93 resultados para geodésicas


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Nowadays, with the implantation of GNSS (Global Navigation Satellite System) reference station networks, several positioning techniques have been developed and/or improved. Using such kind of network data it is possible to model the GNSS distance dependent errors and to compute correction terms for the network region. Several methods have been developed to formulate the corrections terms from network stations data. A method that has been received a great attention is the Virtual Reference Station (VRS). The idea is that the VRS data resemble as much as possible a real receiver data placed in the same local. Therefore, the user has the possibility of using the VRS as if it were a real reference station in your proximities, and to accomplish the relative positioning with a single frequency receiver. In this paper it is described a different methodology applied to implement the VRS concept, using atmospheric models developed by Brazilian researchers. Besides, experiments for evaluating the quality of generated VRS are presented, showing the efficiency of the proposed method.

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The Brazilian Geodetic Network started to be established in the early 40's, employing classical surveying methods, such as triangulation and trilateration. With the introduction of satellite positioning systems, such as TRANSIT and GPS, that network was densified. That data was adjusted by employing a variety of methods, yielding distortions in the network that need to be understood. In this work, we analyze and interpret study cases in an attempt to understand the distortions in the Brazilian network. For each case, we performed the network adjustment employing the GHOST software suite. The results show that the distortion is least sensitive to the removal of invar baselines in the classical network. The network would be more affected by the inexistence of Laplace stations and Doppler control points, with differences up to 4.5 m.

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In the Brazil, several have been the applications of GPS and with the introduction of the Law 10.267/2001 that among other dispositions, it treats of the georeferencing of the rural parcels. However, most of the commercial softwares of processing and adjustment of GPS data doesn't allow that the users may evaluate their results in a reliable way. For example, the constraints are normally used as absolute, which provides results with very optimists precisions. The adoption of additional analyses and the implementation of softwares can reduce these kinds of problems. Thus, it was developed a software for adjustment of GPS networks, aiming to assist in a reliable way the requirements of the Law 10.267/2001. In this context, in this work it is analyzed the adjustments of GPS networks, utilizing absolute and relative constraints. In the case of the last one, the adjustments were accomplished considering and not considering the correlations among the coordinate positions.

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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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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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Observable GNSS (Global Navigation Satellite System) are affected by systematic errors due to free electrons present in the ionosphere. The error associated with the ionosphere depends on the Total Electron Content (TEC), which is influenced by several variables: solar cycle, season, local time, geomagnetic activity and geographic location. The GPS (Global Positioning System), GLONASS (Global Orbiting Navigation Satellite System) and Galileo dual frequency receivers allow the calculation of the error that affects the GNSS observables and the TEC. Using the rate of change of TEC (ROT - Rate of TEC) indices that indicate irregularities of the ionosphere can be determined, allowing inferences about its behavior. Currently it is possible to perform such studies in Brazil, due to the several Active Networks available, such as RBMC/RIBaC (Rede Brasileira de Monitoramento Contínuo/Rede INCRA de Bases Comunitárias) and GNSS Active Network of São Paulo. The proposed research aimed at estimating and analysing of indexes of irregularities of the ionosphere, besides supplying the geosciences of information about the behavior of the ionosphere.

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

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In the past few years several GPS (Global Position System) positioning techniques have been develope and/or improved with the goal of obtaining high accuracy and productivity in real time. The reference station network concept besides to enabling quality and reliability in positioning for scientific and civil GPS community, allows studies concerning tropospheric refraction modeling in the network region. Moreover, among the network corrections transmission methods available to users, there is the VRS (Virtual Reference Station) concept. In this method, the data of a virtual station are generated near the rover receiver (user). This provides a short baseline and the user has the possibility of using a single frequency receiver to accomplish the relative positioning. In this paper, the methodology applied to generate VRS data, using different tropospheric models is described. Thus, comparative tests were conducted in the four seasons with the NWP/INPE (Numerical Weather Prediction/National Institute for Space Research) and Hopfield tropospheric models. In order to analyse the VRS data quality, it was used the Precise Point Positioning (PPP) method, where satisfactory results were found. Mean differences between PNT/INPE and Hopfield models of 9.75% and 24.2% for the hydrostatic and wet days, respectively were obtained.

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The implementation of local geodetic networks for georeferencing of rural properties has become a requirement after publication of the Georeferencing Technical Standard by INCRA. According to this standard, the maximum distance of baselines to GNSS L1 receivers is of 20 km. Besides the length of the baseline, the geometry and the number of geodetic control stations are other factors to be considered in the implementation of geodetic networks. Thus, this research aimed to examine the influence of baseline lengths higher than the regulated limit of 20 km, the geometry and the number of control stations on quality of local geodetic networks for georeferencing, and also to demonstrate the importance of using specific tests to evaluate the solution of ambiguities and on the quality of the adjustment. The results indicated that the increasing number of control stations has improved the quality of the network, the geometry has not influenced on the quality and the baseline length has influenced on the quality; however, lengths higher than 20 km has not interrupted the implementation, with GPS L1 receiver, of the local geodetic network for the purpose of georeferencing. Also, the use of different statistical tests, both for the evaluation of the resolution of ambiguities and for the adjustment, have enabled greater clearness in analyzing the results, which allow that unsuitable observations may be eliminated.

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When registering spectral radiance from surface targets, digital numbers recorded by the imagery sensor may vary. Such variation causes imperfections on the images coming from aerial surveys. Variation in the image brightness related to the distance from the center of the image is known as the vignetting effect. Correcting this effect aims at achieving an homogeneous image brightness. The purpose of this paper is to present a specific methodology to determine a model in order to minimize this vignette effect based on a model fit by Least Squares Method (LSM), using digital numbers (DN) from shadowed regions. The main hypothesis is that the recorded DN of shadow pixels should be suitable to model the vignetting effect. Considering that the vignetting effect could be modeled as a trend of spatial image variation, a trend surface analysis of a sample of pixels from shadowed regions was carried out. Two approaches were adopted to represent the shadow regions of an image. The first one takes into account the components R, G, B of the aerial image within the visible spectral band, and the second one considers the component I of the HSI image. In order to evaluate the methodology, a study case with a color aerial image was carried out. The findings showed that the best results were obtained by applying the model in the RGB components, which allows to conclude that the vignetting effect can be modeled based on trend surfaces fit on shadow regions DN.

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Data from reference stations are widely used in GNSS (Global Navigation Satellite System) positioning, and can be used in relative positioning or network-based positioning concept. Positioning accuracy will be directly influenced by errors in signals collected in these stations. In this paper, it is aimed at evaluating these data quality using temporal series of multipath index MP1 and MP2. A statistical study of temporal series with 7 years of daily observations related to 7 stations from RBMC (Rede Brasileira de Monitoramento Contínuo) was accomplished. In order to investigate trends and seasonality a linear regression model, correlograms, and Fourier periodograms were used. We also used a harmonic adjust to identify peaks on temporal series. At last, the possible causes of seasonality found in some stations were discussed. It was also possible to identify peaks in MP values of March and October months (mainly in stations located near geomagnetic equator).