L’analyse des paysages, de ses dynamiques et ses processus environnementaux, nécessite d’acquérir régulièrement des données des sites, notamment pour le bilan glaciaire au Spitsberg et en haute montagne. A cause des mauvaises conditions climatiques communes aux latitudes polaires et à cause de leur coût, les images satellites journalières ne sont pas toujours accessibles. De ce fait, les événements rapides comme la fonte de la neige ou l'enneigement ne peuvent pas être étudiés à partir des données de télédétection à cause de leur fréquence trop faible. Nous avons complété les images satellites par un ensemble de de stations photo automatiques et autonomes qui prennent 3 photos par jour. L’acquisition de ces photos génère une grande base de données d’images. Plusieurs traitements doivent être appliqués sur les photos afin d’extraire l’information souhaitée (modifications géométriques, gestion des perturbations atmosphériques, classification, etc). Seule l’informatique est à même de stocker et gérer toutes ces informations. Le cloud computing offre en tant que services des ressources informatiques (puissance de calcul, espace de stockage, applications, etc). Uniquement le stockage de la masse de données géographique pourrait être une raison d’utilisation du cloud computing. Mais en plus de son espace de stockage, le cloud offre une simplicité d’accès, une architecture scalable ainsi qu’une modularité dans les services disponibles. Dans le cadre de l’analyse des photos in situ, le cloud computing donne la possibilité de mettre en place un outil automatique afin de traiter l’ensemble des données malgré la variété des perturbations ainsi que le volume de données. A travers une décomposition du traitement d’images en plusieurs tâches, implémentées en tant que web services, la composition de ces services nous permet d’adapter le traitement aux conditions de chacune des données. / Analyzing landscape, its dynamics and environmental evolutions require regular data from the sites, specifically for glacier mass balanced in Spitsbergen and high mountain area. Due to poor weather conditions including common heavy cloud cover at polar latitudes, and because of its cost, daily satellite imaging is not always accessible. Besides, fast events like flood or blanket of snow is ignored by satellite based studies, since the slowest sampling rate is unable to observe it. We complement satellite imagery with a set of ground based autonomous automated digital cameras which take 3 pictures a day. These pictures form a huge database. Each picture needs many processing to extract the information (geometric modifications, atmospheric disturbances, classification, etc). Only computer science is able to store and manage all this information. Cloud computing, being more accessible in the last few years, offers as services IT resources (computing power, storage, applications, etc.). The storage of the huge geographical data could, in itself, be a reason to use cloud computing. But in addition to its storage space, cloud offers an easy way to access , a scalable architecture and a modularity in the services available. As part of the analysis of in situ images, cloud computing offers the possibility to set up an automated tool to process all the data despite the variety of disturbances and the data volume. Through decomposition of image processing in several tasks, implemented as web services, the composition of these services allows us to adapt the treatment to the conditions of each of the data.

The purpose of this work is to develop and evaluate electroding methods for a reverse osmosis (RO) membrane that results in an in situ sensor able to detect RO membrane protein fouling. Four electroding techniques were explored: i) gold exchange-reduction, ii) encapsulated carbon grease, iii) "direct assembly process" (DAP), and iv) platinized polymer graft. The novel platinized polymer graft method involves chemically modifying the RO membrane surface to facilitate platinization based on the hypothesis that deposition of foulant on the platinized surface will affect platinum/foulant/solution interfacial regions, thus sensor impedance. Platinized polymer graft sensors were shown to be sensitive to protein fouling. Electrodes were characterized by their electrical properties, SEM and XPS. Assembled sensors were evaluated for sensitivity to electrolyte concentration and protein fouling. Micrographs showed coating layers and pre-soak solution influence gold exchange-reduction electrode formation. High surface resistance makes gold exchange-reduction an unsuitable method. Concentration sensitivity experiments showed carbon grease and DAP electroding methods produce unusable sensors. Carbon grease sensors have time-dependent impedance response due to electrolyte diffusion within the micro-porous polysulfone support. DAP electroded sensors proved quite fragile upon hydration; their impedance response is transient and lacks predictable trends with changes in concentration. A parametric study of the platinized polymer graft method shows amount of grafted monomer correlates to grafting time, and deposited platinum is a function of exchange-reduction repetitions and amount of grafted monomer. Platinized polymer graft sensors were fouled in both dead-end and cross-flow RO systems, and their impedance trends, while varying between sensors, indicate protein-fouling sensitivity. / Master of Science