The overall goal of this thesis is to better understand changes in the spatial pattern of urban growth and its impact on landscape configuration by conducting a case study in Greater Chengdu, an inland megacity in China. The objectives are as follows: 1) Quantifying changes in the spatial pattern of the study area between 2003 and 2013; 2) Evaluating the degree of urban sprawl over that period; 3) Evaluating urban expansion dynamics; and 4) Examining and defining the types of urban growth. Satellite imagery was employed to distinguish and identify different land surface categories. Integrated remote sensing and GIS (Geographic Information System) technique was used to analyse both qualitative and quantitative perspectives regarding the objectives. The results indicate that the urban area of Greater Chengdu doubled from 525.5 km2 to 1191.85 km2 during 2003 to 2013. The geographic footprint demonstrates that the distribution of the built-up area was dispersed and continues to grow more dispersed. The dominant type of urban growth is outward expansion, by which the city grew within a 10 km to 25 km radius surrounding the city center. A substantial infill phenomenon exists between a 5 km and 10 km radius from the city center. The urban core boundary expanded outward by 5 km, while the fringe of suburban area expanded outward by 10 km during the time period, which both indicate a substantial outward expansion over the city. The significant contribution of this study could benefit to many aspects such as comparative studies between cities or continuous studies relevant to urban growth.

This thesis addresses three research gaps in published literature. These are, the absence of Object Based Image Analysis (OBIA) methods for urban Land Use and Land Cover (LULC) analysis in Nigeria; the inability to use Nigeriasat-1 satellite data for urban LULC analysis and monitoring urban growth in Nigeria with Shannon’s Entropy Index. Using Abuja as a case study, this research investigated the nature of land use/land cover change (LULCC). Specific objectives were: design of an object based classification method to extract urban LULC; validate a method to extract LULC in developing countries from multiple sources of remotely sensed data; apply the method to extract LULC data; use the outputs to validate an Urban Growth Model (UGM); optimise an UGM to represent patterns and trends and through this iterative process identify and prioritise the driving forces of urban change; and finally use the outputs of the land use maps to determine if planning has controlled land use development. Landsat 7 ETM (2001), Nigeriasat-1 SLIM (2003) and SPOT 5 HRG (2006) sensor data were merged with land use cadastre in OBIA, to produce land use maps. Overall classification accuracies were 92%, 89% and 96% respectively. Post classification analysis of LULCC indicated 4.43% annual urban spread. Shannon’s Entropy index for the study period were 0.804 (2001), 0.898 (2003) and 0.930 (2006). Cellular Automata/Markov analysis was also used to predict urban growth trend of 0.89% per annum. For the first time OBIA has been used for LULC analysis in Nigeria. This research has established that Nigeriasat-1 data can contribute to urban studies using innovative OBIA methods. In addition, that Shannon’s Entropy Index can be used to understand the nature of urban growth in Nigeria. Finally, the drivers of LULCC in Abuja are similar to those of planned capital cities in other developing economies. Land use developments in Abuja can provide an insight into urban dynamics in a developing country’s capital region. OBIA, Shannon’s Entropy Index and UGM can aid urban administrators and provide information for sustainable urban planning and development.

The science of curiosity is not fully understood, yet it seems to be a key component of nature which drives both humans and animals to seek out new information. Humans actively seek out to solve problems for the sake of solving them, with evidence suggesting that the seeking and obtaining of new knowledge is itself inherently rewarding. This study uses new methods to collect data to investigate how humans react when presented with novel environments and a problem to solve. Information gain was tracked using Shannon’s entropy, a measure of how effective a communication is at communicating its message across. The study investigates if participants feelings of satisfaction will increase the more information they receive, as measured by a change in Shannon’s entropy. A total of 44 participants with complete data were recruited accross two conditions A and B, with A containing a complete knowlege graph to determine what knowledge is gained through interactions with the environment and B containing more uncertainty so that the participant can be observed building their own knowledge-graph. Participants entered a virtual enviroment named Omosa where they were told about a mystery involving the deaths of herbivores on the island. Participants were given free reign to explore and investigate for a minimum 6 minutes. In increments of 90s, participants were asked questions about what they thought was killing the herd and how confident they were of their answer. After 6 minutes final questions were presented collecting player satisfaction and trait curiosity. Additional meta-data including trajectory and interactions were also collected. No significant results were gleaned due to high drop out and incomplete data. Methodology could be altered in future renditions to increase participation and reduce drop out. / Vetenskapen om nyfikenhet förstås inte helt, men det verkar vara en nyckelkomponent i naturen som driver både människor och djur att söka ny information. Människor försöker aktivt lösa problem för att lösa dem, med bevis som tyder på att att söka och få ny kunskap i sig är givande i sig. Denna studie använder nya metoder för att samla in data för att undersöka hur människor reagerar när de presenteras för nya miljöer och ett problem att lösa. Informationsvinster spårades med hjälp av Shannons entropi, ett mått på hur effektiv en kommunikation är för att kommunicera sitt budskap. Studien undersöker om deltagarnas känslor av tillfredsställelse kommer att öka mer information de får, mätt med en förändring i Shannons entropi. Totalt rekryterades 44 deltagare med fullständig data enligt två villkor A och B, där A innehöll en fullständig kunskapsgraf för att bestämma vilken kunskap som erhålls genom interaktioner med miljön och B som innehåller mer osäkerhet så att deltagaren kan observeras bygga sin egen kunskaps grafen. Deltagarna gick in i ett virtuellt miljö med namnet Omosa där de fick höra om ett mysterium som involverade djur av växtätare på ön. Deltagarna fick fri tid att utforska och undersöka i minst 6 minuter. I steg från 90-talet ställdes deltagarna frågor om vad de trodde dödade besättningen och hur säkra de var på svaret. Efter 6 minuter presenterades de sista frågorna för att samla spelarnas nöjdhet och dragkänslighet. Ytterligare metadata inklusive bana och interaktioner samlades också in. Inga signifikanta resultat samlades in på grund av högt bortfall och ofullständig data. Metodik kan ändras i framtida versioner för att öka deltagandet och minska bortfallet.

Cette thèse porte sur le lien entre la tomographie et la notion de copule. La tomographie à rayons X consiste à (re)construire la structure cachée d'un objet (une densité de matière, la distribution d'une quantité physique, ou une densité de loi conjointe) à partir de certaines données obtenues ou mesurées de l'objet (les projections, les radiographies, les densités marginales). Le lien entre les mesures et l'objet se modélise mathématiquement par la Transformée à Rayons X ou la Transformée de Radon. Par exemple, dans les problèmes d'imagerie en géométrie parallèle, lorsqu'on a seulement deux projections à deux angles de 0 et pi/2 (horizontale et verticale), le problème peut être identifié comme un autre problème très important en mathématique qui est la détermination d'une densité conjointe à partir de ses marginales. En se limitant à deux projections, les deux problèmes sont des problèmes mal posés au sens de Hadamard. Il faut alors ajouter de l'information a priori, ou bien des contraintes supplémentaires. L'apport principal de cette thèse est l'utilisation des critères de plusieurs entropies (Rényi, Tsallis, Burg, Shannon) permettant d'aboutir à une solution régularisée. Ce travail couvre alors différents domaines. Les aspects mathématiques de la tomographie via l'élément fondamental qui est la transformée de Radon. En probabilité sur la recherche d'une loi conjointe connaissant ses lois marginales d'où la notion de ``copule'' via le théorème de Sklar. Avec seulement deux projections, ce problème est extrêmement difficile. Mais en assimilant les deux projections (normalisées) aux densités marginales et l'image à reconstruire à une densité de probabilité, le lien se fait et les deux problèmes sont équivalents et peuvent se transposer dans le cadre statistique. Pour caractériser toutes les images possibles à reconstruire on a choisi alors l'outil de la théorie de probabilité, c'est-à-dire les copules. Et pour faire notre choix parmi les copules ou les images nous avons imposé le critère d'information a priori qui se base sur différentes entropies. L'entropie est une quantité scientifique importante car elle est utilisée dans divers domaines (en Thermodynamique, en théorie de l'information, etc). Ainsi, en utilisant par exemple l'entropie de Rényi nous avons découvert de nouvelles classes de copules. Cette thèse apporte de nouvelles contributions à l'imagerie, par l'interaction entre les domaines qui sont la tomographie et la théorie des probabilités et statistiques. / This thesis studies the relationship between Computed Tomography (CT) and the notion of copula. In X-ray tomography the objective is to (re)construct an image representing the distribution of a physical quantity (density of matter) inside of an object from the radiographs obtained all around the object called projections. The link between these images and the object is described by the X-ray transform or the Radon transform. In 2D, when only two projections at two angles 0 and pi/2 (horizontal and vertical) are available, the problem can be identified as another problem in mathematics which is the determination of a joint density from its marginals, hence the notion of copula. Both problems are ill-posed in the sense of Hadamard. It requires prior information or additional criteria or constraints. The main contribution of this thesis is the use of entropy as a constraint that provides a regularized solution to this ill-posed inverse problem. Our work covers different areas. The mathematics aspects of X-ray tomography where the fundamental model to obtain projections is based mainly on the Radon transform. In general this transform does not provide all necessary projections which need to be associated with certain regularization techniques. We have two projections, which makes the problem extremely difficult, and ill-posed but noting that if a link can be done, that is, if the two projections can be equated with marginal densities and the image to reconstruct to a probability density, the problem translates into the statistical framework via Sklar's theorem. And the tool of probability theory called "copula" that characterizes all possible reconstructed images is suitable. Hence the choice of the image that will be the best and most reliable arises. Then we must find techniques or a criterion of a priori information, one of the criteria most often used, we have chosen is a criterion of entropy. Entropy is an important scientific quantity because it is used in various areas, originally in thermodynamics, but also in information theory. Different types of entropy exist (Rényi, Tsallis, Burg, Shannon), we have chosen some as criteria. Using the Rényi entropy we have discovered new copulas. This thesis provides new contributions to CT imaging, the interaction between areas that are tomography and probability theory and statistics.