Identification of Roof Surfaces from LiDAR Cloud Points by GIS Tools: A Case Study of Lučenec, Slovakia

Abstract

The identification of roof surfaces is characterized by a sequence of several processing steps. The boundary detection of different types of roof is realized from light detection and ranging (LiDAR) cloud points and can confirm the real boundary of the roof. In the process of processing LiDAR data, shortcomings have been found regarding the inappropriate classification of points (class 6 “buildings”) concerning the roofs (the points of the building facade were marked as outliers and reclassified). In cases of insufficient point density, there is a problem with not being able to capture either the roof boundary or small roof objects, along with the possible occurrence of gaps inside the roof areas. This study proposes a processing procedure in a geographic information system (GIS) environment that advocates the identification of roof surfaces based on the LiDAR point cloud. We created the contours of a roof surface boundary with a simplified regular shape. From 824 roofs in the studied area, six different types of roof were selected, which this study presents in detail. The expected result of the study is the generation of segments inside the roof boundary. The study also includes the visualization of the outcomes of the spatial analyses of the identified roof surfaces, which forms the basis for determining the potential of solar systems with respect to green roofs for the development of smart city buildings.

Roof’s Potential and Suitability for PV Systems Based on LiDAR: A Case Study of Komárno, Slovakia

“…The methodology of the study consists of three parts ( Figure 1): (i) preparation and pre-processing of source data, (ii) creation of 3D models and spatial analysis, and (iii) evaluation of the potential use of PV systems on roofs. This case study follows the methodology proposed by [40], and the three parts of our methodology are described in more detail in Sections 2.2 and 2.4 below.…”

“…Estimating incident solar radiation on the surfaces of inclined and flat roofs in the urban environment requires the processing of complex geometry in the form of 2D polygons representing buildings [50] and the subsequent generation of 3D models of these buildings [51]. Our study partially applied the methodology described in [40] to ensure the segmentation of flat and sloping roofs from the LiDAR substrate. This methodology recommends using an approach based on modeling the roof ridge using the flow direction method to achieve segmentation of sloping roof surfaces.…”

“…[51]. Our study partially applied the methodology described in [40] to ensure the segmentation of flat and sloping roofs from the LiDAR substrate. This methodology recommends using an approach based on modeling the roof ridge using the flow direction method to achieve segmentation of sloping roof surfaces.…”

“…LiDAR was fully used for this purpose, which allowed us to create a 3D model of the roofs. Segmentation was used to identify individual roof planes, according to the methodology [40]. This methodology was modified by applying spatial slope analysis [56], which allowed the joint segmentation of flat and sloping roofs together.…”

Detecting Weak Signals of the Future: A System Implementation Based on Text Mining and Natural Language Processing

“…Remote sensing services are providing new applications in observation and analysis of information at remote locations by means of airborne vehicles, satellites, and on-ground equipment [58]. Remote sensing solutions have multifaceted social applications, such as the mapping of open water surfaces, soil moisture mapping, surface movements, data mosaic and satellite maps, geology and mineral resources, urban and rural development, disaster management support, and climate change studies, among others.…”