Influence of LiDAR Point Cloud Density in the Geometric Characterization of Rooftops for Solar Photovoltaic Studies in Cities

The use of LiDAR (Light Detection and Ranging) data for the definition of the 3D geometry of roofs has been widely exploited in recent years for its posterior application in the field of solar energy. Point density in LiDAR data is an essential characteristic to be taken into account for the accurat...

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Main Authors: María Sánchez-Aparicio, Susana Del Pozo, Jose Antonio Martín-Jiménez, Enrique González-González, Paula Andrés-Anaya, Susana Lagüela
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/12/22/3726
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spelling doaj-e065c30436a149898bf87c7144e0e7b02020-11-25T04:02:16ZengMDPI AGRemote Sensing2072-42922020-11-01123726372610.3390/rs12223726Influence of LiDAR Point Cloud Density in the Geometric Characterization of Rooftops for Solar Photovoltaic Studies in CitiesMaría Sánchez-Aparicio0Susana Del Pozo1Jose Antonio Martín-Jiménez2Enrique González-González3Paula Andrés-Anaya4Susana Lagüela5Department of Cartographic and Land Engineering, University of Salamanca, Hornos Caleros, 50, 05003 Ávila, SpainDepartment of Cartographic and Land Engineering, University of Salamanca, Hornos Caleros, 50, 05003 Ávila, SpainDepartment of Cartographic and Land Engineering, University of Salamanca, Hornos Caleros, 50, 05003 Ávila, SpainDepartment of Cartographic and Land Engineering, University of Salamanca, Hornos Caleros, 50, 05003 Ávila, SpainDepartment of Cartographic and Land Engineering, University of Salamanca, Hornos Caleros, 50, 05003 Ávila, SpainDepartment of Cartographic and Land Engineering, University of Salamanca, Hornos Caleros, 50, 05003 Ávila, SpainThe use of LiDAR (Light Detection and Ranging) data for the definition of the 3D geometry of roofs has been widely exploited in recent years for its posterior application in the field of solar energy. Point density in LiDAR data is an essential characteristic to be taken into account for the accurate estimation of roof geometry: area, orientation and slope. This paper presents a comparative study between LiDAR data of different point densities: 0.5, 1, 2 and 14 points/m<sup>2</sup> for the measurement of the area of roofs of residential and industrial buildings. The data used for the study are the LiDAR data freely available by the Spanish Institute of Geography (IGN), which is offered according to the INSPIRE Directive. The results obtained show different behaviors for roofs with an area below and over 200 m<sup>2</sup>. While the use of low-density point clouds (0.5 point/m<sup>2</sup>) presents significant errors in the estimation of the area, the use of point clouds with higher density (1 or 2 points/m<sup>2</sup>) implies a great improvement in the area results, with no significant difference among them. The use of high-density point clouds (14 points/m<sup>2</sup>) also implies an improvement of the results, although the accuracy does not increase in the same ratio as the increase in density regarding 1 or 2 points/m<sup>2</sup>. Thus, the conclusion reached is that the geometrical characterization of roofs requires data acquisition with point density of 1 or 2 points/m<sup>2</sup>, and that higher point densities do not improve the results with the same intensity as they increase computation time.https://www.mdpi.com/2072-4292/12/22/3726LiDARdensitypoint cloudroofsgeometryphotovoltaic energy
collection DOAJ
language English
format Article
sources DOAJ
author María Sánchez-Aparicio
Susana Del Pozo
Jose Antonio Martín-Jiménez
Enrique González-González
Paula Andrés-Anaya
Susana Lagüela
spellingShingle María Sánchez-Aparicio
Susana Del Pozo
Jose Antonio Martín-Jiménez
Enrique González-González
Paula Andrés-Anaya
Susana Lagüela
Influence of LiDAR Point Cloud Density in the Geometric Characterization of Rooftops for Solar Photovoltaic Studies in Cities
Remote Sensing
LiDAR
density
point cloud
roofs
geometry
photovoltaic energy
author_facet María Sánchez-Aparicio
Susana Del Pozo
Jose Antonio Martín-Jiménez
Enrique González-González
Paula Andrés-Anaya
Susana Lagüela
author_sort María Sánchez-Aparicio
title Influence of LiDAR Point Cloud Density in the Geometric Characterization of Rooftops for Solar Photovoltaic Studies in Cities
title_short Influence of LiDAR Point Cloud Density in the Geometric Characterization of Rooftops for Solar Photovoltaic Studies in Cities
title_full Influence of LiDAR Point Cloud Density in the Geometric Characterization of Rooftops for Solar Photovoltaic Studies in Cities
title_fullStr Influence of LiDAR Point Cloud Density in the Geometric Characterization of Rooftops for Solar Photovoltaic Studies in Cities
title_full_unstemmed Influence of LiDAR Point Cloud Density in the Geometric Characterization of Rooftops for Solar Photovoltaic Studies in Cities
title_sort influence of lidar point cloud density in the geometric characterization of rooftops for solar photovoltaic studies in cities
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2020-11-01
description The use of LiDAR (Light Detection and Ranging) data for the definition of the 3D geometry of roofs has been widely exploited in recent years for its posterior application in the field of solar energy. Point density in LiDAR data is an essential characteristic to be taken into account for the accurate estimation of roof geometry: area, orientation and slope. This paper presents a comparative study between LiDAR data of different point densities: 0.5, 1, 2 and 14 points/m<sup>2</sup> for the measurement of the area of roofs of residential and industrial buildings. The data used for the study are the LiDAR data freely available by the Spanish Institute of Geography (IGN), which is offered according to the INSPIRE Directive. The results obtained show different behaviors for roofs with an area below and over 200 m<sup>2</sup>. While the use of low-density point clouds (0.5 point/m<sup>2</sup>) presents significant errors in the estimation of the area, the use of point clouds with higher density (1 or 2 points/m<sup>2</sup>) implies a great improvement in the area results, with no significant difference among them. The use of high-density point clouds (14 points/m<sup>2</sup>) also implies an improvement of the results, although the accuracy does not increase in the same ratio as the increase in density regarding 1 or 2 points/m<sup>2</sup>. Thus, the conclusion reached is that the geometrical characterization of roofs requires data acquisition with point density of 1 or 2 points/m<sup>2</sup>, and that higher point densities do not improve the results with the same intensity as they increase computation time.
topic LiDAR
density
point cloud
roofs
geometry
photovoltaic energy
url https://www.mdpi.com/2072-4292/12/22/3726
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