999 resultados para Imagens de alta resolução


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Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Detecção Remota e Sistemas de Informação Geográfica

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Dissertação de Mestrado em Gestão do Território, Área de Especialização em Detecção Remota e Sistemas de Informação Geográfica

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The spatial resolution improvement of orbital sensors has broadened considerably the applicability of their images in solving urban areas problems. But as the spatial resolution improves, the shadows become even a more serious problem especially when detailed information (under the shadows) is required. Besides those shadows caused by buildings and houses, clouds projected shadows are likely to occur. In this case there is information occlusion by the cloud in association with low illumination and contrast areas caused by the cloud shadow on the ground. Thus, it's important to use efficient methods to detect shadows and clouds areas in digital images taking in count that these areas care for especial processing. This paper proposes the application of Mathematical Morphology (MM) in shadow and clouds detection. Two parts of a panchromatic QuickBird image of Cuiab-MT urban area were used. The proposed method takes advantage of the fact that shadows (low intensity - dark areas) and clouds (high intensity - bright areas) represent the bottom and top, respectively, of the image as it is thought to be a topographic surface. This characteristic allowed MM area opening and closing operations to be applied to reduce or eliminate the bottom and top of the topographic surface.

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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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The metropolitan region of São Paulo is the most populous of the country, this happens because of its great importance in the national economy and the job opportunities that are offered to the population. These factors result in intense population growth and urban expansion, reaching some non-habitable places of the metropolis, as areas of pipelines, which are very important for the transportation of natural gas, oil and its derivatives. Before the population growth of the region, these sites were unoccupied, do not presenting problems for the population. However, with the disorderly occupation is generated great anthropogenic pressure on the pipeline stitches, causing risks to people who are around them. Therefore it is extremely important to monitor the strip of pipelines through products and techniques of remote sensing and geoprocessing, enabling, through high spatial resolution images, identification of objects or phenomena that occur on Earth's surface that can alter the functioning and safety of pipelines. Therefore, this study aims to monitor a stretch of the area of the pipeline mesh GASPAL/OSVAT and Capuava Refinery (RECAP), located on the outskirts of the metropolitan area of São Paulo in the city of Mauá, who suffer great human pressure, proving thus the techniques of remote sensing and geographic information system (GIS) as effective tools for monitoring phenomena occurred in urban areas of great complexity. The monitoring was done by object-based classification applied in orbital images Ikonos II and RapidEye, of high spatial resolution and, image processing, detection of objects, segmentation, classification and editing were developed through the eCognition and ArcGis softwares. To determine the statistical accuracy of the mapping of the land cover of the stretch of pipeline in Maua, the results were analyzed by error matrix... (Complete abstract click electronic access below)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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O objetivo deste trabalho foi gerar um modelo digital de terreno (MDT) e delimitar sub-bacias hidrográficas na área de estudo do projeto ?Sustentabilidade, competividade e valoração de serviços ecossistêmicos da heveicultura em São Paulo com uso de geotecnologias? (GeoHevea). O MDT foi gerado em ambiente de sistema de informações geográficas (SIG) a partir de cartas topográficas digitais e de imagens de alta resolução espacial. Os arquivos vetoriais relativos a curvas de nível, pontos cotados, rede hidrográfica e corpos d?água foram obtidos do Instituto Brasileiro de Geografia e Estatística (IBGE). Os arquivos da rede hidrográfica e dos corpos d?água do IBGE foram editados manualmente no SIG ArcGIS 10.3, tomando como base ortofotos da Empresa Paulista de Planejamento Metropolitano S/A (Emplasa). Na geração do MDT, foi utilizado o interpolador Topo to Raster do ArcGIS. Na delimitação das sub-bacias foi utilizada a extensão ArcHydro Tools no ArcGIS. Os resultados obtidos demonstraram que a rede hidrográfica digital das folhas topográficas disponibilizadas pelo IBGE necessita de ajustes. O MDT gerado pelo interpolador Topo to Raster apresentou menos rugosidades que o modelo digital de elevação (MDE) do Shuttle Radar Topography Mission (SRTM). A metodologia empregada neste estudo pode ser aplicada a outras regiões do Estado de São Paulo para a geração de MDTs. A delimitação das bacias hidrográficas da área de estudo do projeto GeoHevea identificou quatro sub-bacias: do Ribeirão Santa Bárbara, do Ribeirão dos Ferreiros ou das Oficinas, do Ribeirão São Jerônimo e do Córrego da Arribada.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Dissertação de Mestrado em Gestão do Território, Especialização em Detecção Remota e Sistemas de Informação Geográfica

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The habitat loss and fragmentation are considered the main threats to the biodiversity. These threats operate at the landscape level, which drives the need to manage entire landscapes, not just its components. Although systematic monitoring of the Atlantic Forest biome has been ongoing since the late eighties, current data on forest fragmentation for the sub-region of Pernambuco are practically nonexistent. This study aimed to map out, with high spatial resolution, the remnants of Atlantic forest in Rio Grande do Norte, and conduct a landscape level analysis. The results show that the landscape is highly fragmented, where about 13.6% to 17% of biome remains. Most of the fragments is less than 10 ha, while a few fragments have area larger than 100 ha. Although the high degree of fragmentation, the average distance between fragments found was small (128 m), this estimate is lower than has been observed for the biome (1440m). There is evidence that abrupt changes in the quantification of landscape structure can occur when one observes the fragmentation at high spatial resolution. The results presented here can be used in management actions, in order to make the scenario more conducive to maintaining biodiversity.