Este trabalho apresenta um estudo da influência do crescimento epitaxial seletivo (SEG) em dispositivos tensionados mecanicamente (strain) em transistores SOI MuGFET de porta tripla. Com a evolução da tecnologia de integração de transistores, alguns efeitos parasitários são eliminados ou diminuídos, porém outros novos surgem. A tecnologia SOI MuGFETs disponibiliza dispositivos de múltiplas portas, tridimensionais. Nesses dispositivos, há um aumento da resistência de contato dos terminais devido ao estreitamento da região de canal, tornando esta resistência significativa em relação à resistência total. A utilização do Crescimento Epitaxial Seletivo (SEG) é uma das opções para diminuir a resistência total, elevando a região de fonte e dreno, causando o aumento da área de contato, diminuindo essa resistência parasitária. Em contrapartida, a utilização dos canais tensionados Uniaxiais, por filme de Si3N4, pela técnica de CESL, que é uma opção de melhora da transcondutância, mas em conjunto com o SEG afasta essa a camada de nitreto, tornando em determinada altura prejudicial ao invés de benéfico. Este trabalho foi realizado baseado em resultados experimentais e em simulações numéricas, mecânicas e elétricas de dispositivos, variando as tecnologias de tensionamento mecânico nos dispositivos com e sem SEG. Variou-se a altura do SEG em simulações, possibilitando extrapolar e obter resultados que de forma experimental não foram possíveis, permitindo um entendimento físico do fenômeno estudado. O resultados obtidos das diferentes tecnologias com e sem o uso de SEG mostraram que, em transistores SOI MuGFETs de porta tripla, o crescimento seletivo epitaxial nos dispositivos com tensão uniaxial piora a transcondutância máxima para dispositivos abaixo de 200nm de comprimento de canal, mas em contra partida torna mais prolongado o efeito pelos dispositivos acima dessa dimensão, como pode ser comprovado nos resultados obtidos. / This paper presents the study of the influence of selective epitaxial growth (SEG) devices mechanically strained (strain) in SOI transistors MuGFET triple gate. With the evolution of integration technology of transistors, some parasitic effects are eliminated or reduced, but new ones arise. MuGFETs SOI technology, devices are multiple ports, three-dimensional, these devices there is an increase in contact resistance of terminals due to the narrowing of the channel region, making considered in relation to total resistance. Use of Selective Epitaxial Growth (SEG) is one of the options to reduce the total resistance, raising the source and drain region, causing increased contact area by reducing the parasitic resistance. In contrast, the use of uniaxial strained channel by a film of Si3N4 by CESL technique is an option for improvement in transconductance, but in conjunction with the SEG away this layer of nitride, making it at some point or detrimental rather than beneficial. This study was based on experimental results and numerical simulations, mechanical and electrical devices of varying technologies in mechanical tensioning devices with and without FES, the height was varied in simulations of the FES, allowing extrapolate and obtain results that way trial was not possible, allowing a physical understanding of the phenomenon. The results of the different technologies with and without the use of FES showed that in SOI transistors MuGFETs triple gate, the selective epitaxial growth in uniaxial strained devices tends to worsen the maximum transconductance for devices below 200nm channel length, but against departure becomes more unrelenting effect on the devices above this size. As can be evidenced in the results obtained.

Este trabalho apresenta um estudo da influência do crescimento epitaxial seletivo (SEG) em dispositivos tensionados mecanicamente (strain) em transistores SOI MuGFET de porta tripla. Com a evolução da tecnologia de integração de transistores, alguns efeitos parasitários são eliminados ou diminuídos, porém outros novos surgem. A tecnologia SOI MuGFETs disponibiliza dispositivos de múltiplas portas, tridimensionais. Nesses dispositivos, há um aumento da resistência de contato dos terminais devido ao estreitamento da região de canal, tornando esta resistência significativa em relação à resistência total. A utilização do Crescimento Epitaxial Seletivo (SEG) é uma das opções para diminuir a resistência total, elevando a região de fonte e dreno, causando o aumento da área de contato, diminuindo essa resistência parasitária. Em contrapartida, a utilização dos canais tensionados Uniaxiais, por filme de Si3N4, pela técnica de CESL, que é uma opção de melhora da transcondutância, mas em conjunto com o SEG afasta essa a camada de nitreto, tornando em determinada altura prejudicial ao invés de benéfico. Este trabalho foi realizado baseado em resultados experimentais e em simulações numéricas, mecânicas e elétricas de dispositivos, variando as tecnologias de tensionamento mecânico nos dispositivos com e sem SEG. Variou-se a altura do SEG em simulações, possibilitando extrapolar e obter resultados que de forma experimental não foram possíveis, permitindo um entendimento físico do fenômeno estudado. O resultados obtidos das diferentes tecnologias com e sem o uso de SEG mostraram que, em transistores SOI MuGFETs de porta tripla, o crescimento seletivo epitaxial nos dispositivos com tensão uniaxial piora a transcondutância máxima para dispositivos abaixo de 200nm de comprimento de canal, mas em contra partida torna mais prolongado o efeito pelos dispositivos acima dessa dimensão, como pode ser comprovado nos resultados obtidos. / This paper presents the study of the influence of selective epitaxial growth (SEG) devices mechanically strained (strain) in SOI transistors MuGFET triple gate. With the evolution of integration technology of transistors, some parasitic effects are eliminated or reduced, but new ones arise. MuGFETs SOI technology, devices are multiple ports, three-dimensional, these devices there is an increase in contact resistance of terminals due to the narrowing of the channel region, making considered in relation to total resistance. Use of Selective Epitaxial Growth (SEG) is one of the options to reduce the total resistance, raising the source and drain region, causing increased contact area by reducing the parasitic resistance. In contrast, the use of uniaxial strained channel by a film of Si3N4 by CESL technique is an option for improvement in transconductance, but in conjunction with the SEG away this layer of nitride, making it at some point or detrimental rather than beneficial. This study was based on experimental results and numerical simulations, mechanical and electrical devices of varying technologies in mechanical tensioning devices with and without FES, the height was varied in simulations of the FES, allowing extrapolate and obtain results that way trial was not possible, allowing a physical understanding of the phenomenon. The results of the different technologies with and without the use of FES showed that in SOI transistors MuGFETs triple gate, the selective epitaxial growth in uniaxial strained devices tends to worsen the maximum transconductance for devices below 200nm channel length, but against departure becomes more unrelenting effect on the devices above this size. As can be evidenced in the results obtained.

Contaminated areas resulting from anthropogenic activities have, for the most part, concentrations of contaminants that exceed Tier 1 standards below which the risk is considered acceptable. However, contaminants that have been in soil for a prolonged period can become recalcitrant over time, due to various physico-chemical and biological processes. Sequestered and recalcitrant contaminants are not readily biologically available to living organisms. However, they are easily measured analytically because of the strong acid extractions that are used in the analytical methodologies. Because toxicity is a function of exposure concentration(s), exposure duration, and bioavailability, contaminants in soil can be present at concentrations that exceed established standards but they represent minimal risk to ecological receptors because the contaminants are not fully available. To predict toxicity and estimate risk, it is imperative that an accurate and reliable measure of bioavailability be available. Several surrogate measures of bioavailability were compared to the results of a battery of toxicity tests using Cu, Pb, and Zn-contaminated soils collected from a former industrial area and Cu and Zn-contaminated soils collected from a former mining site. CaCl₂extractions, hydroxypropyl-β-cyclodextrin (cyclodextrin) extractions, Simulated Earthworm Gut (SEG) tests, and bioaccumulation tests were performed using the soils. Overall, SEG-extractable Cu was most predictive of adverse effects in industrial soils, likely due to enzymatic activity and/or increased ionic strength of the solution. For the mining soils, all chemical measures of bioavailability correlated with several biological responses; however, CaCl₂-extractable Cu and SEG-extractable Cu and Zn best predicted earthworm responses. Total Cu concentrations in soil correlated best with adverse effects to plants. No method was a good predictor of all biological effects for a single organism when data from the two sites were combined. The SEG test may provide a good indication of metal toxicity at contaminated sites with varying soil physico-chemical characteristics but further validation is required.

Contaminated areas resulting from anthropogenic activities have, for the most part, concentrations of contaminants that exceed Tier 1 standards below which the risk is considered acceptable. However, contaminants that have been in soil for a prolonged period can become recalcitrant over time, due to various physico-chemical and biological processes. Sequestered and recalcitrant contaminants are not readily biologically available to living organisms. However, they are easily measured analytically because of the strong acid extractions that are used in the analytical methodologies. Because toxicity is a function of exposure concentration(s), exposure duration, and bioavailability, contaminants in soil can be present at concentrations that exceed established standards but they represent minimal risk to ecological receptors because the contaminants are not fully available. To predict toxicity and estimate risk, it is imperative that an accurate and reliable measure of bioavailability be available. Several surrogate measures of bioavailability were compared to the results of a battery of toxicity tests using Cu, Pb, and Zn-contaminated soils collected from a former industrial area and Cu and Zn-contaminated soils collected from a former mining site. CaCl₂extractions, hydroxypropyl-β-cyclodextrin (cyclodextrin) extractions, Simulated Earthworm Gut (SEG) tests, and bioaccumulation tests were performed using the soils. Overall, SEG-extractable Cu was most predictive of adverse effects in industrial soils, likely due to enzymatic activity and/or increased ionic strength of the solution. For the mining soils, all chemical measures of bioavailability correlated with several biological responses; however, CaCl₂-extractable Cu and SEG-extractable Cu and Zn best predicted earthworm responses. Total Cu concentrations in soil correlated best with adverse effects to plants. No method was a good predictor of all biological effects for a single organism when data from the two sites were combined. The SEG test may provide a good indication of metal toxicity at contaminated sites with varying soil physico-chemical characteristics but further validation is required.

Today more and more people are moving to the cities around the world. This puts a lot of strain on the infrastructure as the cities grow in both width and height. To be able to monitor the ongoing change remote sensing is an effective tool and ways to make it even more effective, better and easier to use are constantly sought after. One way to monitor change detection is object based change detection. The idea has been around since the seventies, but it wasn’t until the early 2000 when it was introduced by Blaschke and Strobl(2001) to the market as a solution to the issues with pixel based analysis that it became popular with remote analysts around the world. KTH-SEG is developed at KTH Geoinformatics. It is developed to segment images in order to preform object based analysis; it can also be used for classification. In this thesis object based change detection over an area of Shanghai is carried out. Two different approaches are used; post-classification analysis as well as creating change detection images. The maps are assessed using the maximum likelihood report in the software Geomatica. The segmentation and classification is done using KTH-SEG, training areas and ground truth data polygons are drawn in ArcGIS and pre-processing and other operations is carried out using Geomatica. KTH-SEG offers a number of changeable settings that allows the segmentation to suit the image at hand.  It is easy to use and produces well defined classification maps that are usable for change detection The results are evaluated in order to estimate the efficiency of object based change detection in urban area and KTH-SEG is appraised as a segmentation and classification tool. The results show that the post-classification approach is superior to the change detection images. Whether the poor result of the change detection images is affected by other parameters than the object based approach can’t be determined. / Idag flyttar fler och fler människor in i städer runt om i världen. Det utgör en stor påverkan på den befintliga infra-strukturen då städerna växer på både höjden och bredden. För att kunna bevaka den förändring som sker så används ofta fjärranalys som ett effektivt verktyg. Sätt att utveckla befintliga tekniken försöker man hela tiden hitta nya, enklare och mer effektiva sätt att bevaka förändring finns alltid på horisonten. Objektbaserad förändrings analys är ett sätt att bevaka förändringar. Iden om att använda objekt baserad analys har funnits sedan 70-talet, men det var först i början av 2000-talet, då Blaschke och Strobl(2001) introducerade tekniken som en lösning på de problem man stöter på i pixelbaserad analys, som tekniken blev populär bland fjärranalytiker världen över. KTH-SEG är ett program utvecklat på KTH Geoinformatik avdelning. KTH-SEG är utvecklat för att segmentera bilder inför objektbaserad analys. Dessutom utför programmet klassificering. I det här arbetet utförs objektbaserad förändrings analys över ett område i Shanghai. För att hitta de förändringar som har skett har två tillvägsgångssätt använts: dels har analys av bilder efter klassificeringen gjorts och dels har bilder som i sig själva skall visa den förändring som har skett skapats, så kallade förändringsbilder. Bildernas pålitlighet är utvärderad genom att använda ”maximum likelihood report” i programmet Geomatica.   Segmentering och klassificering är gjort i programmet KTH-SEG, träningsområden och testområden är skapade i ArcGIS och förbehandling av bilder samt andra operationer är gjorda i Geomatica. KTH-SEG erbjuder många valmöjligheter för att påverka segmenteringsresultatet. Den är enkelt att använda och producerar tydliga klassificerade bilder som är användbara för analys. Resultatet utvärderas för att bestämma hur effektivt det är att använda objektbaserad förändrings analys av urbana områden och KTH-SEG utvärderas som ett segmenterings- och klassifikations verktyg. Resultaten visar att förändringsbilder ger ett sämre resultat än bilder som analyseras efter klassifikationen. Huruvida det dåliga resultatet på förändingsbilderna beror på andra omständigheter än tillvägagångssättet med objekt baserad klassifikation kan inte bestämmas. Mycket tyder dock på att det är valet av två bilder från olika satelliter som ger det dåliga resultatet.

Bladder cancer (BCa) is the fourth most commonly diagnosed cancers in men and the eighth most common in women. It is an abnormal growth of tissues which develops in the bladder lining. Histological analysis of bladder tissue facilities diagnosis as well as it serves as an important tool for research. To bet- ter understand the molecular profile of bladder cancer and to detect predictive and prognostic features, microscopy methods, such as immunofluorescence (IF), are used to investigate the characteristics of bladder cancer tissue. For this project, a new method is proposed to segment cancer epithelial us- ing nuclei morphology captured with IF staining. The method is implemented using deep learning algorithms and performance achieved is compared with the literature. The dataset is stained for nuclei (DAPI) and a marker for cancer epithelial (panEPI) which was used to create the ground truth. Three popu- lar Convolutional Neural Network (CNN) namely U-Net, Residual U-Net and VGG16 were implemented to perform the segmentation task on the tissue mi- croarray dataset. In addition, a transfer learning approach was tested with the VGG16 network that was pre-trained with ImageNet dataset. Further, the performance from the three networks were compared using 3fold cross-validation. The dice accuracies achieved were 83.32% for U-Net, 88.05% for Residual U-Net and 82.73% for VGG16. These findings suggest that segmentation of cancerous tissue regions, using only the nuclear morphol- ogy, is feasible with high accuracy. Computer vision methods better utilizing nuclear morphology captured by the nuclear stain, are promising approaches to digitally augment the conventional IF marker panels, and therefore offer im- proved resolution of the molecular characteristics for research settings.

Le développement de nouveaux capteurs multispectraux en imagerie astronomique permet l'acquisition de données d'une grande richesse. Néanmoins, la classification d'images multidimensionnelles se heurte souvent au phénomène de Hughes : l'augmentation de la dimensionnalité s'accompagne d'un accroissement du nombre de paramètres du modèle et donc inévitablement une baisse de précision de leur estimation entrainant une dégradation de la qualité de la segmentation. Il est donc impératif d'écarter l'information redondante afin de réaliser des opérations de segmentation ou de classification robustes. Dans le cadre de cette thèse, nous avons propose deux méthodes de réduction de la dimensionnalité pour des images multispectrales : 1) le regroupement de bandes suivis de projections locales ; 2) la réduction des cubes radio par un modèle de mélange de gaussiennes. Nous avons également propose un schéma de réduction/segmentation jointe base sur la régularisation du mélange d'analyseurs en composantes principales probabilistes (MACPP). En se qui concerne la tâche de segmentation, nous avons choisie une approche bayésienne s'appuyant sur des modèles hiérarchiques récents a base d'arbres de Markov cache et couple. Ces modèles permettent en effet un calcul rapide et exact des probabilités a posteriori. Pour le terme d'attache aux données, nous avons utilisée la loi gaussienne multidimensionnelle classique, la loi gaussienne généralisée multidimensionnelles formulée grâce à la théorie des copules et la vraisemblance par rapport au modèle de l'ACP probabiliste (dans le cadre de la MACPP régularisée). L'apport majeur de ce travail consiste donc a proposer différents modèles markoviens hiérarchiques de segmentation adaptés aux données multidimensionnelles multirésolutions. Leur exploitation pour des données issues d'une analyse par ondelettes adaptée au contexte astronomique nous a permis de développer des techniques de débruitage et de fusion d'images astronomiques multispectrales nouvelles. Tous les algorithmes sont non supervises et ont été valides sur des images synthétiques et réelles.

Les hydrocarbures aromatiques polycycliques (HAP) constituent une famille de polluants cancérigènes, classés comme prioritaires tant en environnement qu’en milieu professionnel avec près de 1,6 millions de travailleurs exposés en France. L’évaluation des risques sanitaires (ERS) est primordiale mais reste difficile à mettre en place car ces composés sont toujours émis sous forme de mélanges complexes de gaz et de particules dont la composition varie en fonction des sources d’émission.Les objectifs de ce travail sont de caractériser, dans les différents secteurs industriels français, les expositions professionnelles (niveaux de concentration et composition chimique des mélanges) afin d’estimer les risques de cancer liés à ces expositions. Ce travail est réalisé à partir de la base Exporisq-HAP (E-HAP) qui comprend plus de 1700 données d’exposition atmosphérique ainsi que 40 variables explicatives collectées dans 130 entreprises avec la même méthodologie et codées par le même toxicologue depuis près de 20 ans.Pour conduire l’ERS, les données ont été structurées selon deux dimensions (homogénéité et précision de description), permettant de construire des groupes homogènes d’exposition (GHE) et une analyse descriptive du paysage industriel français. En prenant le benzo[a]pyrène (BaP, HAP le plus dangereux) comme indicateur, près de 40% des activités professionnelles (niveau de codage le plus fin de la base) correspondaient à des GHE (écart-type géométrique ≤ 3) mais l’ajout d’un niveau de description supplémentaire a permis d’augmenter ce pourcentage à 87%. Des variabilités importantes des niveaux de concentration, des compositions chimiques des mélanges et des risques encourus (facteur 2 pour les bitumes à 500 pour les fonderies) lors d’une mono-exposition aux HAP (e.g., BaP, naphtalène…) existaient entre et au sein des industries, soulignant l’importance de recueillir le détail des activités effectuées par le salarié pour caractériser précisément les expositions. Dans la seconde étape, les multi-expositions aux HAP ont été analysées en termes de groupes de fonction d’exposition similaire (GFES basés sur plusieurs HAP). Ces fonctions (distributions des concentrations d’HAP) ont été utilisées pour décrire le paysage industriel français aux mélanges d’HAP, construire des marqueurs de la multi-exposition atmosphérique et réaliser l’estimation préliminaire des risques de survenue de cancers. En plus du BaP, le benzo[k]fluoranthène et le benzo[ghi]pérylène sont apparus comme des indicateurs intéressants de la multi-exposition aux HAP cancérigènes, ce qui n’était pas le cas du pyrène (gazeux ou particulaire), du naphtalène ni du phénanthrène. Les GFES étaient constitués de groupes dont l’origine des sources était la même –produits dérivés de pétrole (GFESP) ou de houille (GFESH). Les GFESH (production d’aluminium, de silicium, de produits carbonés, cokeries, fonderies) avaient des niveaux de concentration élevés et un risque important de cancer du poumon (compris entre 1/100 000 à 1/1 000 de risque d’observer un cas additionnel de cancer du poumon) ; ce qui n’était pas le cas des GFESP (émissions moteurs, huiles, combustion, bitume) pour lesquels les risques de cancers sont compris entre 1/100 000 et un sur 1 million de sujets exposés. Les mesures de prévention et de protection sont encore à améliorer dans les GFESH afin de réduire les risques de survenue de cancers. / Polycyclic aromatic hydrocarbons (PAHs) are a family of organic carcinogens substances, ranked second amongst priority targeted pollutants in the environment as well as in occupational settings where around 1.6 million workers are exposed in France. Sanitary risks assessment (SRA) is paramount but remains difficult to set up considering that PAHs are always emitted in complex mixtures of gas and particles whose composition depends on emission sources.The goals of this PhD were to characterize exposures within industries (levels and chemical composition of PAHs mixtures) in order to assess the cancer risk from occupational exposure to PAHs mixtures. This work was performed using the Exporisq-HAP database (E-HAP) that gathers more than 1,700 airborne exposure data as well as 40 independent variables collected in 130 companies with the same methodology and coded by the same toxicologist for 20 years.To conduct the SRA, data were structured following two dimensions (homogeneity and description accuracy), enabling the construction of similar exposure groups (SEGs) and the descriptive analysis of the French industrial landscape. Using the benzo[a]pyrene as indicator (BaP, the most dangerous PAH), about 40% of the occupational activities (most accurate description level in E-HAP) could be considered as SEGs (geometric standard deviation ≤ 3). Adding a new description level increased this percentage to 87%. High variabilities existed between and within industries in terms of concentrations levels, chemical mixtures composition and risk (between 2 for bitumen to 500 times within foundries) caused by mono-exposure to PAHs (e.g., BaP, naphthalene…). This underlines the importance of collecting detailed information on occupational activities performed by workers to accurately describe and characterize exposures. In the second step, multi-exposures to PAHs were analyzed in terms of similar exposure function groups (SEFG based on several PAHs). Exposure functions (PAHs concentrations distributions) were used to describe the French PAHs industrial landscape, to construct markers of the multi-exposures to airborne PAHs and to perform the preliminary assessment of the cancer risk caused by these mixtures. Besides BaP, benzo[k]fluoranthene and benzo[ghi]perylene were found to be indicators of the multi-exposures to airborne carcinogenic PAHs, which was not the case for pyrene (gaseous and particulate forms), naphthalene and phenanthrene. SEFGs were made up of groups with the same source origin –either from products derived from coal (SEFGH) or petroleum (SEGFP). SEFGH (aluminum, silicon, carbon product, coke production, and foundry) had high concentration levels and high risk of lung cancer (between 100,000 to 1 risk to 1,000 to 1 risk to observe one additional case of lung cancer). It was different for SEGFP (engine emissions, lubricating oil, combustion, bitumen) that had between 100,000 to 1 risk to a million to 1 risk of additional lung cancer. To reduce cancer risks, risk management measures still need improvements in all SEFGH.

The objective of this licentiate thesis is to develop novel algorithms and improve existing methods for urban land cover mapping and urban extent extraction using multi-temporal remote sensing imagery. Past studies have demonstrated that synthetic aperture radar (SAR) have very good properties for the analysis of urban areas, the synergy of SAR and optical data is advantageous for various applications. The specific objectives of this research are: 1. To develop a novel edge-aware region-growing and -merging algorithm, KTH-SEG, for effective segmentation of SAR and optical data for urban land cover mapping; 2. To evaluate the synergistic effects of multi-temporal ENVISAT ASAR and HJ-1B multi-spectral data for urban land cover mapping; 3. To improve the robustness of an existing method for urban extent extraction by adding effective pre- and post-processing. ENVISAT ASAR data and the Chinese HJ-1B multispectral , as well as TerraSAR-X data were used in this research. For objectives 1 and 2 two main study areas were chosen, Beijing and Shanghai, China. For both sites a number of multitemporal ENVISAT ASAR (30m C-band) scenes with varying image characteristics were selected during the vegetated season of 2009. For Shanghai TerraSAR-X strip-map images at 3m resolution X-band) were acquired for a similar period in 2010 to also evaluate high resolution X-band SAR for urban land cover mapping. Ten  major landcover classes were extracted including high density built-up, low density built-up, bare field, low vegetation, forest, golf course, grass, water, airport runway and major road. For Objective 3, eleven globally distributed study areas where chosen, Berlin, Beijing, Jakarta, Lagos, Lombardia (northern Italy), Mexico City, Mumbai, New York City, Rio de Janeiro, Stockholm and Sydney. For all cities ENVISAT ASAR imagery was acquired and for cities in or close to mountains even SRTM digital elevation data. The methodology of this thesis includes two major components, KTH-SEG and KTH-Pavia Urban Extractor. KTH-SEG is an edge aware region-growing and -merging algorithm that utilizes both the benefit of finding local high frequency changes as well as determining robustly homogeneous areas of a low frequency in local change. The post-segmentation classification is performed using support vector machines. KTH-SEG was evaluated using multitemporal, multi-angle, dual-polarization ASAR data and multispectral HJ-1B data as well as TerraSAR-X data. The KTH-Pavia urban extractor is a processing chain. It includes: Geometrical corrections, contrast enhancement, builtup area extraction using spatial stastistics and GLCM texture features, logical operator based fusion and DEM based mountain masking. For urban land cover classification using multitemporal ENVISAT ASAR data, the results showed that KTH-SEG achieved an overall accuracy of almost 80% (0.77 Kappa ) for the 10 urban land cover classes both Beijign and Shanghai, compared to eCognition results of 75% (0.71 Kappa) In particular the detection of small linear features with respect to the image resolution such as roads in 30m resolved data went well with 83% user accuracy from KTH-SEG versus 57% user accuracy using the segments derived from eCognition. The other urban classes which in particular in SAR imagery are characterized by a high degree of heterogeneity were classified superiorly by KTH-SEG. ECognition in general performed better on vegetation classes such as grass, low vegetation and forest which are usually more homogeneous. It is was also found that the combination of ASAR and HJ-1B optical data was beneficial, increasing the final classification accuracy by at least 10% compared to ASAR or HJ-1B data alone. The results also further confirmed that a higher diversity of SAR type images is more important for the urban classification outcome. However, this is not the case when classifying high resolution TerraSAR-X strip-map imagery. Here the different image characteristics of different look angles, and orbit orientation created more confusion mainly due to the different layover and foreshortening effects on larger buildings. The TerraSAR-X results showed also that accurate urban classification can be achieved using high resolution SAR data alone with almost 84% for  eight classes around the Shanghai international Airport (high and low density built-up were not separated as well as roads and runways). For urban extent extraction, the results demonstrated that built-up areas can be effectively extracted using a single ENVISAT ASAR image in 10 global cities reaching overall accuracies around 85%, compared to 75% of MODIS urban class and 73% GlobCover Urban class. Multitemporal ASAR can improve the urban extraction results by 5-10% in Beijing. Mountain masking applied in Mumbai and Rio de Janeiro increased the accuracy by 3-5%.The research performed in  this thesis has contributed to the remote sensing community by providing algorithms and methods for both extracting urban areas and identifying urban land cover in a more detailed fashion. / <p>QC 20140625</p>