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Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data

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Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data

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dc.contributor.author Hermosilla, T. es_ES
dc.contributor.author Coops, Nicholas es_ES
dc.contributor.author Ruiz Fernández, Luis Ángel es_ES
dc.contributor.author Moskal, Monika es_ES
dc.date.accessioned 2015-12-18T14:52:20Z
dc.date.available 2015-12-18T14:52:20Z
dc.date.issued 2014-03
dc.identifier.issn 2150-704X
dc.identifier.uri http://hdl.handle.net/10251/59037
dc.description This is an author's accepted manuscript of an article published in “Remote Sensing Letters", Volume 5, Issue 4, 2014; copyright Taylor & Francis; available online at: http://www.tandfonline.com/doi/abs/10.1080/2150704X.2014.903350 es_ES
dc.description.abstract [EN] When processing scanning LiDAR data, it is commonly assumed that the extracted full-waveform LiDAR pulse registers truly vertical information of forest canopies. This assumption may lead to uncertain results for the spatiotemporal analysis of the waveforms due to off-nadir scanning angles and varying trajectories travelled by the pulses in overlapping strips. In this letter, we investigate these assumptions and undertake some preliminary analysis to overcome their impacts on forest-based LiDAR analyses. Our results demonstrate that for a standard LiDAR forest acquisition programme in Oregon, USA, most of the hits (83%) are acquired off-nadir, which leads to positional displacements on the ground of the full-waveforms of about 0.20 m for each 1-m height increment. We propose an approach to synthetize multiple waveform data into composite waveforms containing the vertical profile of vegetation for a given location. This approach is based on partitioning the aboveground vertical space into voxels and using the maximum full-waveform intensity value to construct new full-waveforms comprising the vertical information of the various waveforms crossing over a location. Our initial results indicate that deriving spatiotemporal metrics from the composite pseudo-vertical full-waveforms produces a more consistent response across adjacent height levels, which in turn enables a more complete characterization and more vegetation structure to be retrieved. We conclude that this type of pseudo-vertical full-waveform analysis is necessary to more fully understand the impact of the return signals from tree crowns es_ES
dc.description.sponsorship This paper was developed as a result of a visiting scholar grant funded by the Erasmus Mundus Programme of the European Commission under the Transatlantic Partnership for Excellence in Engineering – TEE Project. The authors also wish to thank the Generalitat Valenciana for the mobility grant [BEST/2012/235] and the Panther Creek Remote Sensing and Research cooperative programme for the data provided for this research.
dc.language Inglés es_ES
dc.publisher Taylor & Francis: STM, Behavioural Science and Public Health Titles es_ES
dc.relation.ispartof Remote Sensing Letters es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject.classification INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA es_ES
dc.title Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1080/2150704X.2014.903350
dc.relation.projectID info:eu-repo/grantAgreement/GVA//BEST%2F2012%2F235/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Cartográfica Geodesia y Fotogrametría - Departament d'Enginyeria Cartogràfica, Geodèsia i Fotogrametria es_ES
dc.description.bibliographicCitation Hermosilla, T.; Coops, N.; Ruiz Fernández, LÁ.; Moskal, M. (2014). Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data. Remote Sensing Letters. 5(4):332-341. https://doi.org/10.1080/2150704X.2014.903350 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1080/2150704X.2014.903350 es_ES
dc.description.upvformatpinicio 332 es_ES
dc.description.upvformatpfin 341 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 5 es_ES
dc.description.issue 4 es_ES
dc.relation.senia 265530 es_ES
dc.contributor.funder Generalitat Valenciana
dc.contributor.funder Erasmus+ es_ES
dc.contributor.funder European Commission es_ES
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