule sets, which are customized workflows of if-then scenarios the software uses to automatically classify specific objects and map land covers. With these rule sets, Geostella has the flexibility to input spatial data and any other relevant data and instruct the software to classify any given county and thematically map any 2,500-meter-square area by feature type. For the solar maps, that feature type is buildings. Location WEST VIRGINIA, USA "Without the ability to find and extract buildings, it would be impossible to map a rooftop's solar potential." David Levine, Geostellar CEO

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