879 resultados para Geociencias - Sensoriamento remoto


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Como o empréstimo de palavras ocorre em praticamente todas as línguas, o objetivo desta pesquisa foi examinar um corpus paralelo na área de sensoriamento remoto para analisar termos simples, complexos e compostos traduzidos por meio de empréstimo linguístico. Esta investigação baseou-se na abordagem adotada por CAMARGO (2005, 2007), a qual se apóia nos Estudos da Tradução Baseados em Corpus (BAKER, 1995, 1996; TOGNINI-BONELLI, 2001), na Linguística de Corpus (BERBER SARDINHA, 2004) e, em parte, na Terminologia (BARROS; KRIEGER & FINATTO, 2004). Para a extração dos dados foi utilizado o programa WordSmith Tools, versão 6.0 (SCOTT, 2012). No tocante aos resultados, foram encontrados termos traduzidos por meio de empréstimos com explicitação, quando de sua primeira utilização no texto.

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The aim is to analyze a corpus of remote sensing in order to identify acronyms in English and then search for their equivalents in Portuguese. The research is based on the approach of Corpus-Based Translation Studies (BAKER, 1995), Corpus Linguistics (BERBER SARDINHA, 2004), and Phraseology (PAVEL, 2003). The program WordSmith Tools version 6.0 is used. The results show that there is no standardization in these translations.

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Brazil was one of the countries that stood out in the list of nations that publishes more articles in scientific journals. From 2007 to 2008, the Brazilian scientific production has moved from 15th to 13rd place in the world ranking published articles in professional journals. However, 60% of articles published by the Brazilians are in Portuguese, which makes the Brazilian work have little international attention. The purpose of this research is to build and analyze a parallel corpus composed of a book of Remote Sensing and its translation in the direction English into Portuguese in order to create a glossary of most recurrent terms in the literature of Remote Sensing. The achievement of these goals will take for theoretical and methodological foundation the Corpus-Based Translation Studies (BAKER, 1993, 1995, 1996; CAMARGO, 2005), Corpus Linguistics (BERBER SARDINHA, 2004) and principles of Terminology (BARROS, 2004; KRIEGER & FINATTO, 2004). It will also use Wordsmith Tools program and its tools. Besides the parallel corpus, we will also build two comparable corpora respectively from articles published in Brazilian and international journals in the area. The first results show that the translators made use of greater variation of vocabulary in their translations, which can be a way to make the text more clear to the reader. For the analysis of glossary entries, professionals from the National Institute for Space Research - INPE, will be consulted and their views aggregated to this research to give consistency to the production of the proposed bilingual glossary.

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The aim of this research is to build and analyze a parallel corpus in the field of remote sensing in order to identify, according to its frequency, specialized collocations in English and then search for their equivalents in Portuguese. The research is based on the interdisciplinary approach of Corpus-Based Translation Studies (BAKER, 1995; CAMARGO, 2007), Corpus Linguistics (BERBER SARDINHA, 2004; TOGNINI-BONELLI, 2001), Phraseology (ORENHA-OTTAIANO, 2009; PAVEL, 1993), and some principles of Terminology (BARROS, 2004). For manipulating the corpora, the program WordSmith Tools (SCOTT, 2012) version 6.0 is used. To support this study, two comparable corpora in English and Portuguese were also built from articles published in both national and international journals in remote sensing. The results show that the collocations in Portuguese seem to be still in the process of conventionalization, as the translators made use of greater variation in their translational options, which can be a way to make the text clearer for the reader.

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

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Blooms of phytoplankton can be a risk to human health and aquatic biota, so the adoption of monitoring methods of phytoplankton and mechanisms for preventing its occurrence are needed. Thus, traditional monitoring methods could be more effective if complemented by approaches using the optical properties of phytoplankton pigments by means of Remote Sensing. In order to evaluate the potential of multi-scale remote sensing for detection of the phytoplankton activity, a study area was selected in Nova Avanhandava reservoir, located in the Tiete River, SP. For this analysis, hyperspectral field data and multispectral images of low and medium spatial resolution (Modis and RapidEye) were acquired and were related to indicator limnological variables of phytoplankton behavior; chlorophyll a and phycocyanin. The results show that a specific spectral band of RapidEye system (690-730 nm) allowed detect chlorophyll a and to evaluate the phytoplankton biomass, however hyperspectral data are needed to detect the phycocyanin pigment, indicative of cyanobacteria.

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Pós-graduação em Agronomia (Ciência do Solo) - FCAV

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The aim of this work is to discriminate vegetation classes throught remote sensing images from the satellite CBERS-2, related to winter and summer seasons in the Campos Gerais region Paraná State, Brazil. The vegetation cover of the region presents different kinds of vegetations: summer and winter cultures, reforestation areas, natural areas and pasture. Supervised classification techniques like Maximum Likelihood Classifier (MLC) and Decision Tree were evaluated, considering a set of attributes from images, composed by bands of the CCD sensor (1, 2, 3, 4), vegetation indices (CTVI, DVI, GEMI, NDVI, SR, SAVI, TVI), mixture models (soil, shadow, vegetation) and the two first main components. The evaluation of the classifications accuracy was made using the classification error matrix and the kappa coefficient. It was defined a high discriminatory level during the classes definition, in order to allow separation of different kinds of winter and summer crops. The classification accuracy by decision tree was 94.5% and the kappa coefficient was 0.9389 for the scene 157/128. For the scene 158/127, the values were 88% and 0.8667, respectively. The classification accuracy by MLC was 84.86% and the kappa coefficient was 0.8099 for the scene 157/128. For the scene 158/127, the values were 77.90% and 0.7476, respectively. The results showed a better performance of the Decision Tree classifier than MLC, especially to the classes related to cultivated crops, indicating the use of the Decision Tree classifier to the vegetation cover mapping including different kinds of crops.

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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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O uso de imagens de satélite e fotografias aéreas são cada vez mais comuns na obtenção de dados sobre recursos ambientais, como os cursos d?água. Deste modo, o presente trabalho objetivou comparar três diferentes produtos de Sensoriamento Remoto no mapeamento visual de drenagens e nascentes: imagens do satélite SPOT/Ikonos, imagens do programa Google Earth® e fotografias aéreas, na Microbacia Hidrográfica do Córrego do Ceveiro (MHC), localizada em Piracicaba/SP. Utilizou-se rede de drenagem presente em cartas topográficas do IGC/SP, escala 1:10.000, como base para comparação. Foram analisados dois fatores: comprimento de drenagem (CD) e número de nascentes (NN), sendo as análises realizadas apenas em caráter quantitativo. Para o CD, o produto SPOT se mostrou mais semelhante às cartas 1:10.000, apresentando 1,43% acima do CD existente nas cartas. Para o NN, a fotografia aérea mostrou o coeficiente mais alto, sendo esse o produto analisado que apresentou maior equivalência com o valor das nascentes observadas nas cartas.

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Oil spills in marine environments represent immediate environmental impacts of large magnitude. For that reason the Environmental Sensitivity to Oil Maps constitute a major instrument for planning actions of containment and cleanup. For both the Environmental Sensitivity Maps always need to be updated, to have an appropriate scale and to represent accurately the coastal areas. In this context, this thesis presents a methodology for collecting and processing remote sensing data for the purpose of updating the territorial basis of thematic maps of Environmental Sensitivity to Oil. To ensure greater applicability of the methodology, sensors with complementary characteristics, which provide their data at a low financial cost, were selected and tested. To test the methodology, an area located on the northern coast of the Northeast of Brazil was chosen. The results showed that the products of ASTER data and image hybrid sensor PALSAR + CCD and HRC + CCD, have a great potential to be used as a source of cartographic information on projects that seek to update the Environmental Sensitivity Maps of Oil

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Tese (doutorado)—Universidade de Brasília, Instituto de Geociências, Pós-Graduação em Geociências Aplicadas, 2016.