Jacques, DA, Gooding, J, Giesekam, JJ et al. (2 more authors) (2014) Methodology for the assessment of PV capacity over a city region using low-resolution LiDAR data and application to the City of Leeds (UK). Applied Energy, 124. 28 - 34. ISSN 0306-2619
Abstract
An assessment of roof-mounted PV capacity over a local region can be accurately calculated by established roof segmentation algorithms using high-resolution light detection and ranging (LiDAR) datasets. However, over larger city regions often only low-resolution LiDAR data is available where such algorithms prove unreliable for small rooftops. A methodology optimised for low-resolution LiDAR datasets is presented, where small and large buildings are considered separately. The roof segmentation algorithm for small buildings, which are typically residential properties, assigns a roof profile to each building from a catalogue of common profiles after identifying LiDAR points within the building footprint. Large buildings, such as warehouses, offer a more diverse range of roof profiles but geometric features are generally large, so a direct approach is taken to segmentation where each LiDAR point within the building footprint contributes a separate roof segment. The methodology is demonstrated by application to the city region of Leeds, UK. Validation by comparison to aerial photography indicates that the assignment of an appropriate roof profile to a small building is correct in 81% of cases.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014. Elsevier. Uploaded in accordance with the publisher's self-archiving policy. NOTICE: this is the author’s version of a work that was accepted for publication in Applied Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Applied Energy, 124,(2014) DOI:10.1016/j.apenergy.2014.02.076 |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) > Energy Research Institute (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Dec 2014 12:56 |
Last Modified: | 02 Aug 2015 06:43 |
Published Version: | http://dx.doi.org/10.1016/j.apenergy.2014.02.076 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.apenergy.2014.02.076 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:81537 |