Submitted by Fabielle Cheuczuk (fabielle.cheuczuk@unioeste.br) on 2018-06-05T17:45:08Z No. of bitstreams: 2 DISSERTAÇÃO_ANÁLISE DOS FATORES DISCRIMINANTES DOS MUNICÍPIOS DA REGIÃO SUDOESTE DO PARANÁ NO PERÍODO 2000-2010.pdf: 2229053 bytes, checksum: 3c1765c7e54287f20dd9c2e131c3af48 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-06-05T17:45:08Z (GMT). No. of bitstreams: 2 DISSERTAÇÃO_ANÁLISE DOS FATORES DISCRIMINANTES DOS MUNICÍPIOS DA REGIÃO SUDOESTE DO PARANÁ NO PERÍODO 2000-2010.pdf: 2229053 bytes, checksum: 3c1765c7e54287f20dd9c2e131c3af48 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-02-21 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Along the time the humanity has been going by a series of changes, among those changes, is the urbanization phenomenon, that happens some times in a more intense way, other times more slowly, impelled by a series of different factors. For this reason, the objective of this research is to analyze for which reasons some municipal districts of the Southwest area of Paraná presented urban growth, being more dynamic, and others had negative rates of population growth. Therefore, it is sought to determine the factors that differentiate the municipalities with growth from those with negative growth, based on socioeconomic characteristics, considering two distinct periods - 2000 and 2010. This analysis was made from the Discriminant Analysis, dividing the 42 municipalities of the (group 1), stable (group 2) and depressed (group 3). Eight variables were selected from secondary data obtained through IPARDES. The results of the research show that the discrimination between municipalities occurs due to population concentration (population density) and the degree of industrialization. Both factors can become attractive to newcomers who are seeking better living conditions, better job opportunities, increased income and education, that is, in search of a better quality of life. / Ao longo do tempo a humanidade tem passado por uma série de mudanças, dentre essas mudanças, está o fenômeno de urbanização, que ocorre ora de modo mais intenso, ora mais lentamente, impulsionado por uma série de fatores diferentes. Por esta razão, o objetivo desta pesquisa é analisar por quais motivos alguns municípios da região sudoeste do Paraná apresentaram crescimento urbano, sendo mais dinâmicos, e outros tiveram taxas negativas de crescimento populacional. Sendo assim, busca-se determinar os fatores que diferenciam os municípios com crescimento daqueles com crescimento negativo, a partir de características socioeconômicas, considerando dois períodos distintos – 2000 e 2010. Esta análise foi feita a partir da Análise Discriminante, dividindo os 42 municípios da região sudoeste em três grupos: dinâmicos (grupo 1), estáveis (grupo 2) e deprimidos (grupo 3). Foram determinadas oito variáveis selecionadas a partir de dados secundários obtidos através do IPARDES. Os resultados da pesquisa demostram que a discriminação entre os municípios ocorre por conta da concentração populacional (densidade demográfica) e o grau de industrialização. Ambos os fatores podem se tornar atrativos para novos habitantes que estão em busca de melhores condições de vida, melhores oportunidades de trabalho, aumento de renda e educação, ou seja, em busca de uma qualidade de vida melhor.

Esta pesquisa analisa o crescimento econômico, urbano e o desenvolvimento do município de Ubatuba entre os anos de 1980 e 2010. Seu objetivo é descrever o processo de crescimento territorial urbano como reflexo da evolução dos aspectos econômicos e sociais dentro deste espaço. A pesquisa tomou como base o Resumo Executivo de Ubatuba para avaliar a urbanização; o PIB, o PIB per capita para discorrer sobre a economia; e o Índice de Desenvolvimento Humano Municipal e os Objetivos do Milênio para discorrer sobre o desenvolvimento social local. O método utilizado foi a abordagem qualitativa e, para tanto, utilizou-se da coleta de dados de informações disponibilizadas pelo Instituto Polis, IBGE e Fundação SEADE. A partir de resultados observou-se que Ubatuba apresentou pico de crescimento populacional e expansão urbana entre as décadas de 1980 e 1990. Entre as décadas de 1990 e 2000, a expansão urbana irregular passa a ser contida pelo início da fiscalização por parte da Secretaria do Meio Ambiente. Neste mesmo período, indicadores sociais melhoraram seus resultados, mas o município perdeu espaço no ranking de desenvolvimento dos municípios paulistas. Entre 2000 e 2010 o crescimento populacional variou em menor escala e o número de novos loteamentos no município foi reduzido. A economia evoluiu e se concentrou no setor de serviços. Quanto ao social, este período mais recente demonstra que o município evoluiu seus indicadores sociais relacionados ao IDHM e aos ODM, porém ainda apresenta lacunas nos setores de educação, saúde, qualidade de vida e respeito ao meio ambiente. Concluiu-se que o município cresceu populacionalmente e se urbanizou ao longo do período analisado. Ainda assim, estes fenômenos não foram planejados previamente, o que refletiu em um processo de desenvolvimento que não acompanhou as necessidades advindas do aumento populacional. / This research analyzes the economic growth and urban development in the municipality of Ubatuba between the years 1980 and 2010. Its purpose is to describe the urban territorial growth process reflecting the evolution of the economic and social aspects within this space. The research was based on the Ubatuba Executive Summary to evaluate urbanization, GDP, GDP per capita to talk about the economy and the Municipal Human Development Index and the Millennium Development Goals to discuss local social development. The method used is the qualitative approach and, therefore, was used for data collection of information provided by the Polis Institute, IBGE and SEADE Foundation. From the results it was observed that Ubatuba presented peak population growth and urban expansion between 1980 and 1990. Between the 1990s and 2000, the irregular urban sprawl happens to be contained by early inspection by the Department of Environment. In the same period, social indicators are developed MHDI and MDG the number of new housing developments in the city has been reduced. The economy has evolved and focused on the service sector. As for the social, the most recent period shows that the council has evolved its social indicators, but still has gaps in educational, health, quality of life and respect for the environment. It was concluded that the city has grown and urbanized over the analysis period. Still, these phenomena were not planned in advance, which resulted in a development that did not follow the needs arising from population growth.

Urbanisation has had a profound impact in sub-Saharan Africa and can be attributed to the complex human-environment interaction. Knowledge on long-term urbanisation processes in sub-Saharan Africa is lacking. Besides, understanding the urbanisation process in sub-Saharan Africa necessitates to go beyond the global scale to the local scale to unravel the idiosyncrasies in the growth of each city. The perennial lack of data (or data meeting required specifications) is a bottleneck to such studies. Very often, the nature of the available data might present challenges to existing classification algorithms. Moreover, availability of adequate and well-curated reference datasets presents a bottleneck to the generation of accurate land-cover maps. The main aim of this research was to conduct a long-term analysis of urbanisation patterns in Central Africa by developing methodologies based on deep learning, a class of Artificial Intelligence. To this end, we address the main research question: “How can we understand long-term urbanisation patterns by applying deep learning on digital aerial images in Central Africa?” We used case-studies from three cities in Central Africa namely Goma and Bukavu in The Democratic Republic of Congo and Bujumbura in Burundi, to aid in understanding the urbanisation process in sub-Saharan Africa. We generate baseline data from an archive of historical panchromatic orthomosaics that allow for the capturing of the urbanisation before the onset of rapid urbanisation that was characteristic of Countries in sub-Saharan Africa after gaining independence from colonialism.The main contribution of this thesis is the 60-year long-term analysis of urbanisation patterns for three cities in Central Africa using a unique dataset of historical orthomosaics. The growth patterns and driving forces are analysed using spatial and qualitative data. The results show that social triggers such as wars drive urban expansion. On the contrary, biophysical drivers such as geohazards did not limit urban growth only slowing down settlements for a short time span of the analysis. As urbanisation levels increased, constraining effects of natural environment such as relief on urban expansion weakened. In addition, we make some methodological developments based on deep learning to generate land-cover from historical panchromatic orthomosaics (i.e. 1m spatial resolution) and sub-metric RGB aerial images (i.e. 0.175m). Results show that deep learning methods generally have high accuracy metrics, compared to standard machine learning baselines, but at the cost of high demand for a large and accurate, labelled dataset and computational resources. In addition, accurate and sufficient labelled data are still needed to guarantee accurate land-cover maps from deep learning algorithms and novel strategies need to be pursued in approaches investigating insufficient reference data. / L’urbanisation a eu un impact profond sur l’Afrique subsaharienne et peut être attribuée à l’interaction complexe entre l’homme et l’environnement. Les connaissances sur les processus d’urbanisation sur des temps longs font défaut. En outre, pour comprendre le processus d'urbanisation en Afrique subsaharienne, il faut aller au-delà de l'échelle mondiale et s'intéresser à l'échelle locale pour comprendre les particularités de la croissance de chaque ville. L'éternel manque de données (ou de données répondant aux spécifications requises) constitue des limitations de telles études. Très souvent, la nature des données disponibles peut présenter des défis pour les algorithmes de classification existants. De plus, la disponibilité d'ensembles de données de référence adéquats et fiables constitue un goulot d'étranglement pour la création de cartes précises de l'occupation des sols.L'objectif principal de cette recherche était de mener une analyse sur des temps longs des différentes modes d'urbanisation en Afrique centrale en développant des méthodologies basées sur le deep learning, une forme d'intelligence artificielle. A cette fin, nous répondons à la question de recherche suivante :"Comment pouvons-nous comprendre les modes d'urbanisation sur des temps longs en appliquant des approches de deep learning sur des images aériennes numériques en Afrique centrale ?". Nous avons étudié trois villes d'Afrique centrale, à savoir Goma et Bukavu en République démocratique du Congo et Bujumbura au Burundi, de manière à comprendre le processus d'urbanisation en Afrique subsaharienne. Nous pouvons générer des données de base à partir de mosaïques d'orthophotographies aériennes panchromatiques historiques qui permettent de saisir l'urbanisation avant le début de l'urbanisation rapide ayant caractérisé les pays d'Afrique subsaharienne depuis leur indépendance.La principale contribution de cette thèse est l'analyse, sur 60 ans, des modes d'urbanisation pour trois villes d'Afrique centrale en utilisant un ensemble unique d'orthomosaïques historiques. Les modes et les facteurs de croissance y sont analysés en utilisant des données spatiales et qualitatives. Les résultats montrent que les déclencheurs sociaux tels que les guerres étaient positivement corrélé à l'expansion urbaine. Au contraire, les facteurs biophysiques tels que les risques associés aux catastrophes naturelles n'ont pas empêché la croissance urbaine mais ont seulement ralenti les nouvelles implantations pendant une courte période de l'analyse. Par ailleurs, à mesure que les niveaux d'urbanisation augmentent, les effets contraignants de l'environnement naturel tels que le relief sur l'expansion urbaine s'affaiblissent.De plus, certaines avancées méthodologiques ont été accomplies en explorant et en développant une méthodologie basée sur le deep learning pour générer une carte de la couverture du sol à partir d’orthomosaïques panchromatiques historiques (1m) et d'images aériennes RVB sub-métriques (0.175m). Les résultats montrent que les méthodes de deep learning présentent généralement des indicateurs de précision élevés par rapport aux méthodes standard basée sur machine learning, mais au prix d'une grande demande en matière de données étiquetées et de ressources informatiques. En outre, des données étiquetées précises et en quantité suffisante sont toujours nécessaires pour garantir l'exactitude des cartes de l’occupation du sol établies par les algorithmes de deep learning, et de nouvelles stratégies doivent être mises en œuvre dans le cas de travaux ne disposant que de données de référence insuffisantes / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

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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

One of the major consequences of urbanization is the transformation of land surfaces from rural/natural environments to built-up land that supports diverse forms of human activity. These transformations impact the local geology, climate, hydrology, flora and fauna and human-life supporting ecosystem services in the region. Mapping and analysis of land use/land cover change in urban regions and tracking their environmental impact is therefore of vital importance for evaluating policy options for future growth and promoting sustainable urban development. The overall objective of this research is to investigate the extent of urban growth and/or sprawl and its potential environmental impact in the regions surrounding a few selected major cities in North America, Europe and Asia using landscape metrics and other environmental indicators to assess the landscape changes. The urban regions examined are the Greater Toronto Area (GTA) in Canada, Stockholm region and County in Sweden and Shanghai in China. The analyses are based on classificatons of optical satellite imagery (Landsat TM/ETM+ or SPOT 1/5) between 1985 and 2010. Maximum likelihood classification (MLC) under urban/rural masks, objectbased image analysis (OBIA) with rule-based classification and support vector machines (SVM) classification methods were used with grey level cooccurrence matrix (GLCM) texture features as input to help obtain higher accuracies. Based on the classification results, landscape metrics, selected environmental indicators and indices, and ecosystem service valuation were calculated and used to estimate environmental impact of urban growth. The results show that urban areas in the GTA grew by nearly 40% between 1985 and 2005. Results from the landscape metrics and urban compactness indicators show that low-density built-up areas increased significantly in the GTA between 1985 and 2005, mainly at the expense of agricultural areas. The majority of environmentally significant areas were increasingly surrounded by urban areas between 1985 and 2005, furthering their isolation from other natural areas. Urban areas in the Stockholm region increased by 10% between 1986 and 2006. The landscape metrics indicated that natural areas became more isolated or shrank whereas new small urban patches came into being. The most noticeable changes in terms of environmental impact and urban expansion were in the east and north of the study area. Large forested areas in the northeast dropped the most in terms of environmental impact ranking, while the most improved analysis units were close to the central Stockholm area. The study comparing Shanghai and Stockholm County revealed that urban areas increased ten times as much in Shanghai as they did in Stockholm, at 120% and 12% respectively. The landscape metrics results show that fragmentation in both study regions occurred mainly due to the growth of high density built-up areas in previously more natural environments, while the expansion of low density built-up areas was for the most part in conjunction with pre-existing patches. The growth in urban areas resulted in ecosystem service value losses of approximately 445 million USD in Shanghai, mostly due to the decrease in natural coastal wetlands, while in Stockholm the value of ecosystem services changed very little. This study demonstrates the utility of urban and environmental indicators derived from remote sensing data via GIS techniques in assessing both the spatio-temporal dynamics of urban growth and its environmental impact in different metropolitan regions. High accuracy classifications of optical medium resolution remote sensing data are achieved thanks in part to the incorporation of texture features for both object- and pixel-based classification methods, and to the use of urban/rural masks with the latter. The landscape metrics calculated based on the classifications are useful in quantifying urban growth trends and potential environmental impact as well as facilitating their comparison. The environmental indicator results highlight the challenges in terms of sustainable urban growth unique to each landscape, both spatially and temporally. The next phase of this PhD research will involve finding valid methods of comparing and contrasting urban growth patterns and estimated environmental impact in different regions of the world and further exploration of how to link urbanizing landscapes to changes in ecosystem services via environmental indicators. / <p>QC 20141212</p>

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Icons surround us but are so ubiquitous they are difficult to observe. Specifically urban cultural icons are a scientific sub-topic under urban morphology's heading and as well are closely related to economic development issues. This study premises that businesses are urban cultural icons which can be computed into four rankings: local cultural icons, focal, zonal, and global cultural icons. And through using dimensional measurement an index is measured. This index can then be used to assess urban morphology. The data set ranges from businesses opening in 1865 to the present. Some are globally-distributed "big boxes"; others are unique one-store shops. The varied data set includes grocery stores, drug stores, prepared food vendors, confectioneries, coffee houses, electronic stores, and an adult entertainment store. Business rankings are premised upon Maslow's Hierarchy of Needs, Tönnies, and Oldenburg's places to socialize, and node intensity of social connection. Time is measured linearly and ordinally. Two formats of geographical ranking are assessed against each other, with the expanded version providing greater insights. Transactions are determined by who initiates them and location where employee enters exchange. Business' internal consistency is based upon product-line inclusion and theme-ing. Scaled measurements are summed with a comparison of Weighted-Place Index Scores against non-weighted Index Scores. As well, economic development impact of businesses is analyzed with three principal components loadings: two business survival and one growth mode. Study results support the use of Weighted-Place Index Scores as compared to nonweighted Index scores when formatting cultural icon index. Index score using four-level geographical ranking ranged from zero to 25. Morning Call Coffee House had lowest ranking (Index score of 3) and Best Buy had the highest score of 22. Weighted-Place Index Scores ranged from zero to 32, with Morning Call Coffee House continuing as lowest score and Starbucks, Bad Ass Coffee, as well ApplianceWorld and Best Buy continuing with four highest scores. This study supports a research method which can be used to measure urban change. By applying Index score within same cities at 20-year increments, sprawl process of globalization within cities can be analyzed.

Cette thèse propose d’étudier l’évolution des hiérarchies des villes et de la croissance urbaine en s’appuyant sur le cas du Maroc. Le Maroc a connu ces dernières décennies un processus d’urbanisation soutenu, tant dans les grandes villes que dans les petites et moyennes villes. D’où la nécessité de procéder à une structuration démographique urbaine primatiale qui exige une coordination entre certaines politiques économiques nationales et les politiques d’aménagement menées par les grandes métropoles afin de faire preuve d’une réelle efficacité. Une politique d’aménagement résolument tournée jusqu’ici vers la gestion de la pression urbaine dans les grandes métropoles. Ce qui a conduit par conséquent à une polarisation des activités dans quelques régions du territoire. Ainsi, cette thèse se structure autour de trois chapitres. Le premier chapitre examine la loi rang-taille et l’apport des économistes et des géographes dans ce processus. Le second chapitre analyse les trois approches théoriques qui traitent la question de la croissance urbaine notamment les théories de la croissance aléatoire, de la croissance déterministe et l’intersection de ces deux approches dites d’hybrides. Enfin, le dernier chapitre est basé sur une étude empirique à l’échelle régionale afin de recenser les déterminants de la croissance urbaine des régions marocaine. Le travail engagé dans cette thèse s’appuie sur des bases de données originales fournies par le Haut-Commissariat au Plan permettant de recenser la taille des agglomérations marocaines et utilise un ensemble d’instruments statistiques et économétriques. Les différents résultats obtenus s’inscrivent dans le prolongement de différentes études effectuées en sciences régionales. Ces résultats indiquent que les hiérarchies urbaines marocaines sont appelées à changer dans les décennies à venir, mais également que la croissance économique des régions du Maroc n’affecte pas immédiatement la croissance de la population urbaine. / This thesis proposes to study the evolution of city hierarchies and urban growth based on the case of Morocco. This country has experienced in recent decades a sustained urbanization process, both in large cities and small and medium-sized cities. Hence the need to proceed to a primatial urban demographic structure that requires coordination between certain national economic policies and planning policies carried out by major cities to be truly effective. A development policy resolutely turned so far towards the management of urban pressure in major cities. This led to a polarization of activities in some regions of the territory. Thus, this thesis is divided into three chapters. The first chapter examines the rank-size law and the contribution of economists and geographers in this process. The second chapter analyzes the three theoretical approaches that deal with the issue of urban growth, in particular theories of random growth, deterministic growth and the intersection of these two approaches, called hybrid. Finally, the last chapter is based on an empirical study at the regional level to identify the determinants of urban growth in Moroccan regions. The work undertaken in this thesis is based on original databases provided by the Office of the “Haut-Commissariat au Plan” to identify the size of Moroccan agglomerations and uses a set of statistical and econometric instruments. The various results obtained are a continuation of various studies carried out in regional sciences. These results indicate that Moroccan urban hierarchies are destined to change in the decades to come, but also that the economic growth of the regions of Morocco does not immediately affect the growth of the urban population.

The city of Bukavu, located at the eastern border of the Democratic Republic of Congo in the province of South Kivu, is a large and densely populated urban agglomeration that has experienced rapid growth during recent years. At the same time, Bukavu has been repeatedly struck by environmental hazards, especially by devastating landslides. The steepness of slopes in the city’s hilly and mountainous terrain is one of the most important factors contributing to landslide susceptibility, but the anthropogenic impact resulting from uncoordinated urban sprawl and land cover change additionally plays a crucial role in exacerbating the vulnerability of neighbourhoods. This thesis utilizes GIS software to provide cartographic material for landslide risk assessment in Bukavu and the city’s surroundings. It examines risk exposure related to slope inclination of densely built-up areas, the spatial development of the city and urban growth tendencies, and complements these aspects with information about land cover and the terrain.