Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/82252
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dc.contributorInterdisciplinary Division of Aeronautical and Aviation Engineering-
dc.creatorShao, Hen_US
dc.creatorChen, YWen_US
dc.creatorYang, ZRen_US
dc.creatorJiang, Cen_US
dc.creatorLi, Wen_US
dc.creatorWu, HHen_US
dc.creatorWang, SWen_US
dc.creatorYang, Fen_US
dc.creatorChen, Jen_US
dc.creatorPuttonen, Een_US
dc.creatorHyyppa, Jen_US
dc.date.accessioned2020-05-05T05:59:17Z-
dc.date.available2020-05-05T05:59:17Z-
dc.identifier.urihttp://hdl.handle.net/10397/82252-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2019 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/).en_US
dc.rightsThe following publication Shao, H.; Chen, Y.; Yang, Z.; Jiang, C.; Li, W.; Wu, H.; Wang, S.; Yang, F.; Chen, J.; Puttonen, E.; Hyyppä, J. Feasibility Study on Hyperspectral LiDAR for Ancient Huizhou-Style Architecture Preservation. Remote Sens. 2020, 12, 88 is available at https://dx.doi.org/10.3390/rs12010088en_US
dc.subjectHuizhou-styleen_US
dc.subjectAncient architectureen_US
dc.subjectHyperspectral LiDARen_US
dc.subjectClassificationen_US
dc.titleFeasibility study on hyperspectral LiDAR for ancient huizhou-style architecture preservationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1en_US
dc.identifier.epage16en_US
dc.identifier.volume12en_US
dc.identifier.issue1en_US
dc.identifier.doi10.3390/rs12010088en_US
dcterms.abstractHuizhou-style ancient architecture was one of the most important genres of architectural heritage in China. The architecture employed bricks, woods, and stones as raw materials, and timber frames were significant structures. Due to the drawback that the timbers were vulnerable to moisture and atmospheric agents, ancient timber buildings needed frequent protective interventions to maintain its good condition. Such interventions unavoidably disrupted the consistency between the original timber components. Besides this, the modifications brought about difficulty in correctly analysing and judging the state of existing ancient buildings, which, in current preservation practices, mainly rely on the expertise of skilled craftsmen to classify wood species and to identify the building-age of the timber components. Therefore, the industry and the research community urgently need a technique to rapidly and accurately classify wood materials and to discriminate building-age. In the paper, we designed an eye-safe 81-channel hyperspectral LiDAR (HSL) to tackle these issues. The HSL used an acousto-optic tunable filter (AOTF) as a spectral bandpass filter, offering the HSL measurements with 5 nm spectral resolution. Based on the HSL measurements, we analysed the relationship between the surface and cross-section spectral profiles of timber components from different ancient architectures built in the early Qing dynasty (300 years), late Qing dynasty (100 years), and nowadays, and confirmed the feasibility of using surface spectra of timber components for classification purpose. We classified building-ages and wood species with multiple Naive Bayes (NB) and support vector machine (SVM) classifiers by the surface spectra of timber components; this also unveiled the possibility of classifying gnawed timber components from its spectra for the first time. The encouraging experimental results supported that the AOTF-HSL is feasible for historic timber building preservation.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationRemote sensing, 1 Jan. 2020, v. 12, no. 1, 88, p. 1-16en_US
dcterms.isPartOfRemote sensingen_US
dcterms.issued2020-
dc.identifier.isiWOS:000515391700088-
dc.identifier.scopus2-s2.0-85078291407-
dc.identifier.eissn2072-4292en_US
dc.identifier.artn88en_US
dc.description.validate202006 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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