Development of an AOTF-based hyperspectral imager for atmospheric remote sensing

This work addresses important aspects in the development of a new spaceborne instrument called ALTIUS. The imaging capability is first applied to the inversion of atmospheric pressure profiles from the analysis of the apparent flattening of a setting... Continuer

The evolution of atmospheric composition is a complex and living research area. Models need data on a global scale in order to follow, reproduce and forecast the spatio-temporal fields of key species and identify their contribution in the Earth radiative balance. In many aspects, the vertical distribution of these species is an important parameter. Unfortunately, the number of spaceborne sounders capable of providing such information is decreasing. Moreover, the instrumental concepts deployed so far suffer from tangent altitude registration issues. In the particular frame of ozone recovery, this causes large uncertainties compared to the small trends to be observed.
IASB-BIRA has proposed a new spaceborne instrument called ALTIUS. It is a full mission concept aiming at the acquisition of spectral images in limb-scattering and occultation geometries. The spectral selection is performed by an acoustooptical tunable filter (AOTF) and the PROBA-class satellite will offer good pointing control and manoeuvrability. Altogether, the measurement modes, the hyperspectral images, and the spacecraft performance will ensure low-uncertainty and high-vertical resolution geophysical products.
This work addresses important aspects in the development of ALTIUS. The imaging capability is first applied to the inversion of atmospheric pressure profiles from the analysis of the apparent flattening of a setting Sun. Then the spectral feature is added such that the simulation of limb-scattering measurements yield the final error budget of O3 and NO2 profiles. A complete description of the AOTF is also provided and the performance of two units operating in the UV and VIS ranges is examined in laboratory experiments. Finally, a prototype is used to demonstrate remote sensing capabilities with the detection of NO2 in industrial smokes.


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Spécifications


Éditeur
Presses universitaires de Louvain
Auteur
Emmanuel Dekemper,
Collection
Thèses de la Faculté des sciences
Langue
anglais
Catégorie (éditeur)
Sciences exactes > Physique > Astronomie et géophysique
Catégorie (éditeur)
Sciences exactes > Physique
Catégorie (éditeur)
Sciences exactes
BISAC Subject Heading
SCI005000 SCIENCE / Physics / Astrophysics
Code publique Onix
06 Professional and scholarly
CLIL (Version 2013 )
3058 Physique > 3067 Sciences de la terre (géologie, climatologie, hydrologie…)
Date de première publication du titre
07 novembre 2014

Livre broché


Details de produit
1 Reliure cousue
Date de publication
07 novembre 2014
ISBN-13
9782875583444
Ampleur
Nombre de pages de contenu principal : 198
Code interne
90676
Format
16 x 24 x 1,1 cm
Poids
324 grammes
Prix
26,00 €
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Sommaire


Remerciements v
List of acronyms ix
Introduction 1
1 Atmospheric remote sensing 5
1.1 Milestones in atmospheric experimentation . . . . . . . . 5
1.1.1 The in situ atmospheric measurements precursors 5
1.1.2 The advent of ground-based atmospheric remote
sensing . . . . . . . . . . . . . . . . . . . . . . . . 7
1.1.3 Spaceborne atmospheric instruments . . . . . . . . 9
1.2 Importance of vertically resolved information . . . . . . . 11
1.2.1 Stratospheric ozone trends . . . . . . . . . . . . . . 12
1.2.2 Dispersion of the measurements . . . . . . . . . . . 14
1.2.3 Spatio-temporal sampling bias . . . . . . . . . . . 15
1.2.4 Vertically-resolved data and atmospheric models . 16
1.3 The radiative transfer problem for limb scattering instruments
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1.3.1 The photon transport equation . . . . . . . . . . . 18
1.3.2 Rayleigh scattering phase function . . . . . . . . . 21
1.3.3 Rayleigh scattering cross-section . . . . . . . . . . 22
1.3.4 Transport equation in a purely Rayleigh scattering
atmosphere . . . . . . . . . . . . . . . . . . . . . . 23
1.3.5 Molecular absorption . . . . . . . . . . . . . . . . . 25
1.3.6 Radiative transfer equation for a single scattering
and absorbing atmosphere . . . . . . . . . . . . . . 25
1.3.7 Typical limb-scatter radiance profile . . . . . . . . 27
1.4 From radiance to concentration profiles: the inverse problem 29
2 Imaging and atmospheric remote sensing—The refracted
Sun case 35
2.1 Quantitative atmospheric information based on imaging
techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.2 Scope of the theoretical work: pressure profile retrieval
from the apparent flattening of the solar disk . . . . . . . 36
2.3 Sun image simulation . . . . . . . . . . . . . . . . . . . . 37
2.3.1 Virtual instrument definition . . . . . . . . . . . . 37
2.3.2 Solar limb darkening . . . . . . . . . . . . . . . . . 38
2.3.3 Atmospheric refractive index . . . . . . . . . . . . 39
2.3.4 1-D ray tracing problem . . . . . . . . . . . . . . . 39
2.3.5 2-D ray tracing problem . . . . . . . . . . . . . . . 41
2.4 Zernike moments . . . . . . . . . . . . . . . . . . . . . . . 44
2.5 Pressure profiles retrieval . . . . . . . . . . . . . . . . . . 46
2.5.1 Training dataset . . . . . . . . . . . . . . . . . . . 48
2.5.2 Test cases . . . . . . . . . . . . . . . . . . . . . . . 52
2.5.3 Impact of error sources . . . . . . . . . . . . . . . 57
2.6 Adequacy of the proposed method and future work . . . . 58
3 Spectral imaging and atmospheric remote sensing—The
ALTIUS mission 61
3.1 The pointing problem of atmospheric profiling instruments 61
3.1.1 Imaging as an answer to pointing uncertainty . . . 63
3.2 The ALTIUS concept . . . . . . . . . . . . . . . . . . . . . 64
3.3 Nominal orbit and measurement geometries . . . . . . . . 68
3.4 Synthetic limb-scatter radiance . . . . . . . . . . . . . . . 70
3.5 Major payload and platform requirements . . . . . . . . . 71
3.5.1 Signal-to-noise ratio . . . . . . . . . . . . . . . . . 73
3.5.2 Pointing error . . . . . . . . . . . . . . . . . . . . . 73
3.5.3 Wavelength misregistration . . . . . . . . . . . . . 74
3.6 O3 retrieval in bright limb . . . . . . . . . . . . . . . . . . 74
3.6.1 O3 measurements . . . . . . . . . . . . . . . . . . . 74
3.6.2 Measurement error . . . . . . . . . . . . . . . . . . 78
3.6.3 Statement of the inverse problem . . . . . . . . . . 79
3.6.4 Retrieved profile . . . . . . . . . . . . . . . . . . . 83
3.6.5 Vertical resolution . . . . . . . . . . . . . . . . . . 84
3.6.6 Pointing uncertainty . . . . . . . . . . . . . . . . . 86
3.6.7 Spectral uncertainty . . . . . . . . . . . . . . . . . 88
3.6.8 Final O3 retrieval performance budget . . . . . . . 89
3.7 NO2 retrieval in bright limb . . . . . . . . . . . . . . . . . 91
3.7.1 NO2 measurements . . . . . . . . . . . . . . . . . . 91
3.7.2 Statement of the inverse problem . . . . . . . . . . 93
3.7.3 Retrieved profile . . . . . . . . . . . . . . . . . . . 94
3.7.4 Pointing uncertainty . . . . . . . . . . . . . . . . . 96
3.7.5 Spectral uncertainty . . . . . . . . . . . . . . . . . 97
3.7.6 Final NO2 retrieval performance budget . . . . . . 97
4 Acousto-optical tunable filters 99
4.1 Foundations . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4.2 Theoretical background . . . . . . . . . . . . . . . . . . . 100
4.2.1 Optical waves in birefringent crystals . . . . . . . . 100
4.2.2 Acoustic waves in crystals . . . . . . . . . . . . . . 103
4.2.3 Elasto-optic effect and coupled wave equations . . 105
4.2.4 Basic AOTF parameters . . . . . . . . . . . . . . . 109
4.3 Application to NO2 absorption cross-section measurement 121
4.3.1 Commercial TeO2 AOTF . . . . . . . . . . . . . . 122
4.3.2 Experimental setup . . . . . . . . . . . . . . . . . . 123
4.3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . 124
4.4 KDP-based AOTF for hyperspectral imaging in UV . . . 125
4.4.1 Main AOTF parameters . . . . . . . . . . . . . . . 126
4.4.2 Temperature dependence . . . . . . . . . . . . . . 131
5 AOTF-based hyperspectral imager — Application to the
remote sensing of NO2 in industrial smokes 137
5.1 Instrument description . . . . . . . . . . . . . . . . . . . . 138
5.2 Smokestack experiment . . . . . . . . . . . . . . . . . . . 140
5.2.1 Experimental conditions . . . . . . . . . . . . . . . 140
5.2.2 Measurement principle . . . . . . . . . . . . . . . . 142
5.2.3 Data acquisition and correction . . . . . . . . . . . 144
5.2.4 Results . . . . . . . . . . . . . . . . . . . . . . . . 146
Conclusion and future research 151
A Error covariance of limb-scatter measurements 155
A.1 Limb scattering measurement uncertainty . . . . . . . . . 156
A.2 Image ratio covariance . . . . . . . . . . . . . . . . . . . . 157
B The MAP log-normally distributed solution 161
C Acousto-optic interaction and polarization aspects 163
Bibliography 169


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