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Coupled retrieval of the three phases of water from spaceborne imaging spectroscopy measurements

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Coupled retrieval of the three phases of water from spaceborne imaging spectroscopy measurements

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dc.contributor.author Bohn, Niklas es_ES
dc.contributor.author Guanter-Palomar, Luis María es_ES
dc.contributor.author Kuester, Theres es_ES
dc.contributor.author Preusker, René es_ES
dc.contributor.author Segl, Karl es_ES
dc.date.accessioned 2023-04-26T18:01:18Z
dc.date.available 2023-04-26T18:01:18Z
dc.date.issued 2020-06-01 es_ES
dc.identifier.issn 0034-4257 es_ES
dc.identifier.uri http://hdl.handle.net/10251/192982
dc.description.abstract [EN] Measurements of reflected solar radiation by imaging spectrometers can quantify water in different states (solid, liquid, gas) thanks to the discriminative absorption shapes. We developed a retrieval method to quantify the amount of water in each of the three states from spaceborne imaging spectroscopy data, such as those from the German EnMAP mission. The retrieval couples atmospheric radiative transfer simulations from the MODTRAN5 radiative transfer code to a surface reflectance model based on the Beer-Lambert law. The model is inverted on a per-pixel basis using a maximum likelihood estimation formalism. Based on a unique coupling of the canopy reflectance model HySimCaR and the EnMAP end-to-end simulation tool EeteS, we performed a sensitivity analysis by comparing the retrieved values with the simulation input leading to an R-2 of 0.991 for water vapor and 0.965 for liquid water. Furthermore, we applied the algorithm to airborne AVIRIS-C data to demonstrate the ability to map snow/ice extent as well as to a CHRIS-PROBA dataset for which concurrent field measurements of canopy water content were available. The comparison between the retrievals and the ground measurements showed an overall R-2 of 0.80 for multiple crop types and a remarkable clustering in the regression analysis indicating a dependency of the retrieved water content from the physical structure of the vegetation. In addition, the algorithm is able to produce smoother and more physically-plausible water vapor maps than the ones from the band ratio approaches used for multispectral data, since biases due to background reflectance are reduced. The demonstrated potential of imaging spectroscopy to provide accurate quantitative measures of water from space will be further exploited using upcoming spaceborne imaging spectroscopy missions like PRISMA or EnMAP. es_ES
dc.description.sponsorship This study is funded within the EnMAP scientific preparation program under the DLR Space Administration with resources from the German Federal Ministry for Economic Affairs and Energy, Berlin, Germany (grant ID 59EE1923) and the Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Remote Sensing of Environment es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Imaging spectroscopy es_ES
dc.subject Atmospheric correction es_ES
dc.subject Water vapor es_ES
dc.subject Canopy water content es_ES
dc.subject EnMAP es_ES
dc.subject.classification FISICA APLICADA es_ES
dc.title Coupled retrieval of the three phases of water from spaceborne imaging spectroscopy measurements es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.rse.2020.111708 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/BMWI//59EE1923/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Telecomunicación - Escola Tècnica Superior d'Enginyers de Telecomunicació es_ES
dc.description.bibliographicCitation Bohn, N.; Guanter-Palomar, LM.; Kuester, T.; Preusker, R.; Segl, K. (2020). Coupled retrieval of the three phases of water from spaceborne imaging spectroscopy measurements. Remote Sensing of Environment. 242:1-16. https://doi.org/10.1016/j.rse.2020.111708 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.rse.2020.111708 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 16 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 242 es_ES
dc.relation.pasarela S\434481 es_ES
dc.contributor.funder Bundesministerium für Wirtschaft und Energie, Alemania es_ES
dc.contributor.funder Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ es_ES


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