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Remote Sens. 2015, 7(12), 17016-17034; doi:10.3390/rs71215866

Quality Assessment of Roof Planes Extracted from Height Data for Solar Energy Systems by the EAGLE Platform

1
Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Englerstr. 7, Karlsruhe 76128, Germany
2
Department of Geography, University of Leicester, University Road, Leicester LE1 7RH, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Richard Müller and Prasad S. Thenkabail
Received: 8 July 2015 / Revised: 30 November 2015 / Accepted: 7 December 2015 / Published: 17 December 2015
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Abstract

Due to the increasing scarcity of fossil fuels and the upwards trend in energy costs over time, many countries—especially in Europe—have begun to modify their energy policies aiming to increase that percentage obtained from renewable energies. The EAGLE (FP7 program, European Commission) has developed a web-based platform to promote renewable energy systems (RES) in the public and private sectors, and to deliver a comprehensive information source for all interested users. In this paper, a comprehensive quality assessment of extracted roof planes suitable for solar energy installations (photovoltaic, solar thermal) from height data derived automatically from both LiDAR (Light Detection and Ranging) and aerial images will be presented. A shadow analysis is performed regarding the daily path of the sun including the shading effects of nearby objects (chimneys, dormers, vegetation, buildings, topography, etc.). A quality assessment was carried out for both LiDAR and aerial images of the same test sites in UK and Germany concerning building outline accuracy, extraction rate of roof planes and the accuracy of their geometric parameters (inclination and aspect angle, size). The benefit is an optimized system to extract roof planes for RES with a high level of detail, accuracy and flexibility (concerning different commonly available data sources) including an estimation of quality of the results which is important for individual house owners as well as for regional applications by governments or solar energy companies to judge their usefulness. View Full-Text
Keywords: quality assessment; roof plane extraction; LiDAR data; aerial images; renewable energies; urban environment; shadow analysis quality assessment; roof plane extraction; LiDAR data; aerial images; renewable energies; urban environment; shadow analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Schuffert, S.; Voegtle, T.; Tate, N.; Ramirez, A. Quality Assessment of Roof Planes Extracted from Height Data for Solar Energy Systems by the EAGLE Platform. Remote Sens. 2015, 7, 17016-17034.

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