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dc.contributor.authorCastelletti D
dc.contributor.authorPasolli L
dc.contributor.authorBruzzone L
dc.contributor.authorNotarnicola C
dc.contributor.authorDemir B
dc.date.accessioned2018-09-25T10:51:44Z
dc.date.available2018-09-25T10:51:44Z
dc.date.issued2016
dc.identifier.issn0196-2892
dc.identifier.urihttp://dx.doi.org/10.1109/TGRS.2016.2551326
dc.identifier.urihttp://hdl.handle.net/10863/6097
dc.description.abstractThis paper presents a novel hybrid method to the estimation of bio/geophysical parameters, which models and corrects deviations from correct target values when theoretical electromagnetic models are used for the inversion process. The proposed hybrid method integrates theoretical models with empirical observations associated to a few field reference samples. This is achieved based on two steps. In the first step, deviations between estimations obtained by a theoretical model and empirical observations are initially computed. Then, deviations associated to unlabeled samples (for which reference measures are not existing) are characterized based on two different strategies: 1) the global deviation bias strategy (which assumes that the deviations of samples are constant within the input space); and 2) the local deviation bias strategy (which assumes that the deviations of samples are variable within different portions of the input space). In the second step, the theoretical model estimates of unlabeled samples are corrected based on the estimated deviations. The experimental analysis carried out in the context of soil moisture content retrieval from microwave remotely sensed data confirms the effectiveness of the proposed hybrid estimation method.en_US
dc.language.isoenen_US
dc.rights
dc.subjectRemote sensingen_US
dc.titleA Novel Hybrid Method for the Correction of the Theoretical Model Inversion in Bio/Geophysical Parameter Estimationen_US
dc.typeArticleen_US
dc.date.updated2018-09-25T10:43:40Z
dc.language.isiEN-GB
dc.journal.titleIEEE Transactions on Geoscience and Remote Sensing
dc.description.fulltextnoneen_US


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