81 resultados para large geographical area


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The structural health monitoring (SHM) systems based on electromechanical (E/M) impedance technique have been widely investigated. Although many studies indicate the reliability of this technique, some practical considerations still have to be considered in real applications. This paper presents an experimental analysis of the effect of the structure area on the system's performance. The results indicate that the sensitivity of the system to detect damage decreases significantly when the host structure has large cross-section area. Copyright © 2009 by ASME.

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Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of São Paulo, in the city of Cubatão, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar. © 2011 SPIE.

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The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.

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Increased urbanization typically leads to an increase in abundance of a few species and a reduction in bird species richness. Understanding the structure of biotic communities in urban areas will allow us to propose management techniques and to decrease conflicts between wild species and human beings. The objective of this study was to describe the structure of the bird community in an urban ecosystem. The study was carried out in the city of Taubaté in southeastern Brazil. Point-counts were established in areas with different levels of tree density ranging from urban green spaces to predominantly built-up areas. We looked for a correlation between the richness/abundance of birds and the size of the area surveyed, the number of houses, the number of tree species and the number of individual trees. The results of multiple regression showed that bird richness had a direct relationship with vegetation complexity. The abundance and diversity of tree species were better predictors of bird species than the number of houses and size of the area surveyed. We discuss implications of this study for conservation and management of bird diversity in urban areas, such as the need to increase green areas containing a large diversity of native plant species. © 2011 Springer Science+Business Media, LLC.

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The objective of this study was to address the importance of implementing Coastal and Marine Protected Areas in Brazil and to examine their distribution, based on the delimitation of Large Marine Ecosystems. Out of a total of 336 protected areas identified in Brazilian coastal and marine areas, the North Platform has the largest protected area, but the ecosystem with the largest number of protected area, predominantly sustainable areas, was the East Coast followed by the South Platform. One of the reasons the eastern coast of Brazil to have more protected areas is the fact that there is a largest amount of coral reefs. Additionally there was political opportunities for the creation of protected areas for sustainable use. The coastal region of Brazil has achieved the goal proposed by the Seventh Conference of the Parties to the Convention on Biological Diversity - 7, but only then through the category V of the International Union for Conservation of Nature, which is not the best efficient means of conserving resources. The goal for marine conservation shows only the area above the recommended under protection in North Platform. The Marine portion of the East Coast and the South Platform has few protected areas, regardless of category management. We consider the coastal region the range of 12 nautical miles from baselines determined in accordance with the United Nations Convention on the Law of the Sea. As for the number of strategies permitted by law and used for the conservation of coastal and marine systems, coastal systems show a higher number when compared with the marine system. We suggest that the Brazilian government should specify strategies for the protection of marine systems and expand the protected areas of all Large Marine Ecosystems. © 2013 Elsevier Ltd.

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Pós-graduação em Ciências Cartográficas - FCT

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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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Soil CO2 emission (F-CO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere. F-CO2 varies in time and space depending on environmental conditions, including the management of the agricultural area. The aim of this study was to investigate the spatial variability structure of F-CO2 and soil attributes in a mechanically harvested sugarcane area (green harvest) using fractal dimension (D-F) derived from isotropic variograms at different scales (fractograms). F-CO2 showed an overall average of 1.51 mu mol CO2 m(-2) s(-1) and correlated significantly (P < 0.05) with soil physical attributes, such as soil bulk density, air-filled pore space, macroporosity and microporosity. Topologically significant DF values were obtained from the characterization of F-CO2 at medium and large scales (above 20 m), with values of 2.92 and 2.90, respectively. The variations in D-F with scales indicate that the spatial variability structure of F-CO2 was similar to that observed for soil temperature and total pore volume and was the inverse of that observed for other soil attributes, such as soil moisture, soil bulk density, microporosity, air-filled pore space, silt and clay content, pH, available phosphorus and the sum of bases. Thus, the spatial variability structure of F-CO2 presented a significant relationship with the spatial variability structure for most soil attributes, indicating the possibility of using fractograms as a tool to better describe the spatial dependence of variables along the scale. (C) 2014 Elsevier B.V. All rights reserved.

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Pós-graduação em Ciências Biológicas (Zoologia) - IBB

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