161 resultados para Spatial analysis
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Pós-graduação em Geografia - FCT
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Agronomia (Proteção de Plantas) - FCA
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Pós-graduação em Saúde Coletiva - FMB
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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A expansão da obesidade em diversos países do mundo na última década tem resultado no aumento da morbidade e mortalidade por hipertensão arterial e suas complicações. O objetivo deste trabalho é analisar a distribuição espacial da obesidade e hipertensão arterial no estado de São Paulo no período de 2000 a 2010, a partir de registros hospitalares e internação do Sistema de Informações Hospitalares do Sistema Único de Saúde (SIH - SUS). Foram utilizados coeficientes de prevalência das doenças em cada município suavizadas pelo método bayesiano empírico, permitindo uma visualização do padrão espacial dessas morbidades no Estado. Foi explorada a dependência espacial destes padrões verificando a autocorrelação entre os indicadores por meio do cálculo do Índice de Autocorrelação Espacial de Moran. Além disso, estudou-se a correlação positiva (Pearson) entre obesidade e hipertensão. Os dados e os mapas mostraram clusters de 87 municípios onde há maior e menor prevalência de hipertensão e obesidade no espaço com forte autocorrelação entre os municípios vizinhos. O coeficiente correlação de Pearson encontrado para esses municípios foi de 0,404 e sugere associação entre as morbidades. As técnicas de análise espacial mostraram-se úteis para o planejamento de ações de saúde pública.
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The objective of this study was to define a method for estimating soybean crop area in the Northern Rio Grande do Sul state (Brazil). Overall, six different remote sensing methods were proposed based on spectral-temporal profile and minimum and maximum values of NDVI/MODIS related to the stages of sowing, maximum development and harvesting of soybean areas. The resulting estimates were compared to official crop area data provided by the Brazilian government, using statistical analysis and the fuzzy similarity method. The performance of each method depended on information such as crop size, type of crop management, and sowing/harvesting dates. Regression coefficients of determination and fuzzy agreement values were above 0.8 and 0.45, respectively, for all methods. For operational monitoring of soybean crop area, the empirical threshold applied to the image difference with inclusion of harvest image method was the most effective, producing estimates that matched closely the official data. For spatial analysis the application of multitemporal images classification method is recommended that generated a map of better quality. The efficiency of these methods should be evaluated in the areas of soybean expansion in the state.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The concept of Functional Urban Regions (FURs), also called Metropolitan Regions (MRs), is not simple. It is clear, though, that they are not simply a combination of adjacent municipalities or areas. Different methods can be used for their definition. However, especially in developing countries, the application of some methods is not possible, due to the unavailability of detailed data. Alternative approaches have been developed based on spatial analysis methods and using variables extracted from available data. The objective of this study is to compare the results of two spatial analysis methods exploring two variables: population density and an indicator of transport infrastructure supply. The first method regards Exploratory Spatial Data Analyses tools, which define uniform regions based on specific variables. The second method used the same variables and the spatial analysis technique available in the computer program SKATER - Spatial 'K'luster Analysis by Tree Edge Removal. Assuming that those classifications of regions with similar characteristics can be used for identifying potential FURS, the results of all analyses were compared with one another and with the 'official' MR. A combined approach was also considered for comparison, but none of the results match the existing MR boundaries, what challenges the official definitions. (C) 2014 Elsevier Ltd. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This work discourse on Civil Defense’ strategic planning and severe events in the city of Rio Claro – SP. In order to realize spatial analysis about its damages, registered by Civil Defense Department, it is being propose a methodological procedure by the use of Geographical Information System – Arc Gis 9.3.1. and another with SPRING 5.1.8.. The mapping of target areas and their impacts, during a period, have a great importance to the identification of possible risk areas as well as their use for logistic support to corps which is somehow involved to severe events and their victims, and to create a robust alert system