Etude de l'activation et de l'inactivation pH-dépendantes des canaux ASICs (Acide-Sensing Ion Channels)

RESUME: Etude de l'activation et de l'inactivation pH-dépendantes des canaux ASICs (Acid-Sensing Ion Channels) Benoîte BARGETON, Département de Pharmacologie et de Toxicologie, Université de Lausanne, rue du Bugnon 27, CH-1005 Lausanne, Suisse Les canaux sodiques ASICs (Acid-Sensing Ion Channels) participent à la signalisation neuronale dans les systèmes nerveux périphérique et central. Ces canaux non voltage dépendants sont impliqués dans l'apprentissage, l'expression de la peur, la neurodégénération consécutive à une attaque cérébrale et la douleur. Les bases moléculaires sous-tendant leur activité ne sont pas encore totalement comprises. Ces canaux sont activés par une acidification du milieu extracellulaire et régulés, entre autres, par des ions tels que le Ca2+, le Zn2+ et le CI". La cristallisation de ASIC inactivé a été publiée. Le canal est un trimére de sous-unités identiques ou homologues. Chaque sous-unité a été décrite en analogie à un avant bras, un poignet et une main constituée d'un pouce, d'un doigt, d'une articulation, une boule β et une paume. Nous avons appliqué une approche bioinformatique systématique pour identifier les pH senseurs putatifs de ASICIa. Le rôle des pH senseurs putatifs a été testé par mutagénèse dirigée et des modifications chimiques combinées à une analyse fonctionnelle afin de comprendre comment les variations de ρ H ouvrent ces canaux. Les pH senseurs sont des acides aspartiques et glutamiques éparpillés sur la boucle extracellulaire suggérant que les changements de pH contrôlent l'activation et l'inactivation de ASIC en (dé)protonant ces résidus en divers endroits de la protéine. Par exemple lors de l'activation, la protonation des résidus à l'interface entre le pouce, la boule β et le doigt d'une même sous-unité induit un mouvement du pouce vers la bouie β et le doigt. De même lors de l'inactivation du canal les paumes des trois sous-unités formant une cavité se rapprochent. D'après notre approche bioinformatique, aucune histidine n'est impliquée dans la détection des variations de pH extracellulaire c'est-à-dire qu'aucune histidine ne serait un pH-senseur. Deux histidines de ASIC2a lient le Zn2+ et modifient l'affinité apparente du canal pour les protons. Une seule des deux est conservée parmi tous les ASICs, hASICIa H163. Elle forme un réseau de liaison hydrogène avec ses voisins conservés. L'étude détaillée de ce domaine, Pinterzone, montre son importance dans l'expression fonctionnelle des canaux. La perturbation de ce réseau par l'introduction d'un résidu hydrophobe (cystéine) par mutagénèse dirigée diminue l'expression du canal à la membrane plasmique. La modification des cystéines introduites par des réactifs spécifiques aux groupements sulfhydryle inhibe les canaux mutés en diminuant leur probabilité d'ouverture. Ces travaux décrivent les effets de l'acidification du milieu extracellulaire sur les canaux ASICs. ABSTRACT: Study of pH-dependent activation and inactivation of ASIC channels Benoîte BARGETON, Department of Pharmacology and Toxicology, University of Lausanne, Rue du Bugnon 27, CH-1G05 Lausanne, Switzerland The ASIC (Acid-Sensing Ion Channels) sodium channels are involved in neuronal signaling in the central and peripheral nervous system. These non-voltage-gated channels are involved in learning, the expression of fear, neurodegeneration after ischemia and pain sensation. The molecular bases underlying their activity are not yet fully understood. ASICs are activated by extracellular acidification and regulated, eg by ions such as Ca2+, the Zn2+ and CI". The crystallization of inactivated ASIC has been published. The channel is a trimer of identical or homologous subunits. Each subunit has been described in analogy to a forearm, wrist and hand consisting of a thumb, a finger, a knuckle, a β-ball and a palm. We applied a systematic computational approach to identify putative pH sensor(s) of ASICIa. The role of putative pH sensors has been tested by site-directed mutagenesis and chemical modification combined with functional analysis in order to understand how changes in pH open these channels. The pH sensors are aspartic and glutamic acids distributed throughout the extracellular loop, suggesting that changes in pH control activation and inactivation of ASIC by protonation / deprotonation of many residues in different parts of the protein. During activation the protonation of various residues at the interface between the finger, the thumb and the β-ball induces the movement of the thumb toward the finger and the β-ball. During inactivation of the channel the palms of the three subunits forming a cavity approach each other. No histidine has been shown to be involved in extracellular pH changes detection, i.e. no histidine is a pH- sensor. Two histidines of ASIC2 bind Zn2+ and alter the apparent affinity of channel for protons. Only one of the two His is conserved among all ASICs, hASICIa H163. This residue is part of a network of hydrogen bonding with its conserved neighbors. The detailed study of this area, the interzone, shows its importance in the functional expression of ASICs. Disturbance of this network by the introduction of hydrophobic residues decreases the cell surface channel expression. Chemical modification of the introduced cysteines by thiol reactive compounds inhibits the mutated channels by a reduction of their open probability. These studies describe the effects of extracellular acidification on ASICs. RESUME GRAND PUBLIC: Etude de l'activation et de l'inactivation pH-dépendantes des canaux ASICs (Acid-Sensing Ion Channels) Benoîte BARGETON, Département de Pharmacologie et de Toxicologie, Université de Lausanne, rue du Bugnon 27, CH-1005 Lausanne, Suisse La transmission synaptique est un processus chimique entre deux neurones impliquant des neurotransmetteurs et leurs récepteurs. Un dysfonctionnement de certains types de synapses est à l'origine de beaucoup de troubles nerveux, tels que certaine forme d'épilepsie et de l'attention. Les récepteurs des neurotransmetteurs sont de très bonnes cibles thérapeutiques dans de nombreuses neuropathologies. Les canaux ASICs sont impliqués dans la neurodégénération consécutive à une attaque cérébrale et les bloquer pourraient permettre aux patients d'avoir moins de séquelles. Les canaux ASICs sont des détecteurs de l'acidité qui apparaît lors de situations pathologiques comme l'ischémie et l'inflammation. Ces canaux sont également impliqués dans des douleurs. Cibler spécifiquement ces canaux permettrait d'avoir de nouveaux outils thérapeutiques car à l'heure actuelle l'inhibiteur de choix, l'amiloride, bloque beaucoup d'autres canaux empêchant son utilisation pour bloquer les ASICs. C'est pourquoi il faut connaître et comprendre les bases moléculaires du fonctionnement de ces récepteurs. Les ASICs formés de trois sous-unités détectent les variations de l'acidité puis s'ouvrent transitoirement pour laisser entrer des ions chargés positivement dans la cellule ce qui active la signalisation neuronale. Afin de comprendre les bases moléculaires de l'activité des ASICs nous avons déterminé les sites de liaison des protons (pH-senseurs), ligands naturels des ASICs et décrit une zone importante pour l'expression fonctionnelle de ces canaux. Grâce à une validation systématique de résultats obtenus en collaboration avec l'Institut Suisse de Bioinformatique, nous avons décrit les pH-senseurs de ASICIa. Ces résultats, combinés à ceux d'autres groupes de recherche, nous ont permis de mieux comprendre comment les ASICs sont ouverts par une acidification du milieu extracellulaire. Une seconde étude souligne le rôle structural crucial d'une région conservée parmi tous les canaux ASICs : y toucher c'est diminuer l'activité de la protéine. Ce domaine permet l'harmonisation des changements dus à l'acidification du milieu extracellulaire au sein d'une même sous-unité c'est-à-dire qu'elle participe à l'induction de l'inactivation due à l'activation du canal Cette étude décrit donc quelle région de la protéine atteindre pour la bloquer efficacement en faisant une cible thérapeutique de choix.

Structural and gas-sensing properties of WO3 nanocrystalline powders obtained by a sol-gel method from tungstic acid

WO3 nanocrystalline powders were obtained from tungstic acid following a sol-gel process. Evolution of structural properties with annealing temperature was studied by X-ray diffraction and Raman spectroscopy. These structural properties were compared with those of WO3 nanopowders obtained by the most common process of pyrolysis of ammonium paratungstate, usually used in gas sensors applications. Sol-gel WO3 showed a high sensor response to NO2 and low response to CO and CH4. The response of these sensor devices was compared with that of WO3 obtained from pyrolysis, showing the latter a worse sensor response to NO2. Influence of operating temperature, humidity, and film thickness on NO2 detection was studied in order to improve the sensing conditions to this gas.

Gas-sensing properties of sprayed films of (CdO)x(ZnO)1-x mixed oxide

A novel NO2 sensor based on (CdO)x(ZnO)1-x mixed-oxide thin films deposited by the spray pyrolysis technique is developed. The sensor response to 3-ppm NO2 is studied in the range 50°C-350°C for three different film compositions. The device is also tested for other harmful gases, such as CO (300 ppm) and CH4 (3000 ppm). The sensor response to these reducing gases is different at different temperatures varying from the response typical for the p-type semiconductor to that typical for the n-type semiconductor. Satisfactory response to NO2 and dynamic behavior at 230°C, as well as low resistivity, are observed for the mixed-oxide film with 30% Cd. The response to interfering gas is poor at working temperature (230°C). On the basis of this study, a possible sensing mechanism is proposed.

Gas sensing properties of catalytically modified WO3 with copper and vanadium for NH3 detection

Ammonia gas detection by pure and catalytically modified WO3 based gas sensor was analysed. The sensor response of pure WO3 to NH3 was not only rather low but also presented an abnormal behaviour, probably due to the unselective oxidation of ammonia to NOx. Copper and vanadium were introduced in different concentrations and the resulting material was annealed at different temperatures in order to improve the sensing properties for NH3 detection. The introduction of copper and vanadium as catalytic additives improved the response to NH3 and also eliminated the abnormal behaviour. Possible mechanisms of NH3 reaction over these materials are discussed. Sensor responses to other gases like NO2 or CO and the interference of humidity on ammonia detection were also analysed so as to choose the best sensing element.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

Characterization of gravitational rock slope deformations at different spatial scales based on field, remote sensing and numerical approaches

Rock slope instabilities such as rock slides, rock avalanche or deep-seated gravitational slope deformations are widespread in Alpine valleys. These phenomena represent at the same time a main factor that control the mountain belts erosion and also a significant natural hazard that creates important losses to the mountain communities. However, the potential geometrical and dynamic connections linking outcrop and slope-scale instabilities are often unknown. A more detailed definition of the potential links will be essential to improve the comprehension of the destabilization processes and to dispose of a more complete hazard characterization of the rock instabilities at different spatial scales. In order to propose an integrated approach in the study of the rock slope instabilities, three main themes were analysed in this PhD thesis: (1) the inventory and the spatial distribution of rock slope deformations at regional scale and their influence on the landscape evolution, (2) the influence of brittle and ductile tectonic structures on rock slope instabilities development and (3) the characterization of hazard posed by potential rock slope instabilities through the development of conceptual instability models. To prose and integrated approach for the analyses of these topics, several techniques were adopted. In particular, high resolution digital elevation models revealed to be fundamental tools that were employed during the different stages of the rock slope instability assessment. A special attention was spent in the application of digital elevation model for detailed geometrical modelling of past and potential instabilities and for the rock slope monitoring at different spatial scales. Detailed field analyses and numerical models were performed to complete and verify the remote sensing approach. In the first part of this thesis, large slope instabilities in Rhone valley (Switzerland) were mapped in order to dispose of a first overview of tectonic and climatic factors influencing their distribution and their characteristics. Our analyses demonstrate the key influence of neotectonic activity and the glacial conditioning on the spatial distribution of the rock slope deformations. Besides, the volumes of rock instabilities identified along the main Rhone valley, were then used to propose the first estimate of the postglacial denudation and filling of the Rhone valley associated to large gravitational movements. In the second part of the thesis, detailed structural analyses of the Frank slide and the Sierre rock avalanche were performed to characterize the influence of brittle and ductile tectonic structures on the geometry and on the failure mechanism of large instabilities. Our observations indicated that the geometric characteristics and the variation of the rock mass quality associated to ductile tectonic structures, that are often ignored landslide study, represent important factors that can drastically influence the extension and the failure mechanism of rock slope instabilities. In the last part of the thesis, the failure mechanisms and the hazard associated to five potential instabilities were analysed in detail. These case studies clearly highlighted the importance to incorporate different analyses and monitoring techniques to dispose of reliable and hazard scenarios. This information associated to the development of a conceptual instability model represents the primary data for an integrated risk management of rock slope instabilities. - Les mouvements de versant tels que les chutes de blocs, les éboulements ou encore les phénomènes plus lents comme les déformations gravitaires profondes de versant représentent des manifestations courantes en régions montagneuses. Les mouvements de versant sont à la fois un des facteurs principaux contrôlant la destruction progressive des chaines orogéniques mais aussi un danger naturel concret qui peut provoquer des dommages importants. Pourtant, les phénomènes gravitaires sont rarement analysés dans leur globalité et les rapports géométriques et mécaniques qui lient les instabilités à l'échelle du versant aux instabilités locales restent encore mal définis. Une meilleure caractérisation de ces liens pourrait pourtant représenter un apport substantiel dans la compréhension des processus de déstabilisation des versants et améliorer la caractérisation des dangers gravitaires à toutes les échelles spatiales. Dans le but de proposer un approche plus globale à la problématique des mouvements gravitaires, ce travail de thèse propose trois axes de recherche principaux: (1) l'inventaire et l'analyse de la distribution spatiale des grandes instabilités rocheuses à l'échelle régionale, (2) l'analyse des structures tectoniques cassantes et ductiles en relation avec les mécanismes de rupture des grandes instabilités rocheuses et (3) la caractérisation des aléas rocheux par une approche multidisciplinaire visant à développer un modèle conceptuel de l'instabilité et une meilleure appréciation du danger . Pour analyser les différentes problématiques traitées dans cette thèse, différentes techniques ont été utilisées. En particulier, le modèle numérique de terrain s'est révélé être un outil indispensable pour la majorité des analyses effectuées, en partant de l'identification de l'instabilité jusqu'au suivi des mouvements. Les analyses de terrain et des modélisations numériques ont ensuite permis de compléter les informations issues du modèle numérique de terrain. Dans la première partie de cette thèse, les mouvements gravitaires rocheux dans la vallée du Rhône (Suisse) ont été cartographiés pour étudier leur répartition en fonction des variables géologiques et morphologiques régionales. En particulier, les analyses ont mis en évidence l'influence de l'activité néotectonique et des phases glaciaires sur la distribution des zones à forte densité d'instabilités rocheuses. Les volumes des instabilités rocheuses identifiées le long de la vallée principale ont été ensuite utilisés pour estimer le taux de dénudations postglaciaire et le remplissage de la vallée du Rhône lié aux grands mouvements gravitaires. Dans la deuxième partie, l'étude de l'agencement structural des avalanches rocheuses de Sierre (Suisse) et de Frank (Canada) a permis de mieux caractériser l'influence passive des structures tectoniques sur la géométrie des instabilités. En particulier, les structures issues d'une tectonique ductile, souvent ignorées dans l'étude des instabilités gravitaires, ont été identifiées comme des structures très importantes qui contrôlent les mécanismes de rupture des instabilités à différentes échelles. Dans la dernière partie de la thèse, cinq instabilités rocheuses différentes ont été étudiées par une approche multidisciplinaire visant à mieux caractériser l'aléa et à développer un modèle conceptuel trois dimensionnel de ces instabilités. A l'aide de ces analyses on a pu mettre en évidence la nécessité d'incorporer différentes techniques d'analyses et de surveillance pour une gestion plus objective du risque associée aux grandes instabilités rocheuses.

Structural changes in latosols of the cerrado region: II - soil compressive behavior and modeling of additional compaction

Currently in Brazil, as in other parts of the world, the concern is great with the increase of degraded agricultural soil, which is mostly related to the occurrence of soil compaction. Although soil texture is recognized as a very important component in the soil compressive behaviors, there are few studies that quantify its influence on the structural changes of Latosols in the Brazilian Cerrado region. This study aimed to evaluate structural changes and the compressive behavior of Latosols in Rio Verde, Goiás, through the modeling of additional soil compaction. The study was carried out using five Latosols with very different textures, under different soil compaction levels. Water retention and soil compression curves, and bearing capacity models were determined from undisturbed samples collected on the B horizons. Results indicated that clayey and very clayey Latosols were more susceptible to compression than medium-textured soils. Soil compression curves at density values associate with edaphic functions were used to determine the beneficial pressure (σ b) , i.e., pressure with optimal water retention, and critical pressure (σcrMAC), i.e., pressure with macroporosity below critical levels. These pressure values were higher than the preconsolidation pressure (σp), and therefore characterized as additional compaction. Based on the compressive behavior of these Latosols, it can be concluded that the combined preconsolidation pressure, beneficial pressure and critical pressure allow a better understanding of compression processes of Latosols.

Quorum-sensing-negative (lasR) mutants of Pseudomonas aeruginosa avoid cell lysis and death.

In Pseudomonas aeruginosa, N-acylhomoserine lactone signals regulate the expression of several hundreds of genes, via the transcriptional regulator LasR and, in part, also via the subordinate regulator RhlR. This regulatory network termed quorum sensing contributes to the virulence of P. aeruginosa as a pathogen. The fact that two supposed PAO1 wild-type strains from strain collections were found to be defective for LasR function because of independent point mutations in the lasR gene led to the hypothesis that loss of quorum sensing might confer a selective advantage on P. aeruginosa under certain environmental conditions. A convenient plate assay for LasR function was devised, based on the observation that lasR mutants did not grow on adenosine as the sole carbon source because a key degradative enzyme, nucleoside hydrolase (Nuh), is positively controlled by LasR. The wild-type PAO1 and lasR mutants showed similar growth rates when incubated in nutrient yeast broth at pH 6.8 and 37 degrees C with good aeration. However, after termination of growth during 30 to 54 h of incubation, when the pH rose to > or = 9, the lasR mutants were significantly more resistant to cell lysis and death than was the wild type. As a consequence, the lasR mutant-to-wild-type ratio increased about 10-fold in mixed cultures incubated for 54 h. In a PAO1 culture, five consecutive cycles of 48 h of incubation sufficed to enrich for about 10% of spontaneous mutants with a Nuh(-) phenotype, and five of these mutants, which were functionally complemented by lasR(+), had mutations in lasR. The observation that, in buffered nutrient yeast broth, the wild type and lasR mutants exhibited similar low tendencies to undergo cell lysis and death suggests that alkaline stress may be a critical factor providing a selective survival advantage to lasR mutants.

Monitoring and predicting crop growth and analysing agricultural ecosystems by remote sensing

Selostus: Maatalousekosysteemien analysointi ja sadon ennustaminen kaukokartoituksen avulla

Genome-wide meta-analysis for serum calcium identifies significantly associated SNPs near the calcium-sensing receptor (CASR) gene.

Calcium has a pivotal role in biological functions, and serum calcium levels have been associated with numerous disorders of bone and mineral metabolism, as well as with cardiovascular mortality. Here we report results from a genome-wide association study of serum calcium, integrating data from four independent cohorts including a total of 12,865 individuals of European and Indian Asian descent. Our meta-analysis shows that serum calcium is associated with SNPs in or near the calcium-sensing receptor (CASR) gene on 3q13. The top hit with a p-value of 6.3 x 10(-37) is rs1801725, a missense variant, explaining 1.26% of the variance in serum calcium. This SNP had the strongest association in individuals of European descent, while for individuals of Indian Asian descent the top hit was rs17251221 (p = 1.1 x 10(-21)), a SNP in strong linkage disequilibrium with rs1801725. The strongest locus in CASR was shown to replicate in an independent Icelandic cohort of 4,126 individuals (p = 1.02 x 10(-4)). This genome-wide meta-analysis shows that common CASR variants modulate serum calcium levels in the adult general population, which confirms previous results in some candidate gene studies of the CASR locus. This study highlights the key role of CASR in calcium regulation.

Estimation of soil moisture in the root-zone from remote sensing data

Field-based soil moisture measurements are cumbersome. Thus, remote sensing techniques are needed because allows field and landscape-scale mapping of soil moisture depth-averaged through the root zone of existing vegetation. The objective of the study was to evaluate the accuracy of an empirical relationship to calculate soil moisture from remote sensing data of irrigated soils of the Apodi Plateau, in the Brazilian semiarid region. The empirical relationship had previously been tested for irrigated soils in Mexico, Egypt, and Pakistan, with promising results. In this study, the relationship was evaluated from experimental data collected from a cotton field. The experiment was carried out in an area of 5 ha with irrigated cotton. The energy balance and evaporative fraction (Λ) were measured by the Bowen ratio method. Soil moisture (θ) data were collected using a PR2 - Profile Probe (Delta-T Devices Ltd). The empirical relationship was tested using experimentally collected Λ and θ values and was applied using the Λ values obtained from the Surface Energy Balance Algorithm for Land (SEBAL) and three TM - Landsat 5 images. There was a close correlation between measured and estimated θ values (p<0.05, R² = 0.84) and there were no significant differences according to the Student t-test (p<0.01). The statistical analyses showed that the empirical relationship can be applied to estimate the root-zone soil moisture of irrigated soils, i.e. when the evaporative fraction is greater than 0.45.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.