Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/206983
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dc.contributor.authorWang, Shenges_ES
dc.contributor.authorBaum, Andreases_ES
dc.contributor.authorZarco-Tejada, Pablo J.es_ES
dc.contributor.authorDam-Hansen, Carstenes_ES
dc.contributor.authorThorseth, Anderses_ES
dc.contributor.authorBauer-Gottwein, Peteres_ES
dc.contributor.authorBandini, Filippoes_ES
dc.contributor.authorGarcía, Mónicaes_ES
dc.date.accessioned2020-04-08T09:18:45Z-
dc.date.available2020-04-08T09:18:45Z-
dc.date.issued2019-09-
dc.identifier.citationISPRS Journal of Photogrammetry and Remote Sensing 155: 58-71 (2019)es_ES
dc.identifier.issn0924-2716-
dc.identifier.urihttp://hdl.handle.net/10261/206983-
dc.description.abstractUnlike satellite earth observation, multispectral images acquired by Unmanned Aerial Systems (UAS) provide great opportunities to monitor land surface conditions also in cloudy or overcast weather conditions. This is especially relevant for high latitudes where overcast and cloudy days are common. However, multispectral imagery acquired by miniaturized UAS sensors under such conditions tend to present low brightness and dynamic ranges, and high noise levels. Additionally, cloud shadows over space (within one image) and time (across images) are frequent in UAS imagery collected under variable irradiance and result in sensor radiance changes unrelated to the biophysical dynamics at the surface. To exploit the potential of UAS for vegetation mapping, this study proposes methods to obtain robust and repeatable reflectance time series under variable and low irradiance conditions. To improve sensor sensitivity to low irradiance, a radiometric pixel-wise calibration was conducted with a six-channel multispectral camera (mini-MCA6, Tetracam) using an integrating sphere simulating the varying low illumination typical of outdoor conditions at 55oN latitude. The sensor sensitivity was increased by using individual settings for independent channels, obtaining higher signal-to-noise ratios compared to the uniform setting for all image channels. To remove cloud shadows, a multivariate statistical procedure, Tucker tensor decomposition, was applied to reconstruct images using a four-way factorization scheme that takes advantage of spatial, spectral and temporal information simultaneously. The comparison between reconstructed (with Tucker) and original images showed an improvement in cloud shadow removal. Outdoor vicarious reflectance validation showed that with these methods, the multispectral imagery can provide reliable reflectance at sunny conditions with root mean square deviations of around 3%. The proposed methods could be useful for operational multispectral mapping with UAS under low and variable irradiance weather conditions as those prevalent in northern latitudes.es_ES
dc.description.sponsorshipThe authors would like to thank the EU and Innovation Fund Denmark (IFD) for funding, in the frame of the collaborative international consortium AgWIT financed under the ERA-NET Co-fund Water Works 2015 Call. This ERA-NET is an integral part of the 2016 Joint Activities developed by the Water Challenges for a Changing World Joint Programme Initiative (Water JPI). This study was also supported by the Smart UAV project from IFD [125-2013-5]. SW acknowledge an internal PhD grant from the Department of Environmental Engineering at DTU and a short-term research stage with PZT financed by the COST action OPTIMISE.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relation.isversionofPostprintes_ES
dc.rightsopenAccessen_EN
dc.subjectReflectancees_ES
dc.subjectSensor calibrationes_ES
dc.subjectCloud shadow removales_ES
dc.subjectTucker tensor decompositiones_ES
dc.subjectUnmanned Aerial Systemes_ES
dc.titleUnmanned Aerial System multispectral mapping for low and variable solar irradiance conditions: Potential of tensor decompositiones_ES
dc.typeartículoes_ES
dc.identifier.doi10.1016/j.isprsjprs.2019.06.017-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttps://doi.org/10.1016/j.isprsjprs.2019.06.017es_ES
dc.embargo.terms2021-09-01es_ES
dc.contributor.funderInnovation Fund Denmarkes_ES
dc.contributor.funderEuropean Commissiones_ES
dc.contributor.funderTechnical University of Denmarkes_ES
dc.relation.csices_ES
oprm.item.hasRevisionno ko 0 false*
dc.identifier.funderhttp://dx.doi.org/10.13039/501100000780es_ES
item.grantfulltextopen-
item.cerifentitytypePublications-
item.openairetypeartículo-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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