877 resultados para GEOGRAPHIC INFORMATION-SYSTEMS
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The northern coast of Rio Grande do Norte State (RN) shows areas of Potiguar basin with high activity in petroleum industry. With the goal of avoiding and reducing the accident risks with oil it is necessary to understand the natural vulnerability, mapping natural resources and monitoring the oil spill. The use of computational tools for environmental monitoring makes possible better analyses and decisions in political management of environmental preservation. This work shows a methodology for monitoring of environment impacts, with purpose of avoiding and preserving the sensible areas in oil contact. That methodology consists in developing and embedding an integrated computational system. Such system is composed by a Spatial Decision Support System (SDSS). The SDSS shows a computational infrastructure composed by Web System of Geo-Environmental and Geographic Information - SWIGG , the System of Environmental Sensibility Maps for Oil Spill AutoMSA , and the Basic System of Environmental Hydrodynamic ( SisBAHIA a System of Modeling and Numerical Simulating SMNS). In a scenario of oil spill occurred coastwise of Rio Grande do Norte State s northern coast, the integration of such systems will give support to decision agents for managing of environmental impacts. Such support is supplied through a system of supporting to spatial decisions
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This study includes the results of the analysis of areas susceptible to degradation by remote sensing in semi-arid region, which is a matter of concern and affects the whole population and the catalyst of this process occurs by the deforestation of the savanna and improper practices by the use of soil. The objective of this research is to use biophysical parameters of the MODIS / Terra and images TM/Landsat-5 to determine areas susceptible to degradation in semi-arid Paraiba. The study area is located in the central interior of Paraíba, in the sub-basin of the River Taperoá, with average annual rainfall below 400 mm and average annual temperature of 28 ° C. To draw up the map of vegetation were used TM/Landsat-5 images, specifically, the composition 5R4G3B colored, commonly used for mapping land use. This map was produced by unsupervised classification by maximum likelihood. The legend corresponds to the following targets: savanna vegetation sparse and dense, riparian vegetation and exposed soil. The biophysical parameters used in the MODIS were emissivity, albedo and vegetation index for NDVI (NDVI). The GIS computer programs used were Modis Reprojections Tools and System Information Processing Georeferenced (SPRING), which was set up and worked the bank of information from sensors MODIS and TM and ArcGIS software for making maps more customizable. Initially, we evaluated the behavior of the vegetation emissivity by adapting equation Bastiaanssen on NDVI for spatialize emissivity and observe changes during the year 2006. The albedo was used to view your percentage of increase in the periods December 2003 and 2004. The image sensor of Landsat TM were used for the month of December 2005, according to the availability of images and in periods of low emissivity. For these applications were made in language programs for GIS Algebraic Space (LEGAL), which is a routine programming SPRING, which allows you to perform various types of algebras of spatial data and maps. For the detection of areas susceptible to environmental degradation took into account the behavior of the emissivity of the savanna that showed seasonal coinciding with the rainy season, reaching a maximum emissivity in the months April to July and in the remaining months of a low emissivity . With the images of the albedo of December 2003 and 2004, it was verified the percentage increase, which allowed the generation of two distinct classes: areas with increased variation percentage of 1 to 11.6% and the percentage change in areas with less than 1 % albedo. It was then possible to generate the map of susceptibility to environmental degradation, with the intersection of the class of exposed soil with varying percentage of the albedo, resulting in classes susceptibility to environmental degradation
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P>In livestock genetic resource conservation, decision making about conservation priorities is based on the simultaneous analysis of several different criteria that may contribute to long-term sustainable breeding conditions, such as genetic and demographic characteristics, environmental conditions, and role of the breed in the local or regional economy. Here we address methods to integrate different data sets and highlight problems related to interdisciplinary comparisons. Data integration is based on the use of geographic coordinates and Geographic Information Systems (GIS). In addition to technical problems related to projection systems, GIS have to face the challenging issue of the non homogeneous scale of their data sets. We give examples of the successful use of GIS for data integration and examine the risk of obtaining biased results when integrating datasets that have been captured at different scales.
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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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Os Sistemas de Informação Geográfica constituem importantes instrumentos dentro da Saúde Pública como técnicas de análise da distribuição de agravos à população, e, portanto, podem ser usados no estudo da localização de indivíduos portadores de doenças crônicas. Este trabalho objetivou a realização de análise espacial da distribuição da população de sessenta anos e mais no Município de Botucatu, São Paulo, Brasil, estudando o perfil sócio-demográfico e a presença de diabetes e hipertensão arterial. Foram analisados dados de 468 idosos da amostra de inquérito populacional realizado entre 2001 e 2002. Os idosos com melhor nível sócio-econômico residem nos setores censitários de estratos sociais mais altos, o que foi estatisticamente comprovado pela utilização de técnicas de análise espacial para renda e escolaridade. Não se encontrou padrão de distribuição espacial para idosos hipertensos e diabéticos que se localizaram no mapa de forma heterogênea. O presente estudo sugere a utilização das técnicas de geoprocessamento para o mapeamento digital das áreas de abrangências das Unidades de Atenção Primária à Saúde, para um melhor controle da distribuição de idosos portadores de doenças crônicas e de sua assistência pelos profissionais de saúde.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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OBJETIVO: Analisar o padrão espacial da ocorrência dos casos de hanseníase para identificar áreas com probabilidade de riscos de transmissão da doença. MÉTODOS: Estudo ecológico, tendo como unidade de análise os municípios do Estado de São Paulo georreferenciados em seus centróides. A fonte de dados utilizada foi o banco informatizado dos casos de hanseníase notificados do Centro de Vigilância Epidemiológica do Estado de São Paulo, no período de 1991 a 2002. Utilizou-se de técnicas de geoestatística para a detecção das áreas de probabilidade de risco para hanseníase e quantificação da dependência espacial dos casos. RESULTADOS: Detectou-se o alcance de dependência espacial de 0,55 graus de coordenadas georreferenciadas, correspondendo aproximadamente a 60 km. As principais áreas de probabilidade de risco encontradas foram as regiões nordeste, norte e noroeste do Estado. CONCLUSÕES: A verificação de áreas com probabilidades de riscos de casos de hanseníase, utilizando-se a análise da dependência espacial, pode ser ferramenta útil para avaliar a situação de saúde e planejar alocação de recursos.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Este artigo tem por objetivo identificar padrões na distribuição espacial dos casos de dengue ocorridos no município de Cruzeiro/SP, no ano de 2006. Trata-se de um estudo ecológico e exploratório que utiliza as ferramentas de análise espacial na elaboração de mapas temáticos, com dados obtidos do SinanNet. Foi feita uma análise por área, tomando-se como unidade o setor censitário do IBGE; a análise considerou quatro meses do ano de 2006 que mostra a ocorrência da doença no município. Os mapas temáticos foram construídos pelo programa computacional TerraView 3.3.1; assim como os valores dos índices de Moran Global (I M) mês a mês e o estimador de Kernel. Foram georreferenciados 691 casos de dengue (taxa de 864,2 casos/100.000 habitantes); os Índices de Moran e p-valores obtidos foram I M = 0,080 (março) p = 0,11; I M = 0,285 (abril) p = 0,01; I M = 0,201 (maio) p = 0,01 e I M = 0,002 (junho) p = 0,57. Os primeiros casos foram identificados na região nordeste e central e os últimos casos, na região norte, nordeste e central. Foi possível identificar os setores censitários onde a epidemia teve início e como ocorreu têmporo-espacialmente no município.
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Globalisation trends and biorterrorism issues have led to new concerns relating to public health, animal health, international trade and food security. There is an imperative to internationalise and strengthen global public health capacity by renewed emphasis on veterinary public health in veterinary education and increasing opportunities for elective experiential learning in public practice programmes for veterinary students. Recent experience with a US-Brazil Higher Education Consortia Program is used as an example of potential ways in which veterinary students can gain an appreciation for global veterinary issues.
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The acquisition and update of Geographic Information System (GIS) data are typically carried out using aerial or satellite imagery. Since new roads are usually linked to georeferenced pre-existing road network, the extraction of pre-existing road segments may provide good hypotheses for the updating process. This paper addresses the problem of extracting georeferenced roads from images and formulating hypotheses for the presence of new road segments. Our approach proceeds in three steps. First, salient points are identified and measured along roads from a map or GIS database by an operator or an automatic tool. These salient points are then projected onto the image-space and errors inherent in this process are calculated. In the second step, the georeferenced roads are extracted from the image using a dynamic programming (DP) algorithm. The projected salient points and corresponding error estimates are used as input for this extraction process. Finally, the road center axes extracted in the previous step are analyzed to identify potential new segments attached to the extracted, pre-existing one. This analysis is performed using a combination of edge-based and correlation-based algorithms. In this paper we present our approach and early implementation results.
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Riparian forest restoration projects in the Tropics are complex, demanding longterm research, continuous human efforts and correct use of financial resources. This paper presents an approach to rank priority areas for riparian forest restoration on the upper section of the Pardo River watershed, in São Paulo, Brazil, using remote sensing and GIS techniques. Pardo River watershed is specially important, since it is the major source of drinking water supply for the region and water for domestic and industrial use within Botucatu and surrounding. Results indicated that riparian restoration should involve 81,27% of the protected area and could be made in three phases, allocating resources according to a priority scale.
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Semi-automatic building detection and extraction is a topic of growing interest due to its potential application in such areas as cadastral information systems, cartographic revision, and GIS. One of the existing strategies for building extraction is to use a digital surface model (DSM) represented by a cloud of known points on a visible surface, and comprising features such as trees or buildings. Conventional surface modeling using stereo-matching techniques has its drawbacks, the most obvious being the effect of building height on perspective, shadows, and occlusions. The laser scanner, a recently developed technological tool, can collect accurate DSMs with high spatial frequency. This paper presents a methodology for semi-automatic modeling of buildings which combines a region-growing algorithm with line-detection methods applied over the DSM.
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Geographic Information Systems (GIS) integrate the technologies related to Geoprocessing, with the ability to manipulate georeferenced information through data storage, management and analysis. One of the GIS applications is the generation of Digital Elevation Models (DEM) as a result of rebuilding the elevation of a region using computation tools and artificial representation. This paper presents the DEM created from a point base in two computational frameworks with different structures (vector and raster), comparing the contour lines generated from these models with the original contour lines from analog cartographic base. It was observed that one of the generated models presented some discrepancies related to real space for both GIS structures. However, using constrained Delaunay's triangulation in raster GIS a digital elevation model was generated with contour lines quite close to the original ones, with satisfactory results. A 3-D terrain representation was also created offering a very useful tool for analysis.