期刊名称：International Journal of Environment and Geoinformatics
电子版ISSN：2148-9173
出版年度：2019
卷号：6
期号：3
页码：305-308
DOI：10.30897/ijegeo.636962
语种：English
出版社：IJEGEO
摘要：Solar energy is a renewable energy sourcedirectly from sunlight and its production depends on roof characteristics suchas roof type and size. In solar potential analysis, the main purpose is todetermine the suitable roofs for the placement of solar panels. Hence, roofplane detection plays a crucial role in solar energy assessment. LIDARtechnology in the air is one of the most widely used fast solutions to produce3D dense point clouds. In addition, automatic feature extraction is included in3D Modeling in computer vision and photogrammetry. There are several techniquesfor restructuring and classification in this area. RANSAC (RANdom SAmpleConsensus) is one of the data processing methods for using LIDAR data. In thisstudy, a detailed comparison was presented between aerial photogrammetry dataand LIDAR data for roof plane recognition applying RANSAC (Random SampleConsensus) algorithm. RANSAC algorithm was performed to 3D-point cloudsobtained by both LIDAR (Laser Ranging and Detection) and aerial photogrammetricsurvey. In this regard, solar energy assessment from the results can beapplied. It is shown that, the RANSAC algorithm detects building roofs betteron the point cloud data acquired from airborne LIDAR regarding completenesswithin model, since aerial photogrammetric survey provides noisy data in spiteof its high-density data. This noise in the source data leads to deformationsin roof plane detection. The study area of the project is the campus ofIstanbul Technical University.
关键词：LIDAR; Aerial Photogrammetry; Roof Plane; RANSAC; Point Cloud
