Sundarban Reserved Forest in Bangladesh is playing a significant role in local and national economy and is providing protection to the coastline as well as to the indigenous people. During the past decades and also in recent time this forest was heavily disturbed by human intervention in many aspects. As a consequence the resources of the forest are fragmenting, shrinking and declining, which in turn leads to an increasing failure of satisfying increasing demands both at local and national levels. Therefore accurate and continuously updated spatial information is needed for optimising forest management and environmental planning on both levels to support the fulfilment of urgent needs of sustainability of the forest. Considering the specific topography and the poor accessibility of the forest versus the task of collecting information, remote sensing is an attractive, if not the only means of obtaining sound full-coverage spatial information on forest cover of Sundarban. This research used medium resolution Landsat ETM data of November 2000 and Landsat TM data of January 1989 to assess and monitor the forest for 1. Identification of the operational tools for mapping and monitoring the forest as well as on the examination of the reliability of the application of multitemporal satellite remote sensing data for building spatial databases on forest cover in Sundarban. 2. Based on the existing management plan of the forest as well as the spectral properties of Landsat ETM imagery a level III classification system was developed. 3. This classification strategy was tested by applying several methods to achieve the classification result with the highest accuracy and thus to build the most reliable methodology for mapping forest cover in Sundarban. 4. Forest cover change was assessed for the period of eleven years. Significant changes have been observed due to illegal removal of trees from the forest although a governmental moratorium on banning timber extraction exists since 1989. 5. Development of an operational monitoring scheme by means of multitemporal satellite imagery analysis, which will allow concerned authorities to set up sustainable and appropriate monitoring of the Sundarban Reserved Forest. / Das Schutzgebiet des Sundarban Mangrovenwaldes in Bangladesh spielt eine entscheidende Rolle in Hinsicht auf nationale und lokale sozio-ökonomische und sozio-ökologische Aspekte. Das Waldgebiet stabilisiert nicht nur die Küstenlinie, sondern schützt auch die Bevölkerung vor den Einflüssen von Flutkatastrophen. Durch menschlichen Einfluss wurde die Region während der letzten Jahrzehnte mehr und mehr unmittelbar gestört. Der Rückgang des Ertrags an Ressourcen aus dem Wald führte zu wachsender Unzufriedenheit in der von diesen Nutzungs-möglichkeiten abhängigen Bevölkerung. Um eine Optimierung des Waldmanagements durchführen zu können, werden kontinuierliche und genaue raumbezogene Daten benötigt. Betrachtet man die spezifische Topographie und die schlechte Zugänglichkeit der Waldgebiete, so bietet die Fernerkundung eine attraktive Möglichkeit, raumbezogene Informationen für die großen Flächen des Sundurban Mangrovenwaldes zu erfassen. Zur Analyse und Überwachung der Waldgebiete wurden zwei Satellitenbild-Datensätze mit mittlerer Auflösung verwendet, und zwar Landsat ETM Daten aus dem Jahre 2000 (November) sowie Landsat TM Daten aus dem Jahre 1989 (Januar). Die zentralen Aktivitäten im Rahmen der Bearbeitung der Dissertation beziehen sich auf 1. die Identifikation der notwendigen Werkzeuge für eine erfolgreiche Kartierung und Überwachung der Waldgebiete sowie Untersuchung der Zuverlässigkeit multi-temporaler Fernerkundungsdaten für den Aufbau einer Datenbasis für die Kartierung von Waldbedeckungsarten im Untersuchungsgebiet des Sunderban Mangroven-waldes, 2. die Entwicklung eines Klassifikationssystems nach dem USGS-Schlüssel (Auflösungsebene III) auf Grundlage des existierenden Managementplanes und der spektralen Qualität der Landsat ETM Satellitenbilddaten, 3. den Test der Klassifikationsstrategie durch Adaption unterschiedlicher Methoden und Optimierung in bezug auf Erzielung eines Ergebnisses in maximal erreichbarer Genauigkeit als Ausgangspunkt für den Aufbau einer Methodologie zum Monitoring des Sunderban Mangrovenwaldes, 4. die Extraktion der Veränderungen der Waldbedeckung über ein Zeitintervall von 11 Jahren mit weitreichenden Erkenntnissen zur Dynamik der Degradations-effekte, die hauptsächlich durch illegales Fällen trotz Verbot durch ein Regierungs-memorandum seit 1989 beschleunigt wird, 5. die Entwicklung einer operationellen Monitoring-Struktur mit Hilfe von multi-temporaler Satellitenbildanalyse für ein nachhaltiges und angepasstes raumbezo-genes Management des Sunderban-Mangrovenwaldes.

<p>This research assessed landuse changes and trends in vegetation cover in the Sandveld, using remote sensing images. Landsat TM satellite images of 1990, 2004 and 2007 were classified using the maximum likelihood classifier into seven landuse classes, namely water, agriculture, fire patches, natural vegetation, wetlands, disturbed veld, and open sands. Change detection using remote sensing algorithms and landscape metrics was performed on these multi-temporal landuse maps using the Land Change Modeller and Patch Analyst respectively. Markov stochastic modelling techniques were used to predict future scenarios in landuse change based on the classified images and their transitional probabilities. MODIS NDVI multi-temporal datasets with a 16day temporal resolution were used to assess seasonal and annual trends in vegetation cover using time series analysis (PCA and time profiling).Results indicated that natural vegetation decreased from 46% to 31% of the total landscape between 1990 and 2007 and these biodiversity losses were attributed to an increasing agriculture footprint. Predicted future scenario based on transitional probabilities revealed a continual loss in natural habitat and increase in the agricultural footprint. Time series analysis results (principal components and temporal profiles) suggested that the landscape has a high degree of overall dynamic change with pronounced inter and intra-annual changes and there was an overall increase in greenness associated with increase in agricultural activity. The study concluded that without future conservation interventions natural habitats would continue to disappear, a condition that will impact heavily on biodiversity and significant waterdependent ecosystems such as wetlands. This has significant implications for the long-term provision of water from ground water reserves and for the overall sustainability of current agricultural practices.</p>

In recent years landscape-scale fires have occurred in mainland Southeast Asia, including important protected areas (PAs). There has been increasing concern that landscape-scale fires are degrading the seasonally dry evergreen forest (SEF) element of the forest mosaic to more open deciduous forest and savanna, with serious implications for biodiversity conservation. Present management approaches, including fire suppression and prescribed burning, have not been effective managing for landscape-scale fire. Research was undertaken to investigate the occurrence, cause, effect, frequency and predictability of fire in SEF. SEF has the greatest species biodiversity in the forest mosaic and is potentially the most affected by fire, yet little research has been done on fire in SEF in mainland Southeast Asia. Huai Kha Khaeng (HKK) Wildlife Sanctuary in Thailand was selected as the study area. The objectives included: 1) investigate the area of SEF burned in HKK from 1988 to 2002; 2) investigate the conditions for fire in SEF; 3) determine whether the area of SEF in HKK declined as a result of fire; 4) determine the frequency of fire season years between 1984 and 2001 with the conditions for fire spread in SEF; and 5) determine whether there is a significant relationship between pre-fire season drought codes (Keetch-Byram Drought Index (KBDI) and Canadian Drought Code (DC)) and identified SEF fire season years for 1981 to 2003. Methods included: development of a Landsat fire history with associated interviews and reconnaissance field checks; fieldwork lighting test fires and measuring fuel characteristics; remote sensing change detection work using Landsat imagery; generation of a twenty-one year daily relative humidity minimum record for SEF; and logistic regression of the pre-fire season drought code values with identified SEF ‘fire’ and ‘non-fire’ years. Results showed: 1. Extensive areas of SEF have burned, but that Landsat imagery was not suitable for detecting fire in intact SEF. 2. SEF burned in years when there were fires burning adjacent to SEF in mid March and the moisture content of the SEF leaf litter fuel was less than 15%. 3. Fifteen percent of SEF in HKK has been either degraded or converted to deciduous forest forms in 12 years. 4. Conditions for fire spread in SEF occurred four times in 17 consecutive years. 5. A significant relationship exists between both the Keetch-Byram Drought Code (KBDI) and Canadian Drought Code (DC) and the SEF fire years. Implications are that large-scale fires have adversely affected intact SEF in HKK, and that the current damaging situation can be expected to continue. Whereas the extent of burning in intact SEF is not known, the need to manage the situation is immediate. Landscape-scale fires in HKK can be managed by using January 31st drought code values to predict potential large-scale fire years, followed by an aggressive fire suppression campaign in those years. In other years, fires can be allowed to burn without serious threat to the forest mosaic, and should to some extent be encouraged to maintain open deciduous forests and savanna. Additional research is required to determine whether a similar approach can be used for protected areas in other parts of the region.

La réussite du lancement d'un grand nombre des satellites Radar à Synthèse d'Ouverture (RSO - SAR) de nouvelle génération a fourni régulièrement des images SAR et SAR polarimétrique (PolSAR) multitemporelles à haute et très haute résolution spatiale sur de larges régions de la surface de la Terre. Le système SAR est approprié pour des tâches de surveillance continue ou il offre l'avantage d'être indépendant de l'éclairement solaire et de la couverture nuageuse. Avec des données multitemporelles, l'information spatiale et temporelle peut être exploitée simultanément pour rendre plus concise, l'extraction d'information à partir des données. La détection de changement de structures spécifiques dans un certain intervalle de temps nécessite un traitement complexe des données SAR et la présence du chatoiement (speckle) qui affecte la rétrodiffusion comme un bruit multiplicatif. Le but de cette thèse est de fournir une méthodologie pour simplifier l'analyse des données multitemporelles SAR. Cette méthodologie doit bénéficier des avantages d'acquisitions SAR répétitives et être capable de traiter différents types de données SAR (images SAR mono-, multi- composantes, etc.) pour diverses applications. Au cours de cette thèse, nous proposons tout d'abord une méthode générale basée sur une matrice d'information spatio-temporelle appelée Matrice de détection de changement (CDM). Cette matrice contient des informations de changements obtenus à partir de tests croisés de similarité sur des voisinages adaptatifs. La méthode proposée est ensuite exploitée pour réaliser trois tâches différentes: 1) la détection de changement multitemporel avec différents types de changements, ce qui permet la combinaison des cartes de changement entre des paires d'images pour améliorer la performance de résultat de détection de changement; 2) l'analyse de la dynamicité de changement de la zone observée, ce qui permet l'étude de l'évolution temporelle des objets d'intérêt; 3) le filtrage nonlocal temporel des séries temporelles d'images SAR/PolSAR, ce qui permet d'éviter le lissage des informations de changement dans des séries pendant le processus de filtrage.Afin d'illustrer la pertinence de la méthode proposée, la partie expérimentale de la thèse est effectuée sur deux sites d'étude: Chamonix Mont-Blanc, France et le volcan Merapi, Indonésie, avec différents types de changements (i.e. évolution saisonnière, glaciers, éruption volcanique, etc.). Les observations de ces sites d'étude sont acquises sur quatre séries temporelles d'images SAR monocomposantes et multicomposantes de moyenne à haute et très haute résolution: des séries temporelles d'images Sentinel-1, ALOS-PALSAR, RADARSAT-2 et TerraSAR-X. / A large number of successfully launched and operated Synthetic Aperture Radar (SAR) satellites has regularly provided multitemporal SAR and polarimetric SAR (PolSAR) images with high and very high spatial resolution over immense areas of the Earth surface. SAR system is appropriate for monitoring tasks thanks to the advantage of operating in all-time and all-weather conditions. With multitemporal data, both spatial and temporal information can simultaneously be exploited to improve the results of researche works. Change detection of specific features within a certain time interval has to deal with a complex processing of SAR data and the so-called speckle which affects the backscattered signal as multiplicative noise.The aim of this thesis is to provide a methodology for simplifying the analysis of multitemporal SAR data. Such methodology can benefit from the advantages of repetitive SAR acquisitions and be able to process different kinds of SAR data (i.e. single, multipolarization SAR, etc.) for various applications. In this thesis, we first propose a general framework based on a spatio-temporal information matrix called emph{Change Detection Matrix} (CDM). This matrix contains temporal neighborhoods which are adaptive to changed and unchanged areas thanks to similarity cross tests. Then, the proposed method is used to perform three different tasks:1) multitemporal change detection with different kinds of changes, which allows the combination of multitemporal pair-wise change maps to improve the performance of change detection result;2) analysis of change dynamics in the observed area, which allows the investigation of temporal evolution of objects of interest;3) nonlocal temporal mean filtering of SAR/PolSAR image time series, which allows us to avoid smoothing change information in the time series during the filtering process.In order to illustrate the relevancy of the proposed method, the experimental works of the thesis is performed on four datasets over two test-sites: Chamonix Mont-Blanc, France and Merapi volcano, Indonesia, with different types of changes (i.e., seasonal evolution, glaciers, volcanic eruption, etc.). Observations of these test-sites are performed on four SAR images time series from single polarization to full polarization, from medium to high, very high spatial resolution: Sentinel-1, ALOS-PALSAR, RADARSAT-2 and TerraSAR-X time series.

Ce travail de thèse propose une nouvelle approche ponctuelle pour l'analyse de texture dans l'imagerie de télédétection à très haute résolution (THR). Cette approche ne prend en compte que des points caractéristiques, et non pas tous les pixels dans l'image, pour représenter et caractériser la texture. Avec l'augmentation de la résolution spatiale des capteurs satellitaires, les images THR ne vérifient que faiblement l'hypothèse de stationnarité. Une telle approche devient donc pertinente étant donné que seuls l'interaction et les caractéristiques des points-clés sont exploitées. De plus, puisque notre approche ne considère pas tous les pixels dans l'image comme le font la plupart des méthodes denses de la littérature, elle est plus à-même de traiter des images de grande taille acquises par des capteurs THR. Dans ce travail, la méthode ponctuelle est appliquée en utilisant des pixels de maxima locaux et minima locaux (en intensité) extraits à partir de l'image. Elle est intégrée dans plusieurs chaînes de traitement en se fondant sur différentes techniques existantes telles la théorie des graphes, la notion de covariance, la mesure de distance géométrique, etc. En conséquence, de nombreuses applications basées sur la texture sont abordées en utilisant des données de télédétection (images optiques et radar), telles l'indexation d'images, la segmentation, la classification et la détection de changement, etc. En effectuant des expériences dédiées à chaque application thématique, la pertinence et l'efficacité du cadre méthodologique proposé sont confirmées et validées. / This thesis work proposes a novel pointwise approach for texture analysis in the scope of very high resolution (VHR) remote sensing imagery. This approach takes into consideration only characteristic pixels, not all pixels of the image, to represent and characterize textural features. Due to the fact that increasing the spatial resolution of satellite sensors leads to the lack of stationarity hypothesis in the acquired images, such an approach becomes relevant since only the interaction and characteristics of keypoints are exploited. Moreover, as this technique does not need to consider all pixels inside the image like classical dense approaches, it is more capable to deal with large-size image data offered by VHR remote sensing acquisition systems. In this work, our pointwise strategy is performed by exploiting the local maximum and local minimum pixels (in terms of intensity) extracted from the image. It is integrated into several texture analysis frameworks with the help of different techniques and methods such as the graph theory, the covariance-based approach, the geometric distance measurement, etc. As a result, a variety of texture-based applications using remote sensing data (both VHR optical and radar images) are tackled such as image retrieval, segmentation, classification, and change detection, etc. By performing dedicated experiments to each thematic application, the effectiveness and relevance of the proposed approach are confirmed and validated.

Suite aux changements climatiques, de nouveaux paysages reflétant les interactions entre les processus naturels et les activités humaines inappropriées sont apparus en Tunisie Méridionale. L’érosion éolienne en est l’une des manifestations les plus remarquables. Au cours de cette thèse, une méthodologie opérationnelle et validée (méthode du transect permanent) a été mise au point pour la caractérisation des états de surfaces éolisés et la quantification du bilan sédimentaire d’un transect d’environ 500m de longueur sur une période de deux ans. A l’échelle spatiale, la cartographie des Unités Eoliennes : zones de départ, transit et dépôt de sable a été élaborée. Un essai de caractérisation radiométrique des zones de dépôt ensablées a été ensuite tenté pour l’analyse diachronique des changements survenus durant plus de 35 ans. A l’échelle stationnelle, la méthode du transect permanent permet le calcul diachronique des bilans sédimentaires et la comparaison simultanée des changements des Complexes d’Etat de Surface. La seule observation des états de surface éolisés est insuffisante pour déterminer le fonctionnement éolien précis d’une région, elle induit à des erreurs d’interprétation sur les processus sédimentaires en cours.A l’échelle spatiale, les cartes des Unités Eoliennes permettent de déterminer la vulnérabilité du milieu face aux processus de déflation, transport et dépôt. De plus, la caractérisation des zones ensablées par des indices radiométriques n’est pas évidente avec des images de 30 m de résolution. Les analyses statistiques effectuées ont montré que l’indice de couleur est le plus indiqué pour ce genre d’étude. Le calcul des taux de changement entre deux images de dates successives permet d’estimer l’évolution temporelle des espaces ensablés et la distribution spatiale des zones nouvellement ensablées sur plus de 35 ans. / Under the effect of climate change, new landscapes reflecting the interactions between natural processes and human inappropriate activities appeared in Southern Tunisia. Wind erosion is one of the most important events. In this thesis, operational and validated methodology (the permanent transect method) has been developed for the characterization of Surfaces States and quantification of the sediment balance of a 500 m length transect over a period of two years. On spatial scale, mapping of the Aeolian units of deflation, transit and sand deposit was developed. Radiometric characterization of sand accumulations was then tried for the detection of changes that occurred within more than 35 years.At the site level, the permanent transect method enabeled the diachronic sedimentary balance calculation and the comparison of the Surface states changes. The single observation of these areas is insufficient to determine the real eolian process of a region ; moreover it induces to errors of interpretation on the sedimentary process.At the spatial scale, maps of the Aeolian units enabeled to determine the vulnerability of the environment to the process of deflation, transport and deposition. In addition, the characterization of sand accumulations by radiometric indices is not obvious within 30 m resolution images. The statistical analyses have shown that Color Index is the most indicated for this type of study. The calculation of the rates of change between two successive dates images allows to estimate the sandy spaces evolution and their spatial distribution for more than 35 years.

Magister Scientiae (Biodiversity and Conservation Biology) - MSc (Biodiv and Cons Biol) / This research assessed landuse changes and trends in vegetation cover in the Sandveld, using remote sensing images. Landsat TM satellite images of 1990, 2004 and 2007 were classified using the maximum likelihood classifier into seven landuse classes, namely water, agriculture, fire patches, natural vegetation, wetlands, disturbed veld, and open sands. Change detection using remote sensing algorithms and landscape metrics was performed on these multi-temporal landuse maps using the Land Change Modeller and Patch Analyst respectively. Markov stochastic modelling techniques were used to predict future scenarios in landuse change based on the classified images and their transitional probabilities. MODIS NDVI multi-temporal datasets with a 16day temporal resolution were used to assess seasonal and annual trends in vegetation cover using time series analysis (PCA and time profiling).Results indicated that natural vegetation decreased from 46% to 31% of the total landscape between 1990 and 2007 and these biodiversity losses were attributed to an increasing agriculture footprint. Predicted future scenario based on transitional probabilities revealed a continual loss in natural habitat and increase in the agricultural footprint. Time series analysis results (principal components and temporal profiles) suggested that the landscape has a high degree of overall dynamic change with pronounced inter and intra-annual changes and there was an overall increase in greenness associated with increase in agricultural activity. The study concluded that without future conservation interventions natural habitats would continue to disappear, a condition that will impact heavily on biodiversity and significant waterdependent ecosystems such as wetlands. This has significant implications for the long-term provision of water from ground water reserves and for the overall sustainability of current agricultural practices. / South Africa

Mobile widgets now form a new paradigm of simplified web. Probably, the best experience of the Web is when a user has a widget for every frequently executed task, and can execute it anytime, anywhere on any device. However, the current method of programmatically creating personally relevant mobile widgets for every user does not scale. Creation of these mobile web widgets requires application programming as well as knowledge of web-related protocols. Furthermore, these mobile widgets are also limited to smart phones with data connectivity and such smart phones form just about 15% of the mobile phones in India. How do we make web accessible on devices that most people can afford? How does one create simple relevant tasks for the numerous diverse needs of every person? In this thesis, we attempt to address these issues and propose a new method of web simplification that enables an end-user to create simple single-click widgets for a complex personal task - without any programming. The proposed solution enables even low-end phones to access personal web tasks over SMS and voice. We propose a system that enables end users to create personal widgets via programming-by-browsing. A new concept called Tasklets to represent a user’s personal interaction, and a notion of programming over websites using a Web Virtual Machine are presented. Ensuring correct execution of these end user widgets posed interesting problems in web data mining and required us to investigate new methods to characterize and semantically model browser-based interactions. In particular, an instruction set for programming over web sites, new domain-specific similarity measures using ontologies, algorithms for frequent-pattern mining of web interactions and change detection with a proof of its NP-completeness are presented. A quantitative metric to measure the interaction complexity of web browsing and a method of classifying relational data using semantics hidden in the schema are introduced as well. This new web architecture to enable multi-device access to user's personal tasks over low-end phones was piloted with real users, as a solution named SiteOnMobile, and has received very positive response.

Au cours des dernières années, la cartographie urbaine 3D a suscité un intérêt croissant pour répondre à la demande d’applications d’analyse des scènes urbaines tournées vers un large public. Conjointement les techniques d’acquisition de données 3D progressaient. Les travaux concernant la modélisation et la visualisation 3D des villes se sont donc intensifiés. Des applications fournissent au plus grand nombre des visualisations efficaces de modèles urbains à grande échelle sur la base des imageries aérienne et satellitaire. Naturellement, la demande s’est portée vers des représentations avec un point de vue terrestre pour offrir une visualisation 3D plus détaillée et plus réaliste. Intégrées dans plusieurs navigateurs géographiques comme Google Street View, Microsoft Visual Earth ou Géoportail, ces modélisations sont désormais accessibles et offrent une représentation réaliste du terrain, créée à partir des numérisateurs mobiles terrestres. Dans des environnements urbains, la qualité des données obtenues à partir de ces véhicules terrestres hybrides est largement entravée par la présence d’objets temporairement statiques ou dynamiques (piétons, voitures, etc.) dans la scène. La mise à jour de la cartographie urbaine via la détection des modifications et le traitement des données bruitées dans les environnements urbains complexes, l’appariement des nuages de points au cours de passages successifs, voire la gestion des grandes variations d’aspect de la scène dues aux conditions environnementales constituent d’autres problèmes délicats associés à cette thématique. Plus récemment, les tâches de perception s’efforcent également de mener une analyse sémantique de l’environnement urbain pour renforcer les applications intégrant des cartes urbaines 3D. Dans cette thèse, nous présentons un travail supportant le passage à l’échelle pour la cartographie 3D urbaine automatique incorporant la reconnaissance et l’intégration temporelle. Nous présentons en détail les pratiques actuelles du domaine ainsi que les différentes méthodes, les applications, les technologies récentes d’acquisition des données et de cartographie, ainsi que les différents problèmes et les défis qui leur sont associés. Le travail présenté se confronte à ces nombreux défis mais principalement à la classification des zones urbaines l’environnement, à la détection automatique des changements, à la mise à jour efficace de la carte et l’analyse sémantique de l’environnement urbain. Dans la méthode proposée, nous effectuons d’abord la classification de l’environnement urbain en éléments permanents et temporaires. Les objets classés comme temporaire sont ensuite retirés du nuage de points 3D laissant une zone perforée dans le nuage de points 3D. Ces zones perforées ainsi que d’autres imperfections sont ensuite analysées et progressivement éliminées par une mise à jour incrémentale exploitant le concept de multiples passages. Nous montrons que la méthode d’intégration temporelle proposée permet également d’améliorer l’analyse sémantique de l’environnement urbain, notamment les façades des bâtiments. Les résultats, évalués sur des données réelles en utilisant différentes métriques, démontrent non seulement que la cartographie 3D résultante est précise et bien mise à jour, qu’elle ne contient que les caractéristiques permanentes exactes et sans imperfections, mais aussi que la méthode est également adaptée pour opérer sur des scènes urbaines de grande taille. La méthode est adaptée pour des applications liées à la modélisation et la cartographie du paysage urbain nécessitant une mise à jour fréquente de la base de données. / Over the years, 3D urban cartography has gained widespread interest and importance in the scientific community due to an ever increasing demand for urban landscape analysis for different popular applications, coupled with advances in 3D data acquisition technology. As a result, in the last few years, work on the 3D modeling and visualization of cities has intensified. Lately, applications have been very successful in delivering effective visualizations of large scale models based on aerial and satellite imagery to a broad audience. This has created a demand for ground based models as the next logical step to offer 3D visualizations of cities. Integrated in several geographical navigators, like Google Street View, Microsoft Visual Earth or Geoportail, several such models are accessible to large public who enthusiastically view the real-like representation of the terrain, created by mobile terrestrial image acquisition techniques. However, in urban environments, the quality of data acquired by these hybrid terrestrial vehicles is widely hampered by the presence of temporary stationary and dynamic objects (pedestrians, cars, etc.) in the scene. Other associated problems include efficient update of the urban cartography, effective change detection in the urban environment and issues like processing noisy data in the cluttered urban environment, matching / registration of point clouds in successive passages, and wide variations in environmental conditions, etc. Another aspect that has attracted a lot of attention recently is the semantic analysis of the urban environment to enrich semantically 3D mapping of urban cities, necessary for various perception tasks and modern applications. In this thesis, we present a scalable framework for automatic 3D urban cartography which incorporates recognition and temporal integration. We present in details the current practices in the domain along with the different methods, applications, recent data acquisition and mapping technologies as well as the different problems and challenges associated with them. The work presented addresses many of these challenges mainly pertaining to classification of urban environment, automatic change detection, efficient updating of 3D urban cartography and semantic analysis of the urban environment. In the proposed method, we first classify the urban environment into permanent and temporary classes. The objects classified as temporary are then removed from the 3D point cloud leaving behind a perforated 3D point cloud of the urban environment. These perforations along with other imperfections are then analyzed and progressively removed by incremental updating exploiting the concept of multiple passages. We also show that the proposed method of temporal integration also helps in improved semantic analysis of the urban environment, specially building façades. The proposed methods ensure that the resulting 3D cartography contains only the exact, accurate and well updated permanent features of the urban environment. These methods are validated on real data obtained from different sources in different environments. The results not only demonstrate the efficiency, scalability and technical strength of the method but also that it is ideally suited for applications pertaining to urban landscape modeling and cartography requiring frequent database updating.

This thesis investigates decision-making in two-player imperfect information games against opponents whose actions can affect our rewards, and whose strategies may be based on memories of interaction, or may be changing, or both. The focus is on modelling these dynamic opponents, and using the models to learn high-reward strategies. The main contributions of this work are: 1. An approach to learn high-reward strategies in small simultaneous-move games against these opponents. This is done by using a model of the opponent learnt from sequence prediction, with (possibly discounted) rewards learnt from reinforcement learning, to lookahead using explicit tree search. Empirical results show that this gains higher average rewards per game than state-of-the-art reinforcement learning agents in three simultaneous-move games. They also show that several sequence prediction methods model these opponents effectively, supporting the idea of using them from areas such as data compression and string matching; 2. An online expectation-maximisation algorithm that infers an agent's hidden information based on its behaviour in imperfect information games; 3. An approach to learn high-reward strategies in medium-size sequential-move poker games against these opponents. This is done by using a model of the opponent learnt from sequence prediction, which needs its hidden information (inferred by the online expectation-maximisation algorithm), to train a state-of-the-art no-regret learning algorithm by simulating games between the algorithm and the model. Empirical results show that this improves the no-regret learning algorithm's rewards when playing against popular and state-of-the-art algorithms in two simplified poker games; 4. Demonstrating that several change detection methods can effectively model changing categorical distributions with experimental results comparing their accuracies to empirical distributions. These results also show that their models can be used to outperform state-of-the-art reinforcement learning agents in two simultaneous-move games. This supports the idea of modelling changing opponent strategies with change detection methods; 5. Experimental results for the self-play convergence to mixed strategy Nash equilibria of the empirical distributions of plays of sequence prediction and change detection methods. The results show that they converge faster, and in more cases for change detection, than fictitious play.