Advantages of the SolAR Methodology

SolAR has been created using the most up-to-date and accurate high-resolution stereo aerial photography. The methodology used to create SolAR has been developed after extensive research and was found to produce the most accurate results. Using stereo imagery means that inaccuracies with measurements when using 2D imagery, incurred due to loss of perspective, are avoided. These could be as much as 15-20%. This methodology also identifies skylights, dormer windows and chimneys and excludes these areas from any analysis as unusable space, again producing more accurate results.

LiDAR (Digital Surface Model)

Whilst LIDAR can be highly accurate it is still reasonably coarse in detail when compared to aerial photography. Higher detail LiDAR is available but it is very expensive and coverage is sparse. From our own research even the higher detail data is not sufficient to produce accurate results. Analysis of LiDAR is usually automated; due to the nature of the data it is very easy, with the push of button, to produce slope analysis and solar irradiation calculations. However relating these calculations to the exact roof areas is highly problematic. It is possible to segment the data using 2D building polygons, however these will never match exactly due to inaccuracies in both datasets, this means that potentially non-roof areas (i.e. the walls of the buildings) are inadvertently taken into account, and will skew the results.

2D Aerial Photography (such as that seen on Google Earth)

The 2D nature of the imagery means that the measurements of the roof area will be inaccurate due to the loss of perspective. It should be noted that Google terms of service do not allow the user to make derivative works from the aerial photography. This restriction applies to the Google Earth API, Google Earth and Google Earth Pro.