Martian aerosol abundance estimation based on unmixing of hyperspectral imagery

International audienceClassical linear unmixing approaches are not valid if the atmosphere and the aerosol are present in hyperspectral data, since the mixture model is no longer linear. In this paper, we present an iterative approach for estimating the abundance of aerosol based on unmixing of Martian hyperspectral data. On one hand, the results can provide the information on the aerosol of the Mars, which is very difficult to obtain. On the other hand, we can use the result to remove the effect of the aerosol on the original image and obtain more accurate linear unmixing results on the surface reflectance

Mineral identification using data-mining in hyperspectral infrared imagery

Les applications de l’imagerie infrarouge dans le domaine de la géologie sont principalement des applications hyperspectrales. Elles permettent entre autre l’identification minérale, la cartographie, ainsi que l’estimation de la portée. Le plus souvent, ces acquisitions sont réalisées in-situ soit à l’aide de capteurs aéroportés, soit à l’aide de dispositifs portatifs. La découverte de minéraux indicateurs a permis d’améliorer grandement l’exploration minérale. Ceci est en partie dû à l’utilisation d’instruments portatifs. Dans ce contexte le développement de systèmes automatisés permettrait d’augmenter à la fois la qualité de l’exploration et la précision de la détection des indicateurs. C’est dans ce cadre que s’inscrit le travail mené dans ce doctorat. Le sujet consistait en l’utilisation de méthodes d’apprentissage automatique appliquées à l’analyse (au traitement) d’images hyperspectrales prises dans les longueurs d’onde infrarouge. L’objectif recherché étant l’identification de grains minéraux de petites tailles utilisés comme indicateurs minéral -ogiques. Une application potentielle de cette recherche serait le développement d’un outil logiciel d’assistance pour l’analyse des échantillons lors de l’exploration minérale. Les expériences ont été menées en laboratoire dans la gamme relative à l’infrarouge thermique (Long Wave InfraRed, LWIR) de 7.7m à 11.8 m. Ces essais ont permis de proposer une méthode pour calculer l’annulation du continuum. La méthode utilisée lors de ces essais utilise la factorisation matricielle non négative (NMF). En utlisant une factorisation du premier ordre on peut déduire le rayonnement de pénétration, lequel peut ensuite être comparé et analysé par rapport à d’autres méthodes plus communes. L’analyse des résultats spectraux en comparaison avec plusieurs bibliothèques existantes de données a permis de mettre en évidence la suppression du continuum. Les expérience ayant menés à ce résultat ont été conduites en utilisant une plaque Infragold ainsi qu’un objectif macro LWIR. L’identification automatique de grains de différents matériaux tels que la pyrope, l’olivine et le quartz a commencé. Lors d’une phase de comparaison entre des approches supervisées et non supervisées, cette dernière s’est montrée plus approprié en raison du comportement indépendant par rapport à l’étape d’entraînement. Afin de confirmer la qualité de ces résultats quatre expériences ont été menées. Lors d’une première expérience deux algorithmes ont été évalués pour application de regroupements en utilisant l’approche FCC (False Colour Composite). Cet essai a permis d’observer une vitesse de convergence, jusqu’a vingt fois plus rapide, ainsi qu’une efficacité significativement accrue concernant l’identification en comparaison des résultats de la littérature. Cependant des essais effectués sur des données LWIR ont montré un manque de prédiction de la surface du grain lorsque les grains étaient irréguliers avec présence d’agrégats minéraux. La seconde expérience a consisté, en une analyse quantitaive comparative entre deux bases de données de Ground Truth (GT), nommée rigid-GT et observed-GT (rigide-GT: étiquet manuel de la région, observée-GT:étiquetage manuel les pixels). La précision des résultats était 1.5 fois meilleur lorsque l’on a utlisé la base de données observed-GT que rigid-GT. Pour les deux dernières epxérience, des données venant d’un MEB (Microscope Électronique à Balayage) ainsi que d’un microscopie à fluorescence (XRF) ont été ajoutées. Ces données ont permis d’introduire des informations relatives tant aux agrégats minéraux qu’à la surface des grains. Les résultats ont été comparés par des techniques d’identification automatique des minéraux, utilisant ArcGIS. Cette dernière a montré une performance prometteuse quand à l’identification automatique et à aussi été utilisée pour la GT de validation. Dans l’ensemble, les quatre méthodes de cette thèse représentent des méthodologies bénéfiques pour l’identification des minéraux. Ces méthodes présentent l’avantage d’être non-destructives, relativement précises et d’avoir un faible coût en temps calcul ce qui pourrait les qualifier pour être utilisée dans des conditions de laboratoire ou sur le terrain.The geological applications of hyperspectral infrared imagery mainly consist in mineral identification, mapping, airborne or portable instruments, and core logging. Finding the mineral indicators offer considerable benefits in terms of mineralogy and mineral exploration which usually involves application of portable instrument and core logging. Moreover, faster and more mechanized systems development increases the precision of identifying mineral indicators and avoid any possible mis-classification. Therefore, the objective of this thesis was to create a tool to using hyperspectral infrared imagery and process the data through image analysis and machine learning methods to identify small size mineral grains used as mineral indicators. This system would be applied for different circumstances to provide an assistant for geological analysis and mineralogy exploration. The experiments were conducted in laboratory conditions in the long-wave infrared (7.7μm to 11.8μm - LWIR), with a LWIR-macro lens (to improve spatial resolution), an Infragold plate, and a heating source. The process began with a method to calculate the continuum removal. The approach is the application of Non-negative Matrix Factorization (NMF) to extract Rank-1 NMF and estimate the down-welling radiance and then compare it with other conventional methods. The results indicate successful suppression of the continuum from the spectra and enable the spectra to be compared with spectral libraries. Afterwards, to have an automated system, supervised and unsupervised approaches have been tested for identification of pyrope, olivine and quartz grains. The results indicated that the unsupervised approach was more suitable due to independent behavior against training stage. Once these results obtained, two algorithms were tested to create False Color Composites (FCC) applying a clustering approach. The results of this comparison indicate significant computational efficiency (more than 20 times faster) and promising performance for mineral identification. Finally, the reliability of the automated LWIR hyperspectral infrared mineral identification has been tested and the difficulty for identification of the irregular grain’s surface along with the mineral aggregates has been verified. The results were compared to two different Ground Truth(GT) (i.e. rigid-GT and observed-GT) for quantitative calculation. Observed-GT increased the accuracy up to 1.5 times than rigid-GT. The samples were also examined by Micro X-ray Fluorescence (XRF) and Scanning Electron Microscope (SEM) in order to retrieve information for the mineral aggregates and the grain’s surface (biotite, epidote, goethite, diopside, smithsonite, tourmaline, kyanite, scheelite, pyrope, olivine, and quartz). The results of XRF imagery compared with automatic mineral identification techniques, using ArcGIS, and represented a promising performance for automatic identification and have been used for GT validation. In overall, the four methods (i.e. 1.Continuum removal methods; 2. Classification or clustering methods for mineral identification; 3. Two algorithms for clustering of mineral spectra; 4. Reliability verification) in this thesis represent beneficial methodologies to identify minerals. These methods have the advantages to be a non-destructive, relatively accurate and have low computational complexity that might be used to identify and assess mineral grains in the laboratory conditions or in the field

Visible and Near Infrared imaging spectroscopy and the exploration of small scale hydrothermally altered and hydrated environments on Earth and Mars

The use of Visible and Near Infrared (VNIR) imaging spectroscopy is a cornerstone of planetary exploration. This work shall present an investigation into the limitations of scale, both spectral and spatial, in the utility of VNIR images for identifying small scale hydrothermal and potential hydrated environments on Mars, and regions of the Earth that can serve as martian analogues. Such settings represent possible habitable environments; important locations for astrobiological research. The ESA/Roscosmos ExoMars rover PanCam captures spectrally coarse but spatially high resolution VNIR images. This instrument is still in development and the first field trial of an emulator fitted with the final set of geological filters is presented here. Efficient image analysis techniques are explored and the ability to accurately characterise a hydrothermally altered region using PanCam data products is established. The CRISM orbital instrument has been returning hyperspectral VNIR images with an 18 m2 pixel resolution since 2006. The extraction of sub-pixel information from CRISM pixels using Spectral Mixture Analysis (SMA) algorithms is explored. Using synthetic datasets a full SMA pipeline consisting of publically available Matlab algorithms and optimised for investigation of mineralogically complex hydrothermal suites is developed for the first time. This is validated using data from Námafjall in Iceland, the region used to field trial the PanCam prototype. The pipeline is applied to CRISM images covering four regions on Mars identified as having potentially undergone hydrothermal alteration in their past. A second novel use of SMA to extract a unique spectral signature for the potentially hydrated Recurring Slope Lineae features on Mars is presented. The specific methodology presented shows promise and future improvements are suggested. The importance of combining different scales of data and recognising their limitations is discussed based on the results presented and ways in which to take the results presented in this thesis forward are given

Water ice in the dark dune spots of Richardson crater on Mars

In this study we assess the presence, nature and properties of ices - in particular water ice - that occur within these spots using HIRISE and CRISM observations, as well as the LMD Global Climate Model. Our studies focus on Richardson crater (72{\deg}S, 179{\deg}E) and cover southern spring and summer (LS 175{\deg} - 17 341{\deg}). Three units have been identified of these spots: dark core, gray ring and bright halo. Each unit show characteristic changes as the season progress. In winter, the whole area is covered by CO2 ice with H2O ice contamination. Dark spots form during late winter and early spring. During spring, the dark spots are located in a 10 cm thick depression compared to the surrounding bright ice-rich layer. They are spectrally characterized by weak CO2 ice signatures that probably result from spatial mixing of CO2 ice rich and ice free regions within pixels, and from mixing of surface signatures due to aerosols scattering. The bright halo shaped by winds shows stronger CO2 absorptions than the average ice covered terrain, which is consistent with a formation process involving CO2 re-condensation. According to spectral, morphological and modeling considerations, the gray ring is composed of a thin layer of a few tens of {\mu}m of water ice. Two sources/processes could participate to the enrichment of water ice in the gray ring unit: (i) water ice condensation at the surface in early fall (prior to the condensation of a CO2 rich winter layer) or during winter time (due to cold trapping of the CO2 layer); (ii) ejection of dust grains surrounded by water ice by the geyser activity responsible for the dark spot. In any case, water ice remains longer in the gray ring unit after the complete sublimation of the CO2. Finally, we also looked for liquid water in the near-IR CRISM spectra using linear unmixing modeling but found no conclusive evidence for it

Visible and Near Infrared imaging spectroscopy and the exploration of small scale hydrothermally altered and hydrated environments on Earth and Mars

The use of Visible and Near Infrared (VNIR) imaging spectroscopy is a cornerstone of planetary exploration. This work shall present an investigation into the limitations of scale, both spectral and spatial, in the utility of VNIR images for identifying small scale hydrothermal and potential hydrated environments on Mars, and regions of the Earth that can serve as martian analogues. Such settings represent possible habitable environments; important locations for astrobiological research. The ESA/Roscosmos ExoMars rover PanCam captures spectrally coarse but spatially high resolution VNIR images. This instrument is still in development and the first field trial of an emulator fitted with the final set of geological filters is presented here. Efficient image analysis techniques are explored and the ability to accurately characterise a hydrothermally altered region using PanCam data products is established. The CRISM orbital instrument has been returning hyperspectral VNIR images with an 18 m2 pixel resolution since 2006. The extraction of sub-pixel information from CRISM pixels using Spectral Mixture Analysis (SMA) algorithms is explored. Using synthetic datasets a full SMA pipeline consisting of publically available Matlab algorithms and optimised for investigation of mineralogically complex hydrothermal suites is developed for the first time. This is validated using data from Námafjall in Iceland, the region used to field trial the PanCam prototype. The pipeline is applied to CRISM images covering four regions on Mars identified as having potentially undergone hydrothermal alteration in their past. A second novel use of SMA to extract a unique spectral signature for the potentially hydrated Recurring Slope Lineae features on Mars is presented. The specific methodology presented shows promise and future improvements are suggested. The importance of combining different scales of data and recognising their limitations is discussed based on the results presented and ways in which to take the results presented in this thesis forward are given

Hyperspectral unmixing: a theoretical aspect and applications to CRISM data processing

Hyperspectral imaging has been deployed in earth and planetary remote sensing, and has contributed the development of new methods for monitoring the earth environment and new discoveries in planetary science. It has given scientists and engineers a new way to observe the surface of earth and planetary bodies by measuring the spectroscopic spectrum at a pixel scale. Hyperspectal images require complex processing before practical use. One of the important goals of hyperspectral imaging is to obtain the images of reflectance spectrum. A raw image obtained by hyperspectral remote sensing usually undergoes conversion to a physical quantity representing the intensity of light energy, called radiance. In order to obtain the reflectance spectrum of surface, the contribution of atmosphere needs to be addressed and then divided by a spectrum of ``white reference.\u27\u27 Furthermore, the obtained reflectance spectra of image pixels are likely to be the mixtures of multiple species due to limited spatial resolution from orbits around planets. Hyperspectral unmixing is an attempt to unmix those pixels - to identify substantial components and estimate their fractional abundances. Hyperspectral unmixing has been widely explored in the literature, but there are still many aspects yet to be studied. The majority of research focuses on the development of methods to retrieve correct substantial components and accurate fractional abundances. Their theoretical aspects are rarely investigated. Chapter 2 will pursue a theoretical aspect of sparse unmixing, one of the hyperspectral unmixing problems and derive its theoretical conditions that guarantee the correct identification of substantial components. Hyperspectral unmixing can also be used for other stages of hyperspectral data processing. Chapter 3 explores the application of hyperspectral unmixing to the processing of hyperspectral image acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) onboard the Mars Reconnaissance Orbiter (MRO). In particular, new atmospheric correction and de-noising methods for the CRISM data that use a hyperspectral unmixing to model surface spectra, are introduced. The new methods remove most of the problematic systematic artifacts present in CRISM images and significantly improve signal quality. Chapter 4 investigates how hyperspectral images acquired from orbits can be combined with ground exploration. In the recent rush of the launch of many Martian ground rover missions, it is important to effectively integrate knowledge obtained by hyperspectral remote sensing from orbits into ground exploration for facilitating Martian exploration. In specific, this dissertation solves the problem of matching hyperspectral image pixels obtained by the CRISM with ground mega-pixel images acquired by the Mast Camera (Mastcam) installed on the Curiosity rover on Mars. A new systematic methodology to map the CRISM and Mastcam images onto high resolution surface topography is developed

Etude morphologique de la formation des ravines sur les dunes martiennes (approche comparative Terre/Mars.)

L histoire géologique récente de Mars reste peu étudiée, comparativement à l histoire primitive de Mars (>3,5 Ga). Cependant, l arrivée de nouvelles images haute résolution a permis d identifier la présence de ravines à la surface de terrains très récents. Dans ce travail, nous nous sommes attaché à caractériser la morphologie des ravines et les processus qui les ont générés. Ces nouvelles observations relancent la question de la présence d eau liquide actuellement à la surface de Mars que ce soit à l état pur ou sous forme de mélange (saumure, coulée de débris...). Des simulations expérimentales en chambre froide à la pression atmosphérique de Mars et de la Terre ont été menées. Elles ont notamment permis de quantifier le rôle de la teneur en eau dans la couche active du pergélisol sur le mécanisme de formation des ravines et leur mobilité. Nous avons également décrit l évolution saisonnière de petits réseaux ramifiés qui se sont développés chaque année au printemps durant la période 2007-2012.The recent geological history of Mars remains poorly studied, in comparison to theearly history of Mars (>3,5 Ga). However, the acquisition of new high-resolution imagesallowed to identified the presence of gullies on the surface of recent landforms such asdunes. In this work, we focused on characterizing the morphology of gullies and theirprocess(es) of formation. These new observations revive the issue of the presence of liquid water present on the surface of Mars than either pure or as a mixture (brine, debris flow ...). Experimental simulations in a cold room at Martian and terrestrial atmospheric pressure have been conducted. In particular, they allowed us to quantify the role of water content in the active layer of the permafrost in order to better constrain the mechanism of formation of gullies and their motion. We also described the seasonal evolution of small branched networks developed at spring during the 2007-2012 period.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

An evaluation of Multiple Endmember Spectral Mixture Analysis applied to Landsat 8 OLI images for mapping land cover in southern Africa\u27s Savanna.

Mapping land cover in southern Africa’s savannas using traditional pixel based remote sensing techniques can be very challenging due to the heterogeneity of its vegetation structure and the spectral difficulty in separating similar land covers across various land uses. In order to overcome these complications, a Multiple Endmember Spectral Mixture Analysis (MESMA) provides a potential remote sensing approach to quantify spectral variation in the physical environment at a subpixel level. The MESMA approach was applied in the study area of the Mayuni Conservancy, in Namibia. Results show that 32.3% of the study area is covered by photosynthetic vegetation (PV), 32.0% by non-photosynthetic vegetation (NPV), 25.2% by bare soil (B) and 10.6% by shade. Post-classification validation shows that MESMA presented a moderate performance in estimating the proportions of land cover types in the study area. However the validation process is limited to the available resources and carries great subjectivity. It is concluded that future research on the matter should include a more consistent investigation on the endmember selection methodology and expand the study area inside of the same ecosystem