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Abstract Since 1999, Very High spatial Resolution satellite data (Ikonos-2, QuickBird and OrbView-3) represent the surface of the Earth with more detail. However, information extraction by multispectral pixel-based classification proves to have become more complex owing to the internal variability increase in the land-cover units and to the weakness of spectral resolution. Therefore, one possibility is to consider the internal spectral variability of land-cover classes as a valuable source of spatial information that can be used as an additional clue in characterizing and identifying land cover. Moreover, the spatial resolution gap that existed between satellite images and aerial photographs has strongly decreased, and the features used in visual interpretation transposed to digital analysis (texture, morphology and context) can be used as additional information on top of spectral features for the land cover classification. The difficulty of this approach is often to transpose the visual features to digital analysis. To overcome this problem region-based classification could be used. Segmentation, before classification, produces regions that are more homogeneous in themselves than with nearby regions and represent discrete objects or areas in the image. Each region becomes then a unit analysis, which makes it possible to avoid much of the structural clutter and allows to measure and use a number of features on top of spectral features. These features can be the surface, the perimeter, the compactness, the degree and kind of texture. Segmentation is one of the only methods which ensures to measure the morphological features (surface, perimeter...) and the textural features on non-arbitrary neighbourhood. In the pixel-based methods, texture is calculated with mobile windows that smooth the boundaries between discrete land cover regions and create between-class texture. This between-class texture could cause an edge-effect in the classification. In this context, our research focuses on the potential of land cover region-based classification of VHR satellite data through the study of the object extraction capacity of segmentation processes, and through the study of the relevance of region features for classifying the land-cover classes in different kinds of Belgian landscapes; always keeping in mind the parallel with the visual interpretation which remains the reference. Firstly, the results of the assessment of four segmentation algorithms belonging to the two main segmentation categories (contour- and region-based segmentation methods) show that the contour detection methods are sensitive to local variability, which is precisely the problem that we want to overcome. Then, a pre-processing like a filter may be used, at the risk of losing a part of the information. The “region-growing” segmentation that uses the local variability in the segmentation process appears to be the best compromise for the segmentation of different kinds of landscape. Secondly, the features calculated thanks to segmentation seem to be relevant to identify some land-cover classes in urban/sub-urban and rural areas. These relevant features are of the same type as the features selected visually, which shows that the region-based classification gets close to the visual interpretation. The research shows the real usefulness of region-based classification in order to classify the land cover with VHR satellite data. Even in some cases where the features calculated thanks to the segmentation prove to be useless, the region-based classification has other advantages. Working with regions instead of pixels allows to avoid the salt-and-pepper effect and makes the GIS integration easier. The research also highlights some problems that are independent from the region-based classification and are recursive in VHR satellite data, like shadows and the spatial resolution weakness for identifying some land-cover classes. Résumé Depuis 1999, les données satellitaires à très haute résolution spatiale (IKONOS-2, QuickBird and OrbView-3) représentent la surface de la terre avec plus de détail. Cependant, l’extraction d’information par une classification multispectrale par pixel devient plus complexe en raison de l’augmentation de la variabilité spectrale dans les unités d’occupation du sol et du manque de résolution spectrale de ces données. Cependant, une possibilité est de considérer cette variabilité spectrale comme une information spatiale utile pouvant être utilisée comme une information complémentaire dans la caractérisation de l’occupation du sol. De plus, de part la diminution de la différence de résolution spatiale qui existait entre les photographies aériennes et les images satellitaires, les caractéristiques (attributs) utilisées en interprétation visuelle transposées à l’analyse digitale (texture, morphologie and contexte) peuvent être utilisées comme information complémentaire en plus de l’information spectrale pour la classification de l’occupation du sol. La difficulté de cette approche est la transposition des caractéristiques visuelles à l’analyse digitale. Pour résoudre ce problème la classification par région pourrait être utilisée. La segmentation, avant la classification, produit des régions qui sont plus homogène en elles-mêmes qu’avec les régions voisines et qui représentent des objets ou des aires dans l’image. Chaque région devient alors une unité d’analyse qui permet l’élimination de l’effet « poivre et sel » et permet de mesurer et d’utiliser de nombreuses caractéristiques en plus des caractéristiques spectrales. Ces caractéristiques peuvent être la surface, le périmètre, la compacité, la texture. La segmentation est une des seules méthodes qui permet le calcul des caractéristiques morphologiques (surface, périmètre, …) et des caractéristiques texturales sur un voisinage non-arbitraire. Avec les méthodes de classification par pixel, la texture est calculée avec des fenêtres mobiles qui lissent les limites entre les régions d’occupation du sol et créent une texture interclasse. Cette texture interclasse peut alors causer un effet de bord dans le résultat de la classification. Dans ce contexte, la recherche s’est focalisée sur l’étude du potentiel de la classification par région de l’occupation du sol avec des images satellitaires à très haute résolution spatiale. Ce potentiel a été étudié par l’intermédiaire de l’étude des capacités d’extraction d’objet de la segmentation et par l’intermédiaire de l’étude de la pertinence des caractéristiques des régions pour la classification de l’occupation du sol dans différents paysages belges tant urbains que ruraux.

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The diesel engine is growing in popularity due to its energy efficiency and solving the emissions issues associated with diesel engine exhaust would clear the way for further growth. The key pollutants are NOx, particulate matter and unburned hydrocarbons. Selective catalytic reduction (SCR) catalysis is likely the best choice for NOx control. In SCR, NH3 selectively reacts with NOx to form N2 – the selectivity refers to NH3 reacting with NOx instead of the abundant O2. Urea is used as the NH3 source, being injected into the exhaust as an aqueous solution where the urea decomposes and NH3 is generated. Spatial resolution characterization techniques have been gaining attention in the catalysis field because of the higher level of information provided. In this thesis, a new spatial resolution technique, called SpaciFTIR (spatially-resolved, capillary-inlet Fourier transform infra-red spectroscopy), was developed, which overcomes the interference of water in the detection of NH3 in an earlier developed technique, SpaciMS (spatially-resolved, capillary-inlet mass spectrometry). With the new test method, three SCR topics were addressed. First, the three key SCR reactions were spatially resolved. These are the standard SCR reaction (2NO + 2NH3 + 1/2O2 = 2N2 + 3H2O), the fast SCR reaction (NO + NO2 + 2NH3 = 2N2 + 3H2O), and NO2-SCR, (6NO2 + 8NH3 = 7N2 + 12H2O). Results show that in the presence of NO2, but at a NO2/NOx ratio < 0.5, the fast SCR reaction proceeds followed by the standard SCR reaction, i.e. in series. If the NO2/NOx ratio exceeds 0.5, the NO2-SCR and fast SCR reactions occur in parallel. Compared to the standard integral test method, this spatial resolution technique clearly showed such trends. Secondly, the spatial resolution technique was used to characterize the effects of thermal aging on catalyst performance. It was found that for a highly aged catalyst, there was a radial activity profile due to an inhomogeneous temperature distribution in the process of aging. Aging effects on various key SCR reactions, i.e. NO oxidation, NH3 oxidation, and the reduction reactions, were studied. Last but not least, for the purpose of passive SCR system development, transient NH3 storage profiles along the monolith channel were measured with SpaciFTIR. Passive SCR is a system where the NH3 is generated on an upstream catalyst, such as a three-way catalyst or lean-NOx trap, instead of via urea injection. In such a system, NH3 is therefore not constantly being fed to the SCR catalyst, but “arrives” in pulses. Factors such temperature, NH3 concentration, pulsing time, flow rate and thermal aging were investigated. For the first time, NH3 migration was observed and its effect on SCR reactions along the length of catalyst was studied.

Low resolution (LR) Grid Digital Elevation Models (DEMs) are the inputs of multi frame super resolution (MFSR) algorithm to obtain high resolution (HR) grid DEM. In digital image MFSR, non-redundant information carrying LR image pairs are a necessity. By using the analogy between digital image and grid DEMs, it is proven that, although the LR grid DEMs have a single source, they carry non-redundant information and they can be inputs of MFSR. Quality of grid DEM can be increased by using MFSR techniques. The level of spatial enhancement is directly related to the amount of non-redundant information that the LR grid DEM pairs carry. It is seen that super resolution techniques have potential to increase the accuracy of grid DEMs from a limited sampling.

There has been a growing interest in using lean-burn engines due to their higher fuel economy and associated lower CO2 emissions. However, there are challenges in reducing NOX in an O2-rich (lean-burn) exhaust, and in low temperature soot oxidation. NOX storage/reduction (NSR) and selective catalytic reduction (SCR) are commercial NOX reduction technologies, and both are more efficient with levels of NO2 that are higher than those that are in engine exhaust (engine-out NO2 levels are ~10% of the total NOX). Therefore diesel oxidation catalysts are installed upstream of these technologies to provide NO2 through NO oxidation. The motivation behind this research project was two-fold. The first was to gain a better understanding of the effect of hydrocarbons on NO oxidation over a monolithic diesel oxidation catalyst. The second was to spatially resolve competitive oxidation reactions as a function of temperature and position within the same diesel oxidation catalyst (as that used in the first part). A technique known as spatially resolved capillary-inlet mass spectrometry (SpaciMS) was used to measure the gas concentrations at various positions within the catalyst. Diesel engine exhaust contains a mixture of compounds including NO, CO and various hydrocarbons, which react simultaneously over a catalyst, and each can influence the oxidation rates of the others. While studying the effect of hydrocarbons on NO oxidation in this project, propylene was found to have an apparent inhibition effect on NO oxidation, which increased with increasing propylene concentration. This apparent inhibition is a result of the NO2, as a product of NO oxidation, reacting with the propylene as an oxidant. Experiments with NO2 demonstrate a significant temperature decrease in the onset of NO2 reduction when propylene was present, which decreased further with increasing amounts of propylene, verifying NO2 as an oxidant. Similar results were observed with m-xylene and dodecane addition as well. The results also demonstrate that NO2 was consumed preferentially relative to O2 during hydrocarbon oxidation. With low inlet levels of O2, it was evident that the addition of NO2 had an apparent inhibition effect on propylene oxidation after the onset of NO2 reduction. This subsequent inhibition was due to the NO formed, demonstrating that C3H6 results in reduced NO2 outlet levels while NO inhibits C3H6 oxidation. The development of new models as well as validation of existing models requires the ability to spatially resolve oxidation reactions within a monolith. Spatially-resolved data will also give catalyst manufacturers insight into the location of active fronts, thereby directing the design of more efficient catalysts. In this research project, spatially resolving the oxidation reactions demonstrated that H2 and CO are oxidized prior to C3H6 and C12H26 and clearly show back-to-front ignition of the reductant species. An enhancement in NO oxidation was observed at the same time as dodecane oxidation light off, likely related to dodecane partial oxidation products.

There has been a growing interest in using lean-burn engines due to their higher fuel economy and associated lower CO2 emissions. However, there are challenges in reducing NOX in an O2-rich (lean-burn) exhaust, and in low temperature soot oxidation. NOX storage/reduction (NSR) and selective catalytic reduction (SCR) are commercial NOX reduction technologies, and both are more efficient with levels of NO2 that are higher than those that are in engine exhaust (engine-out NO2 levels are ~10% of the total NOX). Therefore diesel oxidation catalysts are installed upstream of these technologies to provide NO2 through NO oxidation. The motivation behind this research project was two-fold. The first was to gain a better understanding of the effect of hydrocarbons on NO oxidation over a monolithic diesel oxidation catalyst. The second was to spatially resolve competitive oxidation reactions as a function of temperature and position within the same diesel oxidation catalyst (as that used in the first part). A technique known as spatially resolved capillary-inlet mass spectrometry (SpaciMS) was used to measure the gas concentrations at various positions within the catalyst. Diesel engine exhaust contains a mixture of compounds including NO, CO and various hydrocarbons, which react simultaneously over a catalyst, and each can influence the oxidation rates of the others. While studying the effect of hydrocarbons on NO oxidation in this project, propylene was found to have an apparent inhibition effect on NO oxidation, which increased with increasing propylene concentration. This apparent inhibition is a result of the NO2, as a product of NO oxidation, reacting with the propylene as an oxidant. Experiments with NO2 demonstrate a significant temperature decrease in the onset of NO2 reduction when propylene was present, which decreased further with increasing amounts of propylene, verifying NO2 as an oxidant. Similar results were observed with m-xylene and dodecane addition as well. The results also demonstrate that NO2 was consumed preferentially relative to O2 during hydrocarbon oxidation. With low inlet levels of O2, it was evident that the addition of NO2 had an apparent inhibition effect on propylene oxidation after the onset of NO2 reduction. This subsequent inhibition was due to the NO formed, demonstrating that C3H6 results in reduced NO2 outlet levels while NO inhibits C3H6 oxidation. The development of new models as well as validation of existing models requires the ability to spatially resolve oxidation reactions within a monolith. Spatially-resolved data will also give catalyst manufacturers insight into the location of active fronts, thereby directing the design of more efficient catalysts. In this research project, spatially resolving the oxidation reactions demonstrated that H2 and CO are oxidized prior to C3H6 and C12H26 and clearly show back-to-front ignition of the reductant species. An enhancement in NO oxidation was observed at the same time as dodecane oxidation light off, likely related to dodecane partial oxidation products.

Intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) have been introduced in radiation therapy to achieve highly conformal dose distributions around the tumour while minimizing dose to surrounding normal tissues. These techniques have increased the need for comprehensive quality assurance tests, to verify that customized patient treatment plans are accurately delivered during treatment. In vivo dose verification, performed during treatment delivery, confirms that the actual dose delivered is the same as the prescribed dose, helping to reduce treatment delivery errors. In vivo measurements may be accomplished using entrance or exit detectors. The objective of this project is to investigate a novel entrance detector designed for in vivo dose verification. This thesis is separated into three main investigations, focusing on a prototype entrance transmission detector (TRD) developed by IBA Dosimetry, Germany. First contaminant electrons generated by the TRD in a 6 MV photon beam were investigated using Monte Carlo (MC) simulation. This study demonstrates that modification of the contaminant electron model in the treatment planning system is required for accurate patient dose calculation in buildup regions when using the device. Second, the ability of the TRD to accurately measure dose from IMRT and VMAT was investigated by characterising the spatial resolution of the device. This was accomplished by measuring the point spread function with further validation provided by MC simulation. Comparisons of measured and calculated doses show that the spatial resolution of the TRD allows for measurement of clinical IMRT fields within acceptable tolerance. Finally, a new general research tool was developed to perform MC simulations for VMAT and IMRT treatments, simultaneously tracking dose deposition in both the patient CT geometry and an arbitrary planar detector system, generalized to handle either entrance or exit orientations. It was demonstrated that the tool accurately simulates dose to the patient CT and planar detector geometries. The tool has been made freely available to the medical physics research community to help advance the development of in vivo planar detectors. In conclusion, this thesis presents several investigations that improve the understanding of a novel entrance detector designed for patient in vivo dosimetry.

Intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) have been introduced in radiation therapy to achieve highly conformal dose distributions around the tumour while minimizing dose to surrounding normal tissues. These techniques have increased the need for comprehensive quality assurance tests, to verify that customized patient treatment plans are accurately delivered during treatment. In vivo dose verification, performed during treatment delivery, confirms that the actual dose delivered is the same as the prescribed dose, helping to reduce treatment delivery errors. In vivo measurements may be accomplished using entrance or exit detectors. The objective of this project is to investigate a novel entrance detector designed for in vivo dose verification. This thesis is separated into three main investigations, focusing on a prototype entrance transmission detector (TRD) developed by IBA Dosimetry, Germany. First contaminant electrons generated by the TRD in a 6 MV photon beam were investigated using Monte Carlo (MC) simulation. This study demonstrates that modification of the contaminant electron model in the treatment planning system is required for accurate patient dose calculation in buildup regions when using the device. Second, the ability of the TRD to accurately measure dose from IMRT and VMAT was investigated by characterising the spatial resolution of the device. This was accomplished by measuring the point spread function with further validation provided by MC simulation. Comparisons of measured and calculated doses show that the spatial resolution of the TRD allows for measurement of clinical IMRT fields within acceptable tolerance. Finally, a new general research tool was developed to perform MC simulations for VMAT and IMRT treatments, simultaneously tracking dose deposition in both the patient CT geometry and an arbitrary planar detector system, generalized to handle either entrance or exit orientations. It was demonstrated that the tool accurately simulates dose to the patient CT and planar detector geometries. The tool has been made freely available to the medical physics research community to help advance the development of in vivo planar detectors. In conclusion, this thesis presents several investigations that improve the understanding of a novel entrance detector designed for patient in vivo dosimetry.