Extraction of Vertical Walls from Mobile Laser Scanning Data for Solar Potential Assessment

Abstract

In recent years there has been an increasing demand among home owners for cost effective sustainable energy production such as solar energy to provide heating and electricity. A lot of research has focused on the assessment of the incoming solar radiation on roof planes acquired by, e.g., Airborne Laser Scanning (ALS). However, solar panels can also be mounted on building facades in order to increase renewable energy supply. Due to limited reflections of points from vertical walls, ALS data is not suitable to perform solar potential assessment of vertical building facades. This paper focuses on a new method for automatic solar radiation modeling of facades acquired by Mobile Laser Scanning (MLS) and uses the full 3D information of the point cloud for both the extraction of vertical walls covered by the survey and solar potential analysis. Furthermore, a new method isintroduced determining the interior and exterior face, respectively, of each detected wall in order to calculate its slope and aspect angles that are of crucial importance for solar potential assessment. Shadowing effects of nearby objects are considered by computing the 3D horizon of each point of a facade segment within the 3D point cloud

Segmentation-Based Ground Points Detection from Mobile Laser Scanning Point Cloud

“…Generally, most building façade segments are very large and aligned vertically Jochem et al, 2011), and most vegetation segments are small (Zhang et al, 2013;Rutzinger et al, 2008) and scattered in 3D space Zhang et al, 2013).Two features about orientation and scatterness are selected to detect object segment herein. A method to calculate the orientation and the scatterness of a planar segment was proposed in (Zhang et al, 2013), where the scatterness is calculated based on the principal components analysis .…”

“…As a stateof-the-art technology for mapping and remote sensing, MLS can serve as an effective solution for surveying complex environment, such as urban environment and road corridors . Many mature MLS systems can be found from the market (Kaartinen et al, 2012), and widely used for various purposes such as road inventory (Pu et al, 2011), map update (Hwang et al, 2013), façade extraction Jochem et al, 2011), building reconstruction (Frueh et al, 2005;Becker et al, 2009), road marking extraction , window extraction (Wang et al, 2012), tree extraction (Wu et al, 2013), object extraction and recognition Yu et al, 2013;Golovinskiy et al, 2009, etc).…”

GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues

“…Jochem et al present a first approach in this direction [102], but there is a growing need for more holistic and fine-grained analysis methods. Future research challenges include the integration of ray tracing algorithms [103], the analysis of high-resolution building data [104], the integration of building part parameters, like walls, windows, line networks, etc.…”

A Density-Based Clustering Method for Urban Scene Mobile Laser Scanning Data Segmentation

“…where (p a , p b ) is the pair point element in the pair point set PPS ij , and C ij a , C ij b are the corresponding curvatures of the pair point measured based on Equation (12).…”

“…Moreover, MLS data are more efficiently acquired than TLS data, as the latter are collected by manually positioned systems. Many researchers have studied the use of MLS data in urban scenes intensively, including in road [6,7] and road marking [8][9][10] detection, building detection and reconstruction [11][12][13], pole-like object detection [3,14,15], tree detection and modeling [16][17][18], and urban scene segmentation and classification [19][20][21][22][23].…”