Which Data Source Is Best For My Solar Project?
Key takeaway: Satellite, LiDAR, and aerial imagery make it easy to draft preliminary solar designs for sales conversations; drone imagery confirms measurements and automatically constructs a photogrammetry-based 3D model to create final PV layouts with accuracy for engineering documents and install plans that never have a revision.
In solar, getting a quick preliminary proposal to a customer could be the difference between winning and losing a deal. That means the remote, preliminary design must be accurate enough to communicate production estimates, offset, and obstructions or shading implications with customers; at the same time, you have to build the plan quickly and cost-efficiently.
That’s where different data sources matter. Whether satellite, LiDAR, aerial, or on-site drone imagery, you need to choose the right source for the right step in your process.
This article explains the core data you need and how different data sources stack up.
The data you need for an accurate solar plan
A lot of data is required for a full, comprehensive plan set. However, you can often get away with slightly less accuracy and comprehensiveness, for the sake of speed, when doing a preliminary design. Here’s what you need for each stage:
Sales conversations: Estimated roof measurements (width, length, and pitch) and a general understanding of obstructions that might cause shade or stop you from placing a panel in a certain location.
Immediately before contract signing: Fully accurate roof measurements (width, length, pitch, and azimuth) with all obstructions and shade analysis noted so you can accurately place panels and estimate production.
Engineering documents and installation plan sets: Precise measurements with noted placements for roof racks, exact panel placement, and a fully accurate shading analysis lead to an accurate production estimate.
Understanding the four main data sources in rooftop solar
Here’s how the main data sources in solar stack up in terms of speed, accuracy, and cost.
Use the layering strategy for maximum accuracy and efficiency
Giving up a little bit of accuracy can make sense in the preliminary stages of a deal. First, remote data sources are easy to pull from, speeding up your proposal process. Second, many customers may not want someone coming to their property until they’ve made a decision. Third, you save time and money on deals that may not close anyway.
But you should only sacrifice the minimum amount of accuracy for the sake of speed and/or customer experience.
Rather than solely relying on one data source for preliminary designs, you should follow a data-layering strategy:
Start with satellite: Whether Google Maps, Bing, Nearmap, or another data source, quickly get the lay of the land for the general roof pitch, property type, and obvious obstructions like trees.
Layer on LiDAR: Add a LiDAR layer to the preliminary design, ensuring you have a more complete picture of object height on site.
Confirm any small issues: In a grainy satellite image, you might see something that looks like an obstruction. See if you can confirm that with other publicly available data sources, for example, if you were using Nearmap, try looking at Bing or Google Earth to see if they have a more recent or slightly clearer image.
This three-step layering strategy will help ensure you have the most accurate preliminary design possible without sacrificing speed, efficiency, or customer experience. From there, you can confirm measurements with a drone on-site when it makes sense for your sales process.
Choose the right data for the right step
Solar projects require a lot of data, and some sources are more critical at each step than others. While you can work quickly in the preliminary stages, you need fully accurate measurements to inform production estimates, procurement, engineering docs, and installation planning. With each successive stage, the need for accurate data increases to maintain a quality build process.
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