30 resultados para Análise spectral

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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The current accessibility to hyperspectral images of Hyperion/EO1 orbital sensor has brought new perspectives for studies of aquatic environments for allowing the remote estimative of several optically active constituents (OACs) in water body. The changes in the composition and concentration of OACs cause different patterns of absorption and scattering of electromagnetic radiation, likely to be detected using hyperspectral data. Therefore, an investigation was conducted taking into account the spectral characterization of water of a reservoir intended for public supply (Itupararanga Reservoir), from Hyperion/EO1 images and derivative analysis technique applied to spectral curves generated. Simultaneously to the acquisition of a Hyperion/EO1 image, a field campaign was carried out to collect limnological data in situ in georeferenced points. After radiometric correction of the image, reflectance curves of pixels were extracted for each station and the curves obtained were subjected to the technique of derivative analysis, which revealed features of absorption and scattering mainly associated to the presence of algal pigments. The results obtained show the presence of phytoplankton and algal activity, matching the field observation.

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GPS active networks are more and more used in geodetic surveying and scientific experiments, as water vapor monitoring in the atmosphere and lithosphere plate movement. Among the methods of GPS positioning, Precise Point Positioning (PPP) has provided very good results. A characteristic of PPP is related to the modeling and/or estimation of the errors involved in this method. The accuracy obtained for the coordinates can reach few millimeters. Seasonal effects can affect such accuracy if they are not consistent treated during the data processing. Coordinates time series analyses have been realized using Fourier or Harmonics spectral analyses, wavelets, least squares estimation among others. An approach is presented in this paper aiming to investigate the seasonal effects included in the stations coordinates time series. Experiments were carried out using data from stations Manaus (NAUS) and Fortaleza (BRFT) which belong to the Brazilian Continuous GPS Network (RBMC). The coordinates of these stations were estimated daily using PPP and were analyzed through wavelets for identification of the periods of the seasonal effects (annual and semi-annual) in each time series. These effects were removed by means of a filtering process applied in the series via the least squares adjustment (LSQ) of a periodic function. The results showed that the combination of these two mathematical tools, wavelets and LSQ, is an interesting and efficient technique for removal of seasonal effects in time series.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Análise espectral de flores utilizada por aves nectarívoras em áreas urbanas. O objetivo deste trabalho foi estabelecer a característica espectral das flores produtoras de néctar visitadas por nectarívoros em áreas urbanas. Este estudo foi desenvolvido na região central do município de Taubaté, no nordeste do Estado de São Paulo. As áreas amostradas incluíram espaços verdes, tais como praças e parques e a vegetação das ruas e avenidas. Foram registradas 12 espécies de plantas utilizadas por cinco espécies de aves nectarívoras. As espécies de flores mais visitadas foram aquelas que refletiram em comprimento de onda longos (>600 nm). Foi discutida a capacidade de detecção das aves em função de visão tetracromática das aves nectarívoras e da conspicuidade das flores em ambientes urbanos. Finalmente, foi abordado o problema da escassez de plantas atrativas para aves nectarívoras nas áreas verdes urbanas e a necessidade de se aumentar a quantidade dessas espécies de plantas para incrementar a biodiversidade em regiões urbanas.

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The great diversity of materials that characterizes the urban environment determines a structure of mixed classes in a classification of multiespectral images. In that sense, it is important to define an appropriate classification system using a non parametric classifier, that allows incorporating non spectral (such as texture) data to the process. They also allow analyzing the uncertainty associated to each class from the output alues of the network calculated in relation to each class. Considering these properties, an experiment was carried out. This experiment consisted in the application of an Artificial Neural Network aiming at the classification of the urban land cover of Presidente Prudente and the analysis of the uncertainty in the representation of the mapped thematic classes. The results showed that it is possible to discriminate the variations in the urban land cover through the application of an Artificial Neural Network. It was also possible to visualize the spatial variation of the uncertainty in the attribution of classes of urban land cover from the generated representations. The class characterized by a defined pattern as intermediary related to the impermeability of the urban soil presented larger ambiguity degree and, therefore, larger mixture.

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GPS active networks are more and more used in geodetic surveying and scientific experiments, as water vapor monitoring in the atmosphere and lithosphere plate movement. Among the methods of GPS positioning, Precise Point Positioning (PPP) has provided very good results. A characteristic of PPP is related to the modeling and / or estimation of the errors involved in this method. The accuracy obtained for the coordinates can reach few millimeters. Seasonal effects can affect such accuracy if they are not consistent treated during the data processing. Coordinates time series analyses have been realized using Fourier or Harmonics spectral analyses, wavelets, least squares estimation among others. An approach is presented in this paper aiming to investigate the seasonal effects included in the stations coordinates time series. Experiments were carried out using data from stations Manaus (NAUS) and Fortaleza (BRFT) which belong to the Brazilian Continuous GPS Network (RBMC). The coordinates of these stations were estimated daily using PPP and were analyzed through wavelets for identification of the periods of the seasonal effects (annual and semi-annual) in each time series. These effects were removed by means of a filtering process applied in the series via the least squares adjustment (LSQ) of a periodic function. The results showed that the combination of these two mathematical tools, wavelets and LSQ, is an interesting and efficient technique for removal of seasonal effects in time series.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Ciências Cartográficas - 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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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Engenharia Mecânica - FEB

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Pós-graduação em Engenharia Mecânica - FEG