Primary School Pupil Numbers and Demographic Change in Czech Municipalities Abstract Following a sharp fall in fertility to its historical minimum after 1990, the population of Czechia began to increase again gradually. Consequently birth cohorts of varying size are emerging and these then enter the education system. Moreover suburbanisation has led to a change in population distribution. These factors have mean that in some areas primary school capacity does not reflect the numbers of primary school age children, with some schools having insufficient places and others suffering from a lack of pupils. The aim of this dissertation is to analyse regional demographic change in Czechia after 1990, including changes in the spatial pattern of compulsory school age children (6-14 years). The information obtained is set against the changes in the spatial patterns of primary school pupils and maximum primary school capacity. The whole analysis is undertaken within the catchment regions for combined primary schools (schools that provide nine years of primary and middle school education), which were created on the basis of the shortest road distance from the district to the nearest combined primary school. Webb's graphs were used along with spatial autocorrelation since these are appropriate methods for conducting...

Objetivo Caracterizar a ocorrência de dengue na cidade de Rio Brando, estado do Acre, no período de 2000 a 2007, no tempo, no espaço e segundo infestação pelo Aedes aegypti e vari- áveis demográficas, socioeconômicas, ambientais e climáticas. Métodos Foi realizada uma descrição da incidência de dengue (CI) e da infestação predial pelo Aedes aegypti (IIP) no período de 2000 a 2007 a partir de dados secundários. Descreveu-se a incidência da dengue em relação ao sexo, faixa etária e escolaridade. O Coeficiente de Incidência e o Índice de In- festação Predial foram testados para aferição de correlações com variáveis climáticas, demo- gráficas, ambientais e socioeconômicas. Foi aplicada a técnica de geoprocessamento com o uso da estatística espacial de Moran Global e Local (LISA) para avaliar a autocorrelação es- pacial dos coeficientes de incidência de dengue entre as localidades urbanas da cidade. Resul- tados - A epidemiologia da dengue na cidade é caracterizada por elevada incidência e intensa infestação predial pelo Aedes aegypti. Não existe diferença na incidência de dengue entre ho- mens e mulheres e a faixa etária mais acometida compreende jovens e adultos de 15 a 49 anos e escolares que não concluíram o ensino médio. A distribuição da doença mostra um padrão sazonal com elevação da incidência nos períodos chuvosos e regressão nos períodos secos. O aumento de casos de dengue e da infestação predial mostrou associação significante (p<0,05) com bairros populosos, onde existe muitos imóveis e alta infestação predial. O aumento das ocorrências se mostrou significante com áreas com baixo índice de abastecimento de água pela rede pública. O Índice de Qualidade de Vida (IQV) não apresentou correlação significa- tiva com a ocorrência de dengue, entretanto, a infestação predial foi mais elevada nos bairros com melhor IQV. A estatística de Moran Global e Local (LISA) mostrou fraca dependência espacial (p<0,05) da incidência de dengue entre bairros da cidade. Conclusão - A análise epi- demiológica da dengue na cidade permitiu visualizar fatores que estão relacionados à trans- missão de dengue e na proliferação do Aedes aegypti que podem ser avaliados na formulação de estratégias mais eficazes para alcançar o melhor controle da doença. O uso da análise espa- cial evidenciou que a distribuição da incidência de dengue entre os bairros da cidade ocorre de maneira aleatória / Objective - Characterize the ocurring of dengue in the city of Rio Branco, Acre, during the period 2000 to 2007, in time and space, and according to the infestation of Aedes Aegypti and the demographic, social-economical, environmental and climatical variables. Methods - a description of dengue incidence (CI) and the house infestation by Aedes aegypti (HI) was made in the period of 2000 to 2007 from secondary data. The distribution of cases was described according to gender, age and education. The Incidence Coefficient of incidence and the House Index Infestation were tested to measure their correlations with demographic, environmental and socioeconomic climatic variables. The geoprocessing technique was applied with the use of Global and Local Moran (LISA) spatial statistics to evaluate spatial autocorrelation of incidence of dengue among the urban localities in the city. Results - The epidemiology of dengue in the city is characterized by high incidence and severe infestation of Aedes aegypti. Theres no difference between the incidence of dengue on men and women and the most affected age group comprises young adults from the age of 15 to 49 years old and students who have not completed high school. The distribution of the disease shows a seasonal pattern with increased incidence in rainy periods and regression in dry periods. The increase of dengue cases and the building infestation showed significant association (p <0.05) with the populated districts, where there are many buildings and high building infestation. The increase in occurrence was found significant in areas with low public water supply. The Quality of Life Index (QLI) showed no significant correlation with the occurrence of dengue, however, the infestation rate was higher in districts with better QLI. Global and Local Moran (LISA) statistics showed weak spatial dependence (p <0.05) of the incidence of dengue among neighborhoods. Conclusion - The epidemiological analysis of dengue in the city allowed the visualization of the factors that are related to the transmission of dengue and the proliferation of Aedes aegypti that can be assessed in the formulation of more effective strategies to achieve better control of the disease. The use of the spatial analysis revealed the randomness of dengue incidence distribution among the neighborhoods of the city

L'agriculture actuelle est impliquée dans de multiples problématiques environnementales, sociales et économiques, aux échelles locales et globales. En agronomie, de nombreux travaux à l'échelle du champ et de l'exploitation visent aujourd'hui à concevoir des systèmes de culture et des systèmes de production en lien avec ces problématiques. En revanche, peu de travaux portent sur la conception et l'évaluation de systèmes agricoles à l'échelle du territoire, alors que cette échelle apparaît pourtant incontournable pour faire face à des enjeux de développement durable. Pour combler ce manque, nous proposons un ensemble méthodologique permettant i) de simuler les conséquences de scénarios de politiques agricoles sur les choix d'assolement des agriculteurs, décrits individuellement, en modélisant l'évolution de leurs système de production et ii) d'évaluer l'impact de ces changements d'assolements à l'échelle du territoire, à l'aide d'indicateurs qui apportent de l'information spatiale sur la contribution de l'agriculture au développement durable. L'ensemble méthodologique proposé débute par la construction d'une typologie des exploitations agricoles du territoire sur la base de la similarité de leur assolement. Parallèlement, l'adaptation d'indicateurs à l'échelle du territoire permet d'évaluer les impacts des externalités des systèmes de culture en mobilisant des procédures de changements d'échelles. Un modèle bioéconomique générique, multi-échelle, spatialement explicite, appelé MOSAICA, qui utilise la typologie et les indicateurs d'impact de l'agriculture à l'échelle régionale, est créé pour produire des mosaïques de systèmes de culture et évalue leur contribution au développement durable du territoire. Ce modèle, couplé à un itinéraire de définition de scénarios exploratoires et normatifs permet de tester l'impact de différents types de leviers agronomiques, socio-économiques, environnementaux, organisationnels et techniques sur les choix des exploitants et in fine sur la contribution de la mosaïque de systèmes de culture au développement durable du territoire. Nous avons appliqué cet ensemble méthodologique à la conception de scénarios de développement agricoles durables en Guadeloupe. Nous avons dans un premier temps développé une typologie des systèmes de production comprenant huit types distincts et relevant de processus décisionnel différents. Puis nous avons adapté à l'échelle du territoire 19 indicateurs pour l'évaluation des mosaïques de systèmes de culture. L’évaluation de la mosaïque actuelle nous a permis de repérer de faibles niveaux de contribution aux enjeux d’autonomie alimentaire et énergétique. Différents scénarios normatifs et exploratoires intégrant des leviers de changement de la mosaïque ont été testés avec MOSAICA. Les évaluations réalisées nous ont permis d'identifier que des leviers agronomiques comme le développement du maraîchage sans intrants chimiques et des leviers sociaux comme la formation de main-d'oeuvre supplémentaire permettraient d'améliorer la contribution de l’agriculture au développement durable du territoire Guadeloupéen. La modélisation mécaniste de l’évolution du territoire agricole permet d'intégrer des connaissances sur la localisation, les performances, les impacts des systèmes de culture et sur les processus décisionnels des exploitants régissant l’orientation productive et le fonctionnement des exploitations. Cette démarche permet de visualiser les changements de système de culture et leurs impacts de manière spatialement explicite, ce qui permet de générer des connaissances sur les leviers susceptibles de faire évoluer positivement l'agriculture du territoire. La démarche et les outils mis en oeuvre sont donc particulièrement utiles pour l'aide à la décision publique pour améliorer la durabilité de l'agriculture dans son ensemble. / Current agricultural systems are responsible for many different environmental, social and economic issues at both local and global scales. Agricultural sciences have contributed to the design of several methods at the farm and field scale in order to prototype cropping systems and farming systems to address these issues. However, few methods have been designed at the regional scale, while this scale seems to be essential in order to address these issues. In order to fill this gap, we here propose a new methodological framework for i) simulating the consequences of policy changes on farmer's cropping plan, described individually, by modeling the evolution of farming systems and to ii) assess the impacts of cropping system changes at the regional scale, with a set of indicators that generate spatially explicit information on the contribution of agriculture to sustainable development. The methodological framework starts with the design of a farm typology over the territory based on the similarity of farmer's crop acreages. In parallel, a set of indicators is adapted to the landscape scale in order to assess the impacts of cropping system externalities by integrating a set of scale change procedures. A generic, multi-scale, spatially explicit bioeconomic model called MOSAICA, which uses the farm typology and the indicators, is created for generating cropping system mosaics and assessing their contribution to sustainable development. This model coupled to a scenario approach composed of exploratory and normative scenarios can simulate the impact of several types of agronomic, socio-economic, environmental, organizational and technical levers of change on the farmer's choices in terms of cropping systems and in fine the impacts of new cropping system mosaics on the contribution to sustainable development of territories. We applied this methodological framework for building scenarios of sustainable agricultural development in Guadeloupe. We first developed a typology of farming systems encompassing eight types of farming systems that revealed several different farmer's decision processes. Then, we developed 19 indicators to assess cropping system mosaics. The assessment of the current cropping system mosaic showed low levels of response of the current mosaic to economic and social issues especially the food and energy self-sufficiency. Different normative and exploratory scenarios integrating levers of change have been simulated with MOSAICA. The assessment of cropping system mosaics from these scenarios highlighted the positive effect of agronomic levers of change such as organic crop-gardening and social levers such as the vocational training of supplementary workforce for improving the contribution of agriculture to sustainable development of the guadeloupean territory. The mechanistic modeling of the agricultural territory allows us to integrate a wide range of knowledge on the location of cropping systems, their levels of performance , their impacts and the decision process of farmer's that drive the farming system characteristics and the farm functioning. This methodological framework helps visualize the cropping system changes at the regional scale and their associated impacts at the landscape scale which is helpful in order to produce knowledge on the levers of change that can improve the response of local agriculture to local and global issues. The framework and tools designed are particularly useful for decision-aid on the future levels of contribution of agriculture to sustainable development.

A acessibilidade está relacionada com a maneira como a disponibilidade de transportes e os usos do solo afetam os indivíduos na realização de viagens para o desenvolvimento de suas atividades habituais. Freqüentemente se assume que os moradores de baixa renda da periferia são os mais afetados pela falta de acesso aos meios de transporte. A questão subjacente a esta afirmação, no entanto, permanece sem uma resposta definitiva: o nível de renda, por si só, seria um indicativo do nível de acessibilidade? O objetivo deste estudo é explorar a união de ferramentas de estatística espacial e SIG (Sistema de Informações Geográficas) com um propósito específico, que é o de analisar as relações entre aspectos da distribuição espacial de características da população (como a renda, por exemplo) de uma cidade média brasileira e os diversos níveis de acessibilidade por diferentes modos de transporte nela observados, buscando possíveis respostas para esta pergunta. Quando se utiliza procedimentos de visualização e classificação de dados espaciais comuns em SIG, nem sempre as informações são diretamente perceptíveis. Logo, deve-se utilizar ferramentas que ampliem as possibilidades de compreensão e análise dos dados. Inicialmente, as ferramentas selecionadas para uso neste trabalho são apresentadas e discutidas quanto à sua aplicação e utilização na análise proposta. Para tal foram utilizados dados coletados em uma pesquisa origem–destino (O-D) realizada na cidade de Bauru - SP, agrupados por setores censitários e adicionados ao SIG, aplicando técnicas de estatística espacial utilizadas para entidades do tipo área. Os resultados obtidos são apresentados na forma de mapas e de índices que medem a associação espacial global e local entre estas zonas. Uma das conclusões interessantes da aplicação foi a identificação de regiões da cidade com dinâmica particular, que contrariam o padrão global observado nas demais partes da área urbana. Pôde-se constatar ainda particularidades a respeito do uso de cada modo de transportes. O modo automóvel como motorista, por exemplo, possui agrupamento espacial bem definido no nível de renda alta tanto nas regiões de periferia, como nas de transição e central. Já o modo ônibus é predominantemente utilizado nas zonas de renda baixa das regiões de periferia e transição, enquanto que os modos não motorizados possuem uma dinâmica bem diversificada em toda a área urbana. Estes e outros resultados do estudo de caso deixam claro que as análises de estatística espacial em ambiente SIG criam uma ferramenta para ampliar a análise convencional de acessibilidade em transportes / Transportation accessibility is directly related to the level of transportation supply and land uses and the way they affect individuals in their trip desires for accomplishing regular-basis activities. It is often assumed that low-income segments of the population living at the periphery of the cities are those affected the most by poor conditions of transportation accessibility. There is a subjacent question behind this statement, however, which is: can the income level or the location of an individual alone explain his/her accessibility level? In order to look for answers to this question, the aim of this study is to analyze, making use of spatial statistics tools in a GIS (Geographic Information System) environment, the relationships between accessibility and income and their geographical distributions in a medium-sized Brazilian city. The application of the most commonly used GIS resources, such as visualization and spatial data classification tools, not always assures a full comprehension of the phenomenon under analysis. As a consequence, many problems require tools that enhance the possibilities of observation and analysis. As tools with this characteristic have been used in this work, they were initially introduced. Thereafter, the possibilities of use of these tools in the problem analyzed were also discussed. Data of an origin-destination (O-D) survey carried out in the city of Bauru, located in the state of São Paulo, which brings information about four different transportation modes, were used in this study. Such data, grouped following the census tracts, were carefully examined in a Geographic Information System in order to look for spatial patterns of accessibility that are not visible in the traditional approaches. The results of the analysis are presented in maps and as indices that are able to capture glabal and local spatial association patterns in areas. One of the interesting outcomes of the application was the identification of regions with particular dynamics, which go against the pattern found in the overall urban area. Particularities regarding each particular transportation mode have also been noticed. The zones where the automobile is most used (by drivers, not by passengers) are spatially clustered, regardless if the zone is at the periphery, transition zone or central area of the city. The bus trips are predominantly carried out in low-income areas of the periphery and transition rings, while the non-motorized modes (walk and bicycle) have shown a very diversified dynamics in the entire urban area. This and other results of the case study clearly indicate that spatial statistics analyses in a GIS environment create a powerful tool to extend conventional transportation accessibility analysis

Resumo: Com o surgimento de áreas degradadas por ações antrópicas, os atributos físicos e químicos do solo e os caracteres silviculturais, passaram a ter importância quanto ao entendimento do processo sucessional das espécies arbóreas e no planejamento de recomposição da paisagem. Este trabalho teve como objetivo avaliar a distribuição de espécies arbóreas em áreas com diferentes níveis de perturbação antrópica, promover a compreensão da relação com os atributos químicos e físicos do solo; avaliar caráteres silviculturais e a relação como possível fator definidor do tipo vegetacional existente, para fins de integrar a programa de conservação genética in situ. O trabalho foi desenvolvido em área da Fazenda Experimental de Pesquisa e Extensão (FEPE) da UNESP de Ilha Solteira, no município de Selvíria - MS. Por meio de transecto foram demarcadas 64 parcelas equidistantes de 50 m com dimensões de 10x10 m. Sendo: 29 parcelas em área altamente antropizada (AAA); cinco em área medianamente antropizada (AMA); 15 em área pouco antropizada (APA); seis na mata ciliar do córrego da Véstia (Mata ciliar) e nove na Reserva legal. As amostras de solo foram coletadas em quatro profundidades (0,0 a 0,10 m; 0,10 a 0,20 m; 0,20 a 0,30 m e 0,30 a 0,40 m) para análise dos atributos físicos e duas profundidades (0,0 a 0,20 m e 0,20 a 0,40 m) para os atributos químicos além da avaliação dos caracteres silviculturais, como altura, diâmetro a altura do peito (DAP) e forma, e da autocorrelação espacial. Com base nos resultados conclui-se que: os atributos físicos e químicos do solo, associados ao nível de antropização e conservação das áreas, estão influenciando a ocorrência natural, diversidade de espécies e desenvolvimento dos indivíduos arbóreos; a altura, DAP e Forma, são bons indicadores para avaliar o crescimento das espécies arbóreas e relacioná-los aos ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: With the emergence of areas degraded by human actions, the physical and chemical soil properties and forestry traits, have gained importance in understanding the process of succession of tree species and restoration of landscape. This study aimed to evaluate the distribution of tree species in areas with different levels of human disturbance, promote understanding of the relationship with the chemical and physical properties of soil; evaluate forestry charatcer relationship as possible and defining factor of the existing vegetation type, for to integrate the program of genetic conservation in situ. The work was developed at the Experimental Farm Research and Extension (FEPE) from UNESP of Ilha Solteira, Selvíria - MS. Through transect were marked 64 plots of 50 m equidistant with dimensions of 10x10 m. Where: 29 plots was located in area highly impacted (AAA), five in moderately disturbed area (AMA) in 15 in little disturbed area (APA); six in Riparian forest river of Véstia (Riparian Forest) and nine in the Legal Reserve. Soil samples were collected at two depths (0,0-0,20 m and 0,20-0,40 m) for the analysis of chemical and four depths (0,0-0,10 m, 0,10-0,20 m, 0,20-0,30 m and 0,30-0,40 m) for physical attributes; assessment of forestry traits such as height, diameter at breast height and shape, and spatial autocorrelation. Based on the results concluded that: the physical and chemical soil properties associated with the level of human disturbance and conservation areas, are influencing the natural occurrence, species diversity and development of the individual trees; the height, diameter at breast height and shape are good indicators to assess the growth of tree species and relate them to physical and chemical attributes of soil; the AAA, and the AMA to show similarity of soil physical properties; APA and Legal reserve have higher natural occurrence, number of individuals and number ... (Complete abstract click electronic access below) / Orientador: Mario Luiz Teixeira de Moraes / Coorientador: Salatiér Buzetti / Banca: Enes Furlani Júnior / Banca: Marco Eustaquio de Sá / Banca: Flávio Bertin Gandara / Banca: Daniela Silvia de Oliveira Canuto / Doutor

Due to the advances in location-acquisition techniques, citizen geospatial data has emerged with opportunity for research, development, innovation, and business. A variety of research has been developed to study society and citizens through exploring patterns from geospatial data. In this thesis, we investigate patterns of population and human sentiments using GPS trajectory data and geo-tagged tweets. Kernel density estimation and emerging hot spot analysis are first used to demonstrate population distribution across space and time. Then a flow extraction model is proposed based on density difference for human movement detection and visualization. Case studies with volleyball game in West Lafayette and traffics in Puerto Rico verify the effectiveness of this method. Flow maps are capable of tracking clustering behaviors and direction maps drawn upon the orientation of vectors can precisely identify location of events. This thesis also analyzes patterns of human sentiments. Polarity of tweets is represented by a numeric value based on linguistics rules. Sentiments of four US college cities are analyzed according to its distribution on citizen, time, and space. The research result suggests that social media can be used to understand patterns of public sentiment and well-being.

Cette thèse, portant sur le choix de localisation résidentielle des ménages, s’inscrit dans le cadre théorique de la microéconomie urbaine et de l’utilité aléatoire. Si l’approche des choix discrets reste la plus appropriée dans ce domaine, la difficulté réside dans l’adaptation de ce type de modèles au contexte spatial (autocorrélation spatiale, grand nombre d’alternatives de choix) d’une part, et dans la manière de définir l’échelle de désagrégation d’autre part. Pour ce faire, nous avons procédé en deux temps. Nous avons estimé un logit multinomial avec un échantillon aléatoire d’alternatives pour comprendre le processus de choix de localisation résidentielle, avant de tester l’apport d’une structure hiérarchique pour traiter les problèmes d’autocorrélation spatiale. Cela a aussi permis l’investigation d’une nouvelle méthode de correction des biais liés à l’échantillonnage d’alternatives dans le cas du modèle logit emboîté. En termes de résultats, nous avons montré que la qualité de l’environnement social est le facteur le plus déterminant, sans remettre en cause le poids toujours important de l’accessibilité à l’emploi. Au plan méthodologique, nous avons été en mesure de tester l’apport de l’utilisation d’un modèle logit emboîté pour analyser les choix de localisation de l’aire urbaine de Lyon. Cependant, nous n’avons pas pu dépasser la difficulté de séparer l’autocorrélation spatiale et entre les nids. Le calage du modèle de choix de localisation en 1999 et en 2007 a aussi permis de donner des éléments de réponse sur la transférabilité temporelle des modèles de choix de localisation et de questionner, dans les travaux futurs, le pouvoir prédictif d’un modèle de choix de localisation. / This thesis, focusing on the choice of residential location, is based on the theoretical framework of urban micro-economy and random utility. Though discrete choice modelling is the most appropriate in this field, the difficulty lies in choosing the appropriate model to the spatial context of residential location choice (spatial autocorrelation, large number of alternatives), on the one hand, and in the way of defining the spatial scale, on the other hand. For this purpose, we proceeded in two stages. We estimated a multinomial logit with random sampling of alternatives to understand the process of residential location choice before taking into account the spatial autocorrelation, and estimating a nested logit model. It also allowed to investigate the feasibility of applying a new method to correct biases of sampling alternatives in the case of nested logit model. In terms of results, we have shown that social environment are the most important determinants of residential location choice. Though job accessibility still weigh on household choice decision. In terms of methodology, we were able to test the feasibility of estimating a nested logit model with sampling of alternatives to analyze the choice of location of Lyon urban area. However, we could not overcome the difficulty of distinguishing spatial autocorrelation from nesting. The use of 1999 and 2007 databases to model residential location choice also helped to provide answers on the temporal transferability of location choice models and discuss in future work the predictive power of a location choice model.

Made available in DSpace on 2017-07-10T19:24:17Z (GMT). No. of bitstreams: 1 DENISE_M_GR_ZEGOZEWSKI.pdf: 8188144 bytes, checksum: 045f54782a1ea2161edf5aa7046a8c1c (MD5) Previous issue date: 2016-02-03 / Estimates of agricultural production are greatly important especially in economy field. However, they depend on area knowledge and cropping yield. Thus, this study aimed to propose a methodology to estimate the areas cropped with soybeans and corn in Paraná State according to multi-temporal EVI/MODIS vegetation index images for 2010/2011, 2011/2012 and 2012/2013 crop years. In addition, there was a research with spatial autocorrelation soybean yield in Paraná, with EVI vegetation index and meteorological variables in a decennial scale and estimate yield using CAR, SAR and GWR models. In Paraná State, there is a drawback to map soybeans crop since corn sowing period is very close to the first one. Therefore, images from the maximum and minimum vegetative vigour were drawn of each studied crop for mapping soybean and corn crops in order to obtain both cropping areas. Although, for the separation, Spectro Angle Mapper algorithm (SAM) was applied by one of the studied crops, while mapping was obtained by multiplying the other bands. Thus, for spatial statistics application of mapped data, the average EV profile of each municipality was extracted as well as for each multi-temporal image, in order to change them into a decennial scale. According to the spatial statistics of such areas, the descriptive analysis of univariate spatial autocorrelation (global and local) of each ten-day variable was used based on the soybean cycle. A bivariate autocorrelation analysis between soybean yield and the studied varieties were also performed. Finalizing the methodology, variables with the highest significant level by stepwise method were selected and SAR, CAR and GWR models were generated to estimate soybean yield. As results, regarding mappings, the following answers for soybean were found out: r = 0.95 and r = 0.99, and while for corn, the answers were: r = 0.72 and r = 0.95 for 2012/2013 and 2013/2014 crop years in relation to the official data from SEAB. So, it has been proved some great efficiency of this methodology to separate and identify crops. When the descriptive statistics of municipalities for each variable was carried out, it was found out that some regions began an early sowing in relation to other ones in Paraná by the decennial vegetation index. The ten-day scale was also possible to be identified according to the climatic factors that caused soybean yield damage. Based on the analysis of spatial autocorrelation, the greatest similarities occurred in 2011/2012 crop year, the one affected by the weather change, whose yields were similar in the municipalities of Paraná State. For spatial modelling, it was observed that selection of decennial variables was different for each studied crop year, and the best model selected by the validation. And GWR was chosen as the best model by the AIC, BIC and adjusted R² validation criteria. The residuals were randomly distributed throughout all the State, so that spatial autocorrelation could be eliminated. / As estimativas das produções agrícolas têm grande importância, principalmente, no âmbito econômico. No entanto, elas são dependentes do conhecimento da área de cultivo e da produtividade da cultura. Desta forma, este trabalho teve por objetivo propor uma metodologia para estimar as áreas cultivadas com soja e milho em escala municipal no Estado do Paraná a partir de imagens multi-temporais do índice de vegetação EVI/MODIS, para os anos-safras 2010/2011, 2011/2012 e 2012/2013. Além disto, trabalhar com a autocorrelação espacial da produtividade da soja nesse Estado, com o índice de vegetação EVI e variáveis agrometeorológicas em escala decendial bem como estimar a produtividade a partir dos modelos CAR, SAR e GWR. No Paraná, há o inconveniente para mapear a soja devido à proximidade de datas de semeadura do milho. Assim, para o mapeamento da soja e do milho, utilizaram-se imagens englobando o período de máximo e mínimo vigor vegetativo de cada cultura, para se obter a área cultivada das duas. Para a separação, utilizou-se o algoritmo Spectro Angle Mapper (SAM) para uma das culturas e obteve-se o mapeamento da outra pela multiplicação de bandas. Para aplicação da estatística espacial dos dados mapeados, extraiu-se o perfil médio do EVI de cada município e para cada imagem multi-temporal para transformá-los em escala decendial. De acordo com a estatística espacial de áreas, utilizou-se a análise descritiva, de autocorrelação espacial univariada (global e local) de cada variável decendial com foco no ciclo da soja. Também realizou-se a análise de autocorrelação bivariada entre a produtividade da soja com as variáveis em estudo. Finalizando a metodologia, selecionaram-se as variáveis com maior índice de significância pelo método de stepwise e, em seguida, foram gerados os modelos estimados (SAR, CAR e GWR) da produtividade da soja. Como resultados, foram encontradas as seguintes respostas para os mapeamentos da soja r= 0,95 e 0,99, e para o milho de r = 0,72 e r= 0,95 para os anos-safras 2012/2013 e 2013/2014 em relação aos dados oficiais da SEAB. Logo, comprovou-se a grande eficiência da metodologia para separação e identificação das culturas. Quando realizada a estatística descritiva dos municípios para cada variável, verificaram-se regiões que iniciam as semeaduras antecipadas em relação a outras regiões do Estado pelos decêndios do índice de vegetação. Foi também possível identificar os decêndios em que os fatores climáticos causaram danos à produtividade da soja. Na análise da autocorrelação espacial, as maiores similaridades ocorreram no ano-safra 2011/2012, ano afetado pela variação climática, cujas produtividades foram semelhantes nos municípios do Paraná. Para a modelagem espacial, verificou-se que a seleção das variáveis decêndiais foi diferente para cada ano-safra estudado, e o GWR foi escolhido como melhor modelo pelos critérios de validação, AIC, BIC e R² ajustado. Foram encontrados resíduos distribuídos aleatoriamente por todo o Estado, para que assim se eliminasse a autocorrelação espacial

A acessibilidade está relacionada com a maneira como a disponibilidade de transportes e os usos do solo afetam os indivíduos na realização de viagens para o desenvolvimento de suas atividades habituais. Freqüentemente se assume que os moradores de baixa renda da periferia são os mais afetados pela falta de acesso aos meios de transporte. A questão subjacente a esta afirmação, no entanto, permanece sem uma resposta definitiva: o nível de renda, por si só, seria um indicativo do nível de acessibilidade? O objetivo deste estudo é explorar a união de ferramentas de estatística espacial e SIG (Sistema de Informações Geográficas) com um propósito específico, que é o de analisar as relações entre aspectos da distribuição espacial de características da população (como a renda, por exemplo) de uma cidade média brasileira e os diversos níveis de acessibilidade por diferentes modos de transporte nela observados, buscando possíveis respostas para esta pergunta. Quando se utiliza procedimentos de visualização e classificação de dados espaciais comuns em SIG, nem sempre as informações são diretamente perceptíveis. Logo, deve-se utilizar ferramentas que ampliem as possibilidades de compreensão e análise dos dados. Inicialmente, as ferramentas selecionadas para uso neste trabalho são apresentadas e discutidas quanto à sua aplicação e utilização na análise proposta. Para tal foram utilizados dados coletados em uma pesquisa origem–destino (O-D) realizada na cidade de Bauru - SP, agrupados por setores censitários e adicionados ao SIG, aplicando técnicas de estatística espacial utilizadas para entidades do tipo área. Os resultados obtidos são apresentados na forma de mapas e de índices que medem a associação espacial global e local entre estas zonas. Uma das conclusões interessantes da aplicação foi a identificação de regiões da cidade com dinâmica particular, que contrariam o padrão global observado nas demais partes da área urbana. Pôde-se constatar ainda particularidades a respeito do uso de cada modo de transportes. O modo automóvel como motorista, por exemplo, possui agrupamento espacial bem definido no nível de renda alta tanto nas regiões de periferia, como nas de transição e central. Já o modo ônibus é predominantemente utilizado nas zonas de renda baixa das regiões de periferia e transição, enquanto que os modos não motorizados possuem uma dinâmica bem diversificada em toda a área urbana. Estes e outros resultados do estudo de caso deixam claro que as análises de estatística espacial em ambiente SIG criam uma ferramenta para ampliar a análise convencional de acessibilidade em transportes / Transportation accessibility is directly related to the level of transportation supply and land uses and the way they affect individuals in their trip desires for accomplishing regular-basis activities. It is often assumed that low-income segments of the population living at the periphery of the cities are those affected the most by poor conditions of transportation accessibility. There is a subjacent question behind this statement, however, which is: can the income level or the location of an individual alone explain his/her accessibility level? In order to look for answers to this question, the aim of this study is to analyze, making use of spatial statistics tools in a GIS (Geographic Information System) environment, the relationships between accessibility and income and their geographical distributions in a medium-sized Brazilian city. The application of the most commonly used GIS resources, such as visualization and spatial data classification tools, not always assures a full comprehension of the phenomenon under analysis. As a consequence, many problems require tools that enhance the possibilities of observation and analysis. As tools with this characteristic have been used in this work, they were initially introduced. Thereafter, the possibilities of use of these tools in the problem analyzed were also discussed. Data of an origin-destination (O-D) survey carried out in the city of Bauru, located in the state of São Paulo, which brings information about four different transportation modes, were used in this study. Such data, grouped following the census tracts, were carefully examined in a Geographic Information System in order to look for spatial patterns of accessibility that are not visible in the traditional approaches. The results of the analysis are presented in maps and as indices that are able to capture glabal and local spatial association patterns in areas. One of the interesting outcomes of the application was the identification of regions with particular dynamics, which go against the pattern found in the overall urban area. Particularities regarding each particular transportation mode have also been noticed. The zones where the automobile is most used (by drivers, not by passengers) are spatially clustered, regardless if the zone is at the periphery, transition zone or central area of the city. The bus trips are predominantly carried out in low-income areas of the periphery and transition rings, while the non-motorized modes (walk and bicycle) have shown a very diversified dynamics in the entire urban area. This and other results of the case study clearly indicate that spatial statistics analyses in a GIS environment create a powerful tool to extend conventional transportation accessibility analysis

Made available in DSpace on 2017-05-12T14:47:34Z (GMT). No. of bitstreams: 1 DENISE_M_GR_ZEGOZEWSKI.pdf: 8188144 bytes, checksum: 045f54782a1ea2161edf5aa7046a8c1c (MD5) Previous issue date: 2016-02-03 / Estimates of agricultural production are greatly important especially in economy field. However, they depend on area knowledge and cropping yield. Thus, this study aimed to propose a methodology to estimate the areas cropped with soybeans and corn in Paraná State according to multi-temporal EVI/MODIS vegetation index images for 2010/2011, 2011/2012 and 2012/2013 crop years. In addition, there was a research with spatial autocorrelation soybean yield in Paraná, with EVI vegetation index and meteorological variables in a decennial scale and estimate yield using CAR, SAR and GWR models. In Paraná State, there is a drawback to map soybeans crop since corn sowing period is very close to the first one. Therefore, images from the maximum and minimum vegetative vigour were drawn of each studied crop for mapping soybean and corn crops in order to obtain both cropping areas. Although, for the separation, Spectro Angle Mapper algorithm (SAM) was applied by one of the studied crops, while mapping was obtained by multiplying the other bands. Thus, for spatial statistics application of mapped data, the average EV profile of each municipality was extracted as well as for each multi-temporal image, in order to change them into a decennial scale. According to the spatial statistics of such areas, the descriptive analysis of univariate spatial autocorrelation (global and local) of each ten-day variable was used based on the soybean cycle. A bivariate autocorrelation analysis between soybean yield and the studied varieties were also performed. Finalizing the methodology, variables with the highest significant level by stepwise method were selected and SAR, CAR and GWR models were generated to estimate soybean yield. As results, regarding mappings, the following answers for soybean were found out: r = 0.95 and r = 0.99, and while for corn, the answers were: r = 0.72 and r = 0.95 for 2012/2013 and 2013/2014 crop years in relation to the official data from SEAB. So, it has been proved some great efficiency of this methodology to separate and identify crops. When the descriptive statistics of municipalities for each variable was carried out, it was found out that some regions began an early sowing in relation to other ones in Paraná by the decennial vegetation index. The ten-day scale was also possible to be identified according to the climatic factors that caused soybean yield damage. Based on the analysis of spatial autocorrelation, the greatest similarities occurred in 2011/2012 crop year, the one affected by the weather change, whose yields were similar in the municipalities of Paraná State. For spatial modelling, it was observed that selection of decennial variables was different for each studied crop year, and the best model selected by the validation. And GWR was chosen as the best model by the AIC, BIC and adjusted R² validation criteria. The residuals were randomly distributed throughout all the State, so that spatial autocorrelation could be eliminated. / As estimativas das produções agrícolas têm grande importância, principalmente, no âmbito econômico. No entanto, elas são dependentes do conhecimento da área de cultivo e da produtividade da cultura. Desta forma, este trabalho teve por objetivo propor uma metodologia para estimar as áreas cultivadas com soja e milho em escala municipal no Estado do Paraná a partir de imagens multi-temporais do índice de vegetação EVI/MODIS, para os anos-safras 2010/2011, 2011/2012 e 2012/2013. Além disto, trabalhar com a autocorrelação espacial da produtividade da soja nesse Estado, com o índice de vegetação EVI e variáveis agrometeorológicas em escala decendial bem como estimar a produtividade a partir dos modelos CAR, SAR e GWR. No Paraná, há o inconveniente para mapear a soja devido à proximidade de datas de semeadura do milho. Assim, para o mapeamento da soja e do milho, utilizaram-se imagens englobando o período de máximo e mínimo vigor vegetativo de cada cultura, para se obter a área cultivada das duas. Para a separação, utilizou-se o algoritmo Spectro Angle Mapper (SAM) para uma das culturas e obteve-se o mapeamento da outra pela multiplicação de bandas. Para aplicação da estatística espacial dos dados mapeados, extraiu-se o perfil médio do EVI de cada município e para cada imagem multi-temporal para transformá-los em escala decendial. De acordo com a estatística espacial de áreas, utilizou-se a análise descritiva, de autocorrelação espacial univariada (global e local) de cada variável decendial com foco no ciclo da soja. Também realizou-se a análise de autocorrelação bivariada entre a produtividade da soja com as variáveis em estudo. Finalizando a metodologia, selecionaram-se as variáveis com maior índice de significância pelo método de stepwise e, em seguida, foram gerados os modelos estimados (SAR, CAR e GWR) da produtividade da soja. Como resultados, foram encontradas as seguintes respostas para os mapeamentos da soja r= 0,95 e 0,99, e para o milho de r = 0,72 e r= 0,95 para os anos-safras 2012/2013 e 2013/2014 em relação aos dados oficiais da SEAB. Logo, comprovou-se a grande eficiência da metodologia para separação e identificação das culturas. Quando realizada a estatística descritiva dos municípios para cada variável, verificaram-se regiões que iniciam as semeaduras antecipadas em relação a outras regiões do Estado pelos decêndios do índice de vegetação. Foi também possível identificar os decêndios em que os fatores climáticos causaram danos à produtividade da soja. Na análise da autocorrelação espacial, as maiores similaridades ocorreram no ano-safra 2011/2012, ano afetado pela variação climática, cujas produtividades foram semelhantes nos municípios do Paraná. Para a modelagem espacial, verificou-se que a seleção das variáveis decêndiais foi diferente para cada ano-safra estudado, e o GWR foi escolhido como melhor modelo pelos critérios de validação, AIC, BIC e R² ajustado. Foram encontrados resíduos distribuídos aleatoriamente por todo o Estado, para que assim se eliminasse a autocorrelação espacial