Automatic Parametrization and Shadow Analysis of Roofs in Urban Areas from ALS Point Clouds with Solar Energy Purposes
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Automatic Parametrization and Shadow Analysis of Roofs in Urban Areas from ALS Point Clouds with Solar Energy PurposesData
2018-07-28Centro/Dpto/Entidade
Construcións e Estruturas Arquitectónicas, Civís e AeronáuticasCita bibliográfica
Soilán, M.; Riveiro, B.; Liñares, P.; Padín-Beltrán, M. Automatic Parametrization and Shadow Analysis of Roofs in Urban Areas from ALS Point Clouds with Solar Energy Purposes. ISPRS Int. J. Geo-Inf. 2018, 7, 301. https://doi.org/10.3390/ijgi7080301
Resumo
[Abstract]: A basic feature of modern and smart cities is their energetic sustainability, using clean and renewable energies and, therefore, reducing the carbon emissions, especially in large cities. Solar energy is one of the most important renewable energy sources, being more significant in sunny climate areas such as the South of Europe. However, the installation of solar panels should be carried out carefully, being necessary to collect information about building roofs, regarding its surface and orientation. This paper proposes a methodology aiming to automatically parametrize building roofs employing point cloud data from an Aerial Laser Scanner (ALS) source. This parametrization consists of extracting not only the area and orientation of the roofs in an urban environment, but also of studying the shading of the roofs, given a date and time of the day. This methodology has been validated using 3D point cloud data of the city of Santiago de Compostela (Spain), achieving roof area measurement errors in the range of ±3%, showing that even low-density ALS data can be useful in order to carry out further analysis with energetic perspective.
Palabras chave
Aerial Laser scanner
Point cloud processing
Segmentation
Roof parametrization
Roof shading
Point cloud processing
Segmentation
Roof parametrization
Roof shading
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© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open Access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
ISSN
2220-9964