888 resultados para Spatial Data Infrastructure (SDI)
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OBJETIVO Analisar mudanças espaciais no risco de Aids e a relação entre incidência da doença e variáveis socioeconômicas. MÉTODOS Estudo caso-controle espacial, de base populacional, realizado em Rondônia, Brasil, com 1.780 casos notificados pelo Sistema de Vigilância Epidemiológica e os controles a partir de dados demográficos de 1987 a 2006. Os casos foram agrupados em cinco períodos de cinco anos consecutivos. Um modelo aditivo generalizado foi ajustado aos dados. O status dos indivíduos (caso ou controle) foi considerado como a variável dependente e independente: um alisamento ( spline ) bidimensional das coordenadas geográficas e variáveis socioeconômicas municipais. Os valores observados para o teste Moran I foram comparados com a distribuição de referência dos valores obtidos em condições de aleatoriedade espacial. RESULTADOS O risco de Aids apresentou padrão espacial e temporal marcado. A incidência associou-se a indicadores socioeconômicos municipais, como urbanização e capital humano. As maiores taxas de incidência de Aids ocorreram em municípios ao longo da rodovia BR-364; os resultados do teste Moran I mostram correlação espacial positiva associada à contiguidade dos municípios com a rodovia, no terceiro e quarto períodos (p = 0,05). CONCLUSÕES A incidência da doença foi maior em municípios de maior riqueza econômica e urbanização e naqueles cortados pelas estradas principais de Rondônia. O rápido desenvolvimento associado à ocupação de regiões remotas pode ser acompanhado por aumento de riscos à saúde.
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In different regions of Brazil, population growth and economic development can degrade water quality, compromising watershed health and human supply. Because of its ability to combine spatial and temporal data in the same environment and to create water resources management (WRM) models, the Geographical Information System (GIS) is a powerful tool for managing water resources, preventing floods and estimating water supply. This paper discusses the integration between GIS and hydrological models and presents a case study relating to the upper section of the Paraíba do Sul Basin (Sao Paulo State portion), situated in the Southeast of Brazil. The case study presented in this paper has a database suitable for the basin's dimensions, including digitized topographic maps at a 50,000 scale. From an ArcGIS®/ArcHydro Framework Data Model, a geometric network was created to produce different raster products. This first grid derived from the digital elevation model grid (DEM) is the flow direction map followed by flow accumulation, stream and catchment maps. The next steps in this research are to include the different multipurpose reservoirs situated along the Paraíba do Sul River and to incorporate rainfall time series data in ArcHydro to build a hydrologic data model within a GIS environment in order to produce a comprehensive spatial-temporal model.
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This study aimed to analyze the spatial distribution of dengue risk and its association with socio-environmental conditions. This was an ecological study of the counts of autochthonous dengue cases in the municipality of Campinas, São Paulo State, Brazil, in the year 2007, aggregated according to 47 coverage areas of municipal health centers. Spatial models for mapping diseases were constructed with Bayesian hierarchical models, based on Integrated Nested Laplace Approximation (INLA). The analyses were stratified according to two age groups, 0 to 14 years and above 14 years. The results indicate that the spatial distribution of dengue risk is not associated with socio-environmental conditions in the 0 to 14 year age group. In the age group older than 14 years, the relative risk of dengue increases significantly as the level of socio-environmental deprivation increases. Mapping of socio-environmental deprivation and dengue cases proved to be a useful tool for data analysis in dengue surveillance systems.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Nowadays, the culture of the sugarcane plays an important role regarding the Brazilian reality, especially in the aspect related to the alternative energy sources. In 2009, the municipality of Suzanapolis (SP), in the Brazilian Cerrado, an experiment was conducted with the culture of the sugarcane in a Red eutrophic, with the aim of selecting, using Pearson correlation coefficients, modeling, simple, linear and multiple regressions and spatial correlation, and also the best technological and productive components, to explain the variability of the productivity of the sugarcane. The geostatistical grid was installed in order to collect the data, with 120 sampling points, in an area of 14.53 ha. For the simple linear regressions, the plants population is the component of production that presents the best quadratic correlation with the productivity of the sugarcane, given by: PRO = -0.553**xPOP(2)+16.14*xPOP-15.77. However, for multiple linear regressions, the equation PRO = -21.11+4.92xPOP**+0.76xPUR** is the one that best presents in order to estimate that productivity. Spatially, the best correlation with yield of the sugarcane is also determined by the component of the production population of plants.
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Pós-graduação em Geografia - FCT
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Context. The giant anteater, Myrmecophaga tridactyla, is a large insectivorous mammal from Cerrado which is classified as vulnerable by the IUCN's red list. In spite of frequent giant anteater casualties, there continues to be a lack of published data on how road and landscape attributes affect road-kill rates - information that could prove useful in guiding mitigation measures.Aims. We seek to determine whether road and landscape attributes influence the incidence of road-kills of the giant anteater.Methods. From February 2002 to December 2012 (except for 2004), five roads in two regions in south-eastern Brazil were surveyed twice each month by car. We recorded temporal road-kill data for the giant anteater and related spatial road variables. These variables were also recorded at regular control sites every 2 km. We also took traffic volume data on stretches of the two roads to correlate with road-kills.Key results. Of the 45 anteater casualties recorded, there was a predominance of adult males. On roads MG-428 and SP-334, we found anteater road-kills were more common in the dry season, negatively correlated with traffic volume and related to the presence of native vegetation. Accordingly, road-kill sites tended to occur near the cerrado and grasslands and also appeared more frequently on some straight stretches of roadways. Although it was not shown to influence road-kill rates, topography data does point to regular overpass/underpass locations allowing population connectivity. Termitaria or ant nests were present at all road-kill sites, with 86% having signs of feeding.Conclusions. Native vegetation along roadways, together with straight road design, increases the probability of anteater road-kills by 40.1%.Implications. For mitigation, mowing and removing insect nests on roadsides, as well as roadside wildlife fencing in cerrado and grassland areas is suggested. Warning signs and radar to reduce vehicle speed are recommended for both human safety and anteater conservation. With regard to population connectivity, the absence of aggregated anteater road-kill data in this study meant that there were no particular crossing locations identified. However, the collected topography data do show places that could be used for roadway crossings. The measures indicated may apply to similar species and types of topography on other continents.