20 resultados para satellite data processing

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


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Nowadays, L1 SBAS signals can be used in a combined GPS+SBAS data processing. However, such situation restricts the studies over short baselines. Besides of increasing the satellite availability, SBAS satellites orbit configuration is different from that of GPS. In order to analyze how these characteristics can impact GPS positioning in the southeast area of Brazil, experiments involving GPS-only and combined GPS+SBAS data were performed. Solutions using single point and relative positioning were computed to show the impact over satellite geometry, positioning accuracy and short baseline ambiguity resolution. Results showed that the inclusion of SBAS satellites can improve the accuracy of positioning. Nevertheless, the bad quality of the data broadcasted by these satellites limits their usage. © Springer-Verlag Berlin Heidelberg 2012.

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The CMS Collaboration conducted a month-long data taking exercise, the Cosmic Run At Four Tesla, during October-November 2008, with the goal of commissioning the experiment for extended operation. With all installed detector systems participating, CMS recorded 270 million cosmic ray events with the solenoid at a magnetic field strength of 3.8 T. This paper describes the data flow from the detector through the various online and offline computing systems, as well as the workflows used for recording the data, for aligning and calibrating the detector, and for analysis of the data. © 2010 IOP Publishing Ltd and SISSA.

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Until mid 2006, SCIAMACHY data processors for the operational retrieval of nitrogen dioxide (NO2) column data were based on the historical version 2 of the GOME Data Processor (GDP). On top of known problems inherent to GDP 2, ground-based validations of SCIAMACHY NO2 data revealed issues specific to SCIAMACHY, like a large cloud-dependent offset occurring at Northern latitudes. In 2006, the GDOAS prototype algorithm of the improved GDP version 4 was transferred to the off-line SCIAMACHY Ground Processor (SGP) version 3.0. In parallel, the calibration of SCIAMACHY radiometric data was upgraded. Before operational switch-on of SGP 3.0 and public release of upgraded SCIAMACHY NO2 data, we have investigated the accuracy of the algorithm transfer: (a) by checking the consistency of SGP 3.0 with prototype algorithms; and (b) by comparing SGP 3.0 NO2 data with ground-based observations reported by the WMO/GAW NDACC network of UV-visible DOAS/SAOZ spectrometers. This delta-validation study concludes that SGP 3.0 is a significant improvement with respect to the previous processor IPF 5.04. For three particular SCIAMACHY states, the study reveals unexplained features in the slant columns and air mass factors, although the quantitative impact on SGP 3.0 vertical columns is not significant.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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This work presents one software developed to process solar radiation data. This software can be used in meteorological and climatic stations, and also as a support for solar radiation measurements in researches of solar energy availability allowing data quality control, statistical calculations and validation of models, as well as ease interchanging of data. (C) 1999 Elsevier B.V. Ltd. All rights reserved.

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Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field. (C) 2010 Elsevier B.V. All rights reserved.

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Grinding process is usually the last finishing process of a precision component in the manufacturing industries. This process is utilized for manufacturing parts of different materials, so it demands results such as low roughness, dimensional and shape error control, optimum tool-life, with minimum cost and time. Damages on the parts are very expensive since the previous processes and the grinding itself are useless when the part is damaged in this stage. This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 e VC131 steels. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. In each test AE data was analyzed off-line, with results compared to inspection of each workpiece for burn and other metallurgical anomaly. A number of statistical signal processing tools have been evaluated.

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This paper adresses the problem on processing biological data such as cardiac beats, audio and ultrasonic range, calculating wavelet coefficients in real time, with processor clock running at frequency of present ASIC's and FPGA. The Paralell Filter Architecture for DWT has been improved, calculating wavelet coefficients in real time with hardware reduced to 60%. The new architecture, which also processes IDWT, is implemented with the Radix-2 or the Booth-Wallace Constant multipliers. Including series memory register banks, one integrated circuit Signal Analyzer, ultrasonic range, is presented.

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The Paraguay River is the main tributary of the Paraná River and has an extension of 1.693 km in Brazilian territory. The navigability conditions are very important for the regional economy because most of the central-west Brazilian agricultural and mineral production is transported by the Paraguay waterway. Increased sedimentation along the channel requires continuous dredging to waterway maintenance. Systematic bathymetric surveys are periodically carried out in order to check depth condition along the channel using echo-sounding devices. In this paper, digital image processing and geostatistical analysis methods were used to analyze the applicability of the ASTER sensor to estimate channel depths in a segment of the upper Paraguay River. The results were compared with field data in order to choose the band with better adjustment and to evaluate the standard deviation. Comparing the VNIR bands, the best fit was presented by the red wavelength (band 2; 0,63 - 0,69 μm), showing a good representation of the channel depths shallow than 1,7 m. Applying geostatistical methods, the model accuracy was enhanced from 43 cm to 36 cm and undesired components were slacked. It was concluded that the digital number of band 2, converted to bathymetry information allows a good estimation of river depths and channel morphology.

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In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of São Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation. © 2011 by the Istituto Nazionale di Geofisica e Vulcanologia. All rights reserved.

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Studying the physical environment of a watershed is the basic condition for a successful planning of the riparian forest preservation, and for water production and conservation. The aims of the present study were to analyze and quantify the spatial and temporal evolution (1984 and 2010) using Landsat-5 satellite images of Cintra Stream sub-watershed, Botucatu, São Paulo State, Brazil, processed by the software IDRISI Andes, as well as to analyze the water quality through the parameters pH, EC, DO and BOD5 at 4 different sites in the years 1999, 2008 and 2009. Considering the 1076.48ha area of the sub-watershed, the pasture class of 1984 was reduced by 25.55% in 2010, resulting in an increase in the remaining classes. The most important class was native forest and reforestation since it had an increase of 5.08%, which indicates recovery of the riparian forest. Degraded areas were identified close to the inferior limit of the sub-watershed (P3 and P4), as well as local contamination (P1 and P2) with worsening of the water quality in the remaining sites in the periods 2008 and 2009. Recovery and management of the ecological succession of degraded areas and water quality monitoring at 1 and 2 sites will be necessary to reestablish the natural condition of the area studied.

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Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the search for consumers that cause great frauds. In this context, a electric power company may be interested in to go deeper a specific profile of illegal consumer. In this paper, we introduce the Optimum-Path Forest (OPF) clustering technique to this task, and we evaluate the behavior of a dataset provided by a brazilian electric power company with different values of an OPF parameter. © 2011 IEEE.

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The land question has been a widely discussed topic in Brazil, regarding land tenure. Law No. 10.267/01 was a major breakthrough for the agrarian issue. Since then on all rural properties must be georeferenced to the Brazilian Geodetic System (BGS). Therefore, satellite positioning and conventional methods are extensively used. Changes have been occurring in satellite positioning systems due to the addition of new signals in GPS (Global System Positioning), restructuring of GLONASS (Global Orbiting Navigation Satellite System), and the new systems like Galileo and Compass as well. To evaluate the effects of combining GPS and GLONASS data, several batches of processings were performed on different configurations. The data processing was performed to determine the coordinates of points of basic support and those materializing the neighborhood of the rural properties. As a result, it was found that the use of accurate ephemeris in transporting coordinates to support points has no significant influence, since transportation with broadcast ephemeris also meets the accuracy requirements for the Standard Technique for Georreferencing Rural Properties. On the other hand, when GPS and GLONASS data were used, such combination provides the best results. In the case of neighboring points, the use of GPS and GLONASS data is also recommended because such data meet the precision requirement and showed better results than those from where data were processed separately.

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The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China-Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced. © 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

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Pós-graduação em Ciências Cartográficas - FCT