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

Guido Masiello,Carmine Serio,Giuliano Liuzzi,Sara Venafra,Laurent Poutier,Frank-M Göttsche

doi:10.3390/rs10060976

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.

Highlights

The problem of retrieving surface emissivity from infrared spectral observations is mainly that of separating it from temperature in the surface radiation emission: this is is commonly referred to as Ts − ε (Temperature-Emissivity) separation.Within the framework of high spectral resolution infrared observations from air planes and satellites, the problem has been addressed by [3,4], who arrived at a closed form, in which emissivity is separated from surface temperature and atmospheric emission by using the radiation reflected at the surface, which under a Lambertian model depends on emissivity alone
The dimensionality issue has been handled by representing the emissivity spectrum with a truncated PC transform with twenty Principal Component Analysis (PCA) coefficients
The PCA orthogonal basis was obtained from a set of laboratory measurements and the methodology was applied to IASI and a set of soundings over Gobabeb validation station (Namib desert), which was used to check the accuracy and sensitivity of the methodology

Summary

Introduction

The problem of retrieving surface emissivity from infrared spectral observations is mainly that of separating it from temperature in the surface radiation emission: this is is commonly referred to as Ts − ε (Temperature-Emissivity) separation (e.g., see [1,2] and references therein).Within the framework of high spectral resolution infrared observations from air planes and satellites, the problem has been addressed by [3,4], who arrived at a closed form, in which emissivity is separated from surface temperature and atmospheric emission by using the radiation reflected at the surface, which under a Lambertian model depends on emissivity alone. Similar approaches have been considered in previous studies from aircraft, ship and in situ observations of spectral radiance, usually acquired with Fourier Transform Spectrometers [5,6,7,8]. All of these methods inevitably assume that the atmospheric state is known from independent sources, whereas the methodology we describe and demonstrate, simultaneously retrieves surface and atmospheric parameters from spectral information contained in the earth emission spectrum

Methods

Results

Conclusion