Identifying obstacles and key measurements of roof surfaces using a digital surface model and an orthomosaic
This thesis proposes a machine-learning-supported pipeline which, put together, provides an estimate of roof surface area for solar panel installation. This pipeline is comprised of roof segmentation based on images and digital surface models and provides subsequent identification of key measurements such as roof length, roof width and roof angle. Obstacles belonging to a roof are also identified
