UAV PHOTOGRAMMETRY FOR FEATURE EXTRACTION AND MAPPING OF CORRUGATED INDUSTRIAL ROOFTOPS

Abstract

Corrugated roof sheets used for large-scale industrial rooftops have the potential to carry solar panels. The sheets, however, need to be surveyed so that the solar panels can be installed according to the measurements of various features. For this purpose, information about exhausts, skylights, corrugation spacing, including extraction of roof slope, which is essential for planning solar panel installations, needs to be measured and mapped. UAV surveying, in contrast to traditional surveying and manual measurements, has proven to be of great benefit in the recent years due to its mobility and low-cost operations and with photogrammetric processing, 3D information with sufficient details can be obtained. In this study, we explored the use of UAV platforms for extraction of fine features (corrugations) of industrial rooftops. The point cloud obtained after photogrammetric processing contained significant geometric information about the corrugation, along with noise. The point cloud was processed to remove noise. Smoothing and exaggeration in the Z-direction, without altering X and Y coordinates, ensured a smooth profile with pronounced peaks at the location of corrugations. Cross-sectional profiles were extracted as a vector and peaks in the profile indicated presence of the corrugation. A peak identification algorithm was used to extract local maxima with corresponding distances along the profile. The peak points were plotted on the ortho-image, and the mean distance between subsequent peaks was approximately 20.3 cm with a standard deviation of 1–2 cm. The spacing between the corrugations was approximately 20 cm when measured manually.