Once a user searches for an address or clicks on a building, the wizard appears. This is the first screen of the wizard, which shows approximate monthly power generation that the building could potentially produce if a solar system is installed.
The second screen of the wizard displays potential savings based on an estimated solar system size for the building.
Graphic shows rooftop obstructions that are automatically mapped through the feature extraction process.
Graphic shows rooftop obstructions that solar installers can see for each building in the back end of the application when they login.
By Matthew Krusemark, GISP Information Services Manager Denver Regional Council of Governments Denver, Colo. www.drcog.org
The Denver Regional Solar Map is a Web-based application the Denver Regional Council of Governments (DRCOG) developed with funding from a New Energy Economic Development grant through the Colorado Governor’s Energy Office. DRCOG began developing the site in March 2010 and launched in November 2010. The application lets users easily locate their properties and explore the benefits of solar photo-voltaic (PV) installation through a simple address search for their buildings.
In addition, it allows local solar installers in the Denver region login access to respond to consumer inquiries. DRCOG’s initial hopes were that the project would not only bolster adoption of renewable energy in the Denver region, but also create jobs by connecting local solar providers and contractors with building owners. Installers have been actively using the site to respond to consumer inquiries.
The Denver metropolitan area encompasses over 5,000 square miles making it a challenge to find contiguous, detailed geospatial data to support the solar map needs (see Figure 1). In order to accurately calculate solar PV potential for buildings in the region, DRCOG needed several key datasets to support the application, including digital orthophotography for feature and building identification, LiDAR to quickly identify rooftop obstructions on buildings that would potentially inhibit solar PV panel placement, and building footprints where LiDAR information might not exist.
DRCOG has a long history of collaboration that includes 56 member governments (local municipalities and counties) and other regional, state and federal agency partners in the region. One area of collaboration in the last decade has been in the development of regional geospatial data to support long-range planning and current and future transportation investments. The Denver Regional Aerial Photography Project (DRAPP) has become the de facto regional base map with which many agency’s spatial data is often referenced, including transportation, property ownership (parcels) and land use/zoning, to name a few.
The DRAPP project operates on a two-year cycle and is usually made up of a consortium of 40+ members, making the approximately 1 million dollar project affordable to all the partners involved. In addition to DRAPP, a Denver Regional Data Consortium (DRDC) was founded in 2009 to foster regional data development beyond the DRAPP imagery effort that could be used in regional software decision-making applications like the Denver Regional Solar Map and others. These additional DRDC-developed datasets include transportation, open space, and the built environment (categories of building types, number of building floors and addresses, for example).
The DRAPP imagery provided the base map for the solar mapping effort. In 2008, LiDAR was collected to support emergency planning for the Democratic National Convention (DNC, an article about which appeared in the Spring 2009 issue of Imaging Notes) through additional partnerships that included local, regional and federal government agencies and made publicly available after the DNC event by the United States Geological Survey (USGS) NSDI Partnership Office. DRCOG acquired DRAPP imagery in the spring of 2008. The summer 2008 LiDAR acquisition covered the densest portions of the built environment in the region which is made up of 512,000+ buildings. However, the LiDAR acquisition area only encompassed approximately 20 percent of the geographic land area of the region making it necessary to reach out to local governments to fill in those gaps with building footprints they had already developed. The local governments and DRDC partners in the Denver region provided an additional 306,000+ building footprints to fill the gaps.
Partnerships and Economies of Scale
DRCOG partnered with Woolpert, Inc. (Dayton, Ohio) to develop a feature extraction methodology to identify rooftop obstructions to solar PV placement on buildings within the LiDAR project area. Woolpert was able to utilize DRAPP imagery, DNC LiDAR and local agency building footprints to create an automated feature extraction process that mapped rooftop obstructions for all 512,000+ buildings.
Outside the LiDAR project area, DRCOG developed in-house algorithms that calculate a more generalized solar estimation for those areas that only had building footprints. In addition, where no building footprints or LiDAR existed, DRCOG utilized its regional parcel inventory of over 1.2 million parcels to fill in the gaps and calculate a single and more generalized solar estimation so that all facilities in the region would be included.
Finally, DRCOG partnered with the Colorado Solar Energy Industries Association (COSEIA, Boulder, Colo.) and worked even more closely with one of the COSEIA members who is a local solar installer to develop region-specific solar power generation estimates, electric bill savings and an estimate of solar PV system sizing for each building in the database. This was an important partnership that provides Solar Map users with the most accurate solar estimation specific to Colorado’s environmental factors.
The App Framework
DRCOG also partnered with a Woolpert software developer to build a customized front end. It was important for DRCOG to utilize a mix of open source and commercial technologies that fit the existing DRCOG architecture with which the in-house GIS programmers were already familiar, and would be able to further extend in the future, as needed.
DRCOG staff used the Google Maps API (Google, Inc., Mountain View, Calif.) to allow the app user to geocode their business or residential address, or zoom around manually to find a building that they might be interested in (see Figure 2). The Google Maps API was chosen because it is already familiar to most Internet users and no training would be required to learn to geocode an address or use the map to locate a building. After a building is chosen by the user, a wizard is utilized to show the benefits of solar PV installation (see Figures 3 and 4). DRCOG’s open source enterprise spatial database environment is PostGIS (OSGeo Project of the OSGeo Foundation, Vancouver, BC, Canada) and this is where all the building locations (800,000+ records) and rooftop obstruction polygons (2.5+ million) are stored for use in the application. Woolpert’s software developer used the Ruby on Rails framework to make the connection between the Google Maps API click events and the PostGIS database.
The partnership with COSEIA provided the solar estimation to populate the buildings database, and provided DRCOG members with a login to the application that would allow the solar installers to see and explore the obstructions that were mapped from Woolpert’s feature extraction process (see Figures 5 and 6). COSEIA members can create a login to the site and explore the mapping details of the application that might be too complex for the users.
DRCOG performed detailed interviews with several COSEIA members in gathering requirements for their interface and mapping needs. DRCOG GIS programmers then performed usability testing with additional COSEIA members to get their final feedback before deploying the application to the public. Once a member of the public chooses through the application to be “contacted by a local installer,” the record goes into a queue where up to five installers can contact and provide a more detailed building assessment and solar PV estimate for prospective customers.
The Benefits and the Future
The Denver Regional Solar Map has leveraged existing data and resources in the Denver region from local, regional, state, federal and private partnerships. Acquisition of high resolution digital orthophotography and LiDAR in conjunction with the availability of building footprint data has greatly benefitted the potential for solar PV installations on buildings throughout the Denver metropolitan region.
The application has created a foundational mapping framework that is complex on the backend for local solar installers to research buildings with obstructions, and simple yet powerful on the front end for the public to learn more about solar and for the local installers to connect directly to customers.
After the first year of use of the application by the public and COSEIA members, DRCOG will be analyzing and sharing the successes and challenges encountered and thoughts on how the application might be improved for future use. In addition, the application data, database and process that were developed for identifying rooftop obstructions could easily be reprocessed in the future when new DRAPP imagery and LiDAR are acquired. This allows the team to leverage the existing methodology and make improvements to the data behind the application without a significant additional investment of resources.