The natural characteristics of protected areas have changed for a variety of reasons through time. Changes in protected area landscapes can occur because of natural and/or cultural processes. Natural processes such as geomorphological disturbance and climatic condition can permanently and/or temporarily change the characteristics of the environment. In addition, changes in human needs, knowledge and activities are the cultural driving forces behind changing characteristics of landscape through time. These changes can be studied both spatially and temporally. Spatially, protected area landscape structures such as shape, size and location with respect to their neighbourhood context can be studied to describe landscape configuration. Temporally, landscape functions such as different geographical locations and land characteristics can be studied to determine the rate of temporal variability in landscape. Any changes in temporal characteristics may lead to changes in spatial characteristics of protected areas and vice versa. This thesis has developed a framework to enhance the landscape ecological planning approach with attention to changes in landscapes of protected areas. Considering landscape ecological concepts, this framework draws upon spatial and temporal characteristics of protected areas. Initially, a basic model of the landscape ecological approach to protected area planning and data requirements for landscape ecological planning was developed according to the concept of landscape ecological planning. In order to examine the model in the real world, the data requirements for landscape ecological planning were implemented using a case study method. The basic list of data required for landscape ecological planning was further developed through the case study approach by highlighting the importance of road metrics in the process of planning. In addition, the case study approach proved that spatial and temporal metrics can be used in the interpretation of spatial configuration and temporal variability of protected areas th rough a quantitative method. The framework was developed for three case studies in Iran and three case studies in Australia. A number of metrics were applied in order to quantify spatial and temporal aspects of the protected areas. A list of spatial and temporal criteria was developed to assist interpretation of area compaction, spatial fragmentation and temporal variability of protected areas. Using the criteria list, a new framework for spatial and temporal evaluation of protected areas has been developed. This can be used to determine spatial and temporal management issues of protected areas at the landscape scale. Then planning scenarios for spatial and temporal issues of protected areas at the landscape scale can be suggested. The developed framework has the potential to be applied to all protected areas even where detailed ecological data and information are not available. In addition, when all data required are available, the developed framework using spatial and temporal metrics has the potential to suggest a flexible zoning plan for protected areas.

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Supporting huge population, megacities are definitely the hot spots of production, consumption, and waste generation. Without careful investment and planning, megacities will be overwhelmed by burgeoning negative impacts on the environment, natural resources, and human health, as well as a host of social and economic issues. The unprecedented combination of economic and population growth since the Reform and Open Policy has led China into transition from a largely rural society to a predominantly urban one. Chinese cities, without question, have not escaped the danger of the series of problems during the rapid progress of urbanization. Therefore, monitoring the spatial-temporal patterns of urban sprawl and their impact on the environment is of critical importance for urban planning and sustainable development, especially in developing Chinese cities such as Shanghai. To date, few studies have focused on the urban trajectories of Shanghai over the past 30 years from a remote sensing perspective. Most of the studies were concentrated on the technical issues of image processing and classification. Moreover, research on spatial metrics has focused on analyzing remote sensing classification results rather than on the use of interpreting, assessing, and verifying urban simulation results. Furthermore, many researches merely focused on baseline projection and very few studies took into consideration urban growth scenarios so far. As yet there have been no reported scenario simulations of future Shanghai growth with several land-use categories within urban areas. The overall objective of this research is to investigate the integration of remote sensing, spatial metrics, and spatial-temporal models in the monitoring, analysis, and simulation of urban growth in Shanghai, China. The specific objectives are to: 1). monitor urban dynamics over time with multi-sensor remote sensing images; 2). quantify spatial-temporal properties of urban growth and representing the urban morphological structures by means of spatial metrics; and 3). simulate the geographic extent, patterns, and detailed catalogs of urban growth under different scenarios using Markov-Cellular Automata (Markov-CA) model to support decision making for a more sustainable Shanghai. Through this study, the combined approach using remotely sensed data with change detection techniques, spatial metrics, and a scenarios-based simulation model proved to be effective to understand, represent, and predict the spatial-temporal dynamics of urban growth. In detail, the segmented-based hierarchy classification and visual interpretation were effective methods to extract urban and industrial land with high-resolution remotely sensed images. Direct change detection using variables derived from tasseled cap transformation was efficient for monitoring impervious surface sprawl. Spatial metrics is a quick and executable way to assessing the impact of urban sprawl on landscape dynamic. Markov-CA model is a useful tool to simulate the scenarios of future urban developments and therefore provides the policy options for sustainable urban planning. The research results of urban trajectories and impervious surface sprawl showed that Shanghai experienced high-speed urban sprawl and the rate of urban expansion, however, was not homogeneous spatially and temporally. The general annual urban expansion speed was 34.8 km2 per year; nevertheless, it reached 80.2 km2 per year recent six years from 2001 to 2007, while it touched the bottom speed around 14.3 km2 per year during 1979-1989. The expanded area in the Puxi region was 5.23 times of its original area while that of Pudong region was 19.94 times of its original area during 1979-2007. The research results of landscape analysis demonstrated that greenbelt becomes fractured while infrastructural and commercial area is more and more aggregated in the central Shanghai area, and satellite images such as SPOT Pan, XS and Landsat TM with 10-30 meter resolution are sufficient for the landscape dynamic research in central Shanghai area. The results of scenarios-based simulation indicated that built-up areas in Shanghai will increase significantly in 2025 and Shanghai will experience less urban sprawl and retain a better environment in 2025 under service-oriented center (SOC) than under baseline (NS) or manufacturing-dominant center (MDC) scenario. If favorable policy for MDC scenario is adopted, however, there will be a lot of manufacturing industries gathering in Shanghai and more agricultural lands will be encroached. The present research focused on the analysis of physical and morphological aspects of urban growth. Urban land-use dynamics are, however, intrinsically linked with socio-economic, political, or demographic drivers. Trying to fill in the missing link between traditional urban geography and urban remote sensing & urban simulation and to improve understanding of the interactions between human and natural aspects in the urban socio-ecosystem is the major focus in the next phase of the Ph.D. research. Keywords: Urban growth, Spatial-temporal pattern, Remote sensing, Spatial metrics, Scenarios-based simulation, Shanghai / QC 20110224

Depuis les années 1960, les villes françaises sont soumises à un processus d'étalement urbain. Cet étalement se traduit par l'émergence d'une catégorie d'espace située à l'interface entre la ville et la campagne : le périurbain. Les caractéristiques sociales, urbanistiques, ou liées aux pratiques spatiales de ses habitants confèrent au périurbain une singularité et une spécificité propres. Il s'agit d'un espace de contradiction qui attire à la fois en raison du cadre de vie plutôt « naturel » qu'il offre aux ménages, mais également en raison de sa proximité avec la ville et des potentialités liées à l'accessibilité à diverses aménités urbaines.Pour comprendre plus finement cet engouement pour le périurbain, cette thèse propose d'explorer la relation individu-environnement résidentiel sous l'angle de la satisfaction que retirent les individus de leur cadre de vie. Il s'agit de mettre en relation une information de nature cognitive avec une information de nature spatiale. En modélisant chacune de ces composantes par l'utilisation d'indicateurs spécifiques, divers modèles statistiques sont mobilisés pour mettre en lumière les attributs spatiaux du cadre de vie susceptibles d'avoir une influence sur la satisfaction des individus.L'approche modélisatrice est centrale dans la démarche suivie. Après voir mené une enquête de satisfaction sur plus d'un millier de ménages vivant dans un secteur périurbain de Besançon, la démarche s'est attelée à construire des indicateurs en vue de caractériser deux types d'aménités de leur environnement résidentiel : le paysage et l'accessibilité aux commerces et services. Chacune de ces aménités est ensuite intégrée dans des modèles statistiques permettant d'évaluer leur contribution dans le degré de satisfaction du ménage.La démarche, essentiellement modélisatrice et exploratoire, offre toutefois des perspectives intéressantes dans le domaine de l'aménagement du territoire et de la planification urbaine. En ayant recours à des modèles simples et reproductibles, il s'agit de d'établir des documents cartographiques décrivant le potentiel de satisfaction à grande échelle. / Since the 1960s, French cities are concerned with an urban sprawl process. This urban sprawl leads to the emergence of a particular space located at the interface between the city and the countryside: the periurban. The social, morphological or the spatial practices of its inhabitants give the suburban a particular singularity and specificity. It is a space of contradiction that attracts both because of the "natural" living environment that it provides to households, but also because of its proximity to the city and the opportunities related to accessibility to various urban amenities.To understand more precisely this enthusiasm for periurban areas, this thesis proposes to explore the individual-residential environment relationship in terms of the satisfaction. The aim is to link a cognitive information with a spatial information. By modeling each of these components by the use of specific indicators, various statistical models are used to highlight the spatial attributes of the living environment that influence the satisfaction level of individuals.The modeling approach is central in this thesis. After the establishment of a satisfaction survey conducted on more than one thousand households living in a suburban area of ​​Besancon, the process is to build indicators to characterize two types of residential amenities: the landscape and the accessibility to shops and services. Each of these amenities is then incorporated into statistical models to assess their contribution to the satisfaction of the household.The approach essentially modeling and exploratory offers interesting perspectives in the field of urban planning. By using basic and reproducible models, one of the objectives is to build mapping documents describing the potential of satisfaction on a large scale.

China is engaged in the largest healthcare construction program in history, expecting to build more than 2,000 hospitals and a large number of healthcare facilities at all scale over the next few years. This once-in-a-lifetime construction boom provides a valuable opportunity to rethink Chinese hospital design, and especially to consider how to design modern hospitals that are effective and efficient in delivering care, and are responsive to the cultural needs of the Chinese people as well. This dissertation seeks to rigorously define these issues and develop metrics that link design to key healthcare processes. This study uses a range of concepts and analysis tools drawn from cross-culture organizational communications, evidence-based design, space syntax and other research traditions. This thesis develops and refines metrics for four main drivers of nursing unit design: space economy, staff efficiency, natural light and cultural preferences for communication. Communication among Chinese healthcare workers is strongly influenced by cultural preferences for patterns of authority and decision-making reflected in organizational culture and rooted in Confucian principles of hierarchical social structure (Dengji), social network (Guanxi) and face (Mianzi). While the dissertation builds on a longstanding tradition of research focusing on healthcare space economy and staff efficiency, new measures for cultural preferences are proposed and tested. Based on emerging theories of cross-cultural organizational communication by Hofstede and other scholars, and space syntax, this study particularly explores how cultural preferences for face-to-face communication are reflected in the design of Chinese nursing units. Based on the proposed metrics, the dissertation analyzes six pairs of Chinese and US nursing units, matched on layout type. While the Chinese nursing units appear Western, deeper quantitative analysis of their layouts reveals significant national differences in the application of unit typologies in China when compared to those in the U.S. It shows that Chinese hospital design is rooted in cultural preferences such as for positive energy (qi) based on Fengshui theory, and in Confucian principles of hierarchy, social networking and face.

Orientador: Gustavo Garcia Manzato / Resumo: O trabalho apresentado teve como objetivo principal avaliar as relações entre características espaciais das cidades e a resiliência em relação à mobilidade urbana, considerando os diferentes portes de municípios, em um estudo aplicado para o estado de São Paulo. Para atingir tal objetivo, foi proposto o desenvolvimento de um método de avaliação da resiliência na mobilidade urbana considerando viagens não motorizadas (caminhada e bicicleta), utilizando como inovação a Grade Estatística do IBGE. Em geral, para o modo a pé foi observado que cerca de 46% dos municípios analisados seriam totalmente resilientes, sendo que esta proporção é composta pelos munícipios de menor porte. Já os municípios que apresentaram uma baixa resiliência compreendem aproximadamente 11% do total de municípios e são caracterizados por aqueles de maior porte e mais populosos do estado. Para o modo bicicleta a situação é diferente, nota-se que apenas os municípios de São Paulo e Ilhabela apresentam baixa resiliência. Além disso, é observado que 91% dos municípios são totalmente resilientes em relação a esse modo de deslocamento. A partir dos resultados do método, buscou-se relacionar essa resiliência com métricas espaciais das cidades por meio de índices de forma urbana, a saber: Densidade, Concentração, Agrupamento e Centralidade. Dessa maneira, concluiu-se que a Densidade Domiciliar é o parâmetro que mais se destaca, uma vez que quanto maior o porte do município, maior foi o valor observado para essa mé... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The objective of this work was to evaluate the relationship between spatial characteristics of cities and the resilience in urban mobility, considering the different sizes of the municipalities, in a study applied to the state of São Paulo. To achieve this objective, we proposed the development of a method for assessing the resilience in urban mobility considering non-motorized trips (walking and cycling), using the Statistical Grid of the Brazilian Institute of Geography and Statistics as an innovation. In general, for walking, we observed that around 46% of the municipalities would be totally resilient, and this proportion corresponds to the smaller municipalities. On the other hand, the municipalities that show a lower resilience comprise approximately 11% of the total and are characterized by the largest and most populous municipalities in the state. For cycling the situation is different. We noted that only the municipalities of São Paulo and Ilhabela present a low resilience rate. In addition, we observed that 91% of the municipalities are totally resilient to this travel mode. In turn, we sought to establish a relationship between this resilience with spatial metrics of the cities through urban form indexes: Density, Concentration, Clustering and Centrality. Thus, we concluded that the household density is the parameter that stands out the most, since the larger the size of the municipality, the higher the value for this metric. For the other metrics (Concentration, Cl... (Complete abstract click electronic access below) / Mestre

Geospatial analysis involves application of statistical methods, algorithms and information retrieval techniques to geospatial data. It incorporates time into spatial databases and facilitates investigation of land cover (LC) dynamics through data, model, and analytics. LC dynamics induced by human and natural processes play a major role in global as well as regional scale patterns, which in turn influence weather and climate. Hence, understanding LC dynamics at the local / regional as well as at global levels is essential to evolve appropriate management strategies to mitigate the impacts of LC changes. This can be captured through the multi-resolution remote sensing (RS) data. However, with the advancements in sensor technologies, suitable algorithms and techniques are required for optimal integration of information from multi-resolution sensors which are cost effective while overcoming the possible data and methodological constraints. In this work, several per-pixel traditional and advanced classification techniques have been evaluated with the multi-resolution data along with the role of ancillary geographical data on the performance of classifiers. Techniques for linear and non-linear un-mixing, endmember variability and determination of spatial distribution of class components within a pixel have been applied and validated on multi-resolution data. Endmember estimation method is proposed and its performance is compared with manual, semi-automatic and fully automatic methods of endmember extraction. A novel technique - Hybrid Bayesian Classifier is developed for per pixel classification where the class prior probabilities are determined by un-mixing a low spatial-high spectral resolution multi-spectral data while posterior probabilities are determined from the training data obtained from ground, that are assigned to every pixel in a high spatial-low spectral resolution multi-spectral data in Bayesian classification. These techniques have been validated with multi-resolution data for various landscapes with varying altitudes. As a case study, spatial metrics and cellular automata based models applied for rapidly urbanising landscape with moderate altitude has been carried out.

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