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Remote Sens. 2018, 10(6), 976; https://doi.org/10.3390/rs10060976

Physical Retrieval of Land Surface Emissivity Spectra from Hyper-Spectral Infrared Observations and Validation with In Situ Measurements

1
School of Engineering, University of Basilicata, Viale Ateneo Lucano, 10, 85100 Potenza, Italy
2
NASA Goddard Space Flight Center, 8800 Greenbelt Rd, Greenbelt, MD 20771, USA
3
ONERA, The French Aerospace Lab, 2 avenue Edouard Belin, FR-31055 Toulouse, France
4
IMK-ASF, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
*
Author to whom correspondence should be addressed.
Received: 17 May 2018 / Revised: 8 June 2018 / Accepted: 14 June 2018 / Published: 20 June 2018
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Abstract

A fully physical retrieval scheme for land surface emissivity spectra is presented, which applies to high spectral resolution infrared observations from satellite sensors. The surface emissivity spectrum is represented with a suitably truncated Principal Component Analysis (PCA) transform and PCA scores are simultaneously retrieved with surface temperature and atmospheric parameters. The retrieval methodology has been developed within the general framework of Optimal Estimation and, in this context, is the first physical scheme based on a PCA representation of the emissivity spectrum. The scheme has been applied to IASI (Infrared Atmospheric Sounder Interferometer) and the retrieved emissivities have been validated with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. It has been found that the retrieved emissivity spectra are independent of background information and in good agreement with in situ observations. View Full-Text
Keywords: emissivity spectrum; infrared; satellite; optimal estimation validation emissivity spectrum; infrared; satellite; optimal estimation validation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Masiello, G.; Serio, C.; Venafra, S.; Liuzzi, G.; Poutier, L.; Göttsche, F.-M. Physical Retrieval of Land Surface Emissivity Spectra from Hyper-Spectral Infrared Observations and Validation with In Situ Measurements. Remote Sens. 2018, 10, 976.

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