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Title: Quality assessment of roof planes extracted from height data for solar energy systems by the EAGLE platform
Authors: Schuffert, Simon
Voegtle, Thomas
Tate, Nicholas J.
Ramirez, Alberto
First Published: 17-Dec-2015
Publisher: MDPI
Citation: Remote Sensing, 2015, 7, pp. 17016-17034
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.
DOI Link: 10.3390/rs71215866
ISSN: 2072-4292
eISSN: 2072-4292
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2015. This is an open-access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Appears in Collections:Published Articles, Dept. of Geography

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