124 resultados para geodésicas


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The ionosphere is a major source of systematic error in the GPS observables. As this error is directly proportional to the TEC (Total Electron Content), the quality of GPS positioning (especially with single frequency receivers) can be significantly affected by regular changes of TEC. The ionosphere factor is even more relevant in the Brazilian region, where ionospheric phenomena, such as the Equatorial Anomaly, intensify these variations. Taking the above mentioned factors into account, experiments were conducted in this research to evaluate the daily and seasonal behavior of the TEC and the point positioning with GPS (single frequency) in periods of high and low solar activity in the Brazilian region. The results showed a direct correlation between the decrease in electrons density in the ionosphere (period of low solar activity) and improvement in positioning accuracy, as well as a large influence of Equatorial Anomaly on the results of point positioning.

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In this paper a methodology for automatic extraction of road segments from images with different resolutions (low, middle and high resolution) is presented. It is based on a generalized concept of lines in digital images, by which lines can be described by the centerlines of two parallel edges. In the specific case of low resolution images, where roads are manifested as entities of 1 or 2 pixels wide, the proposed methodology combines an automatic image enhancement operation with the following strategies: automatic selection of the hysteresis thresholds and the Gaussian scale factor; line length thresholding; and polygonization. In medium and high resolution images roads manifest as narrow and elongated ribbons and, consequently, the extraction goal becomes the road centerlines. In this case, it is not necessary to apply the previous enhancement step used to enhance roads in low resolution images. The results obtained in the experimental evaluation satisfied all criteria established for the efficient extraction of road segments from different resolution images, providing satisfactory results in a completely automatic way.

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Image acquisition systems based on multi-head arrangement of digital frame cameras, such as the commercial systems DMC, UltraCam, besides others, are attractive alternatives enabling larger imaging area when compared to a single frame camera. Considering that in these systems, cameras are tightly attached to an external mount, it is assumed that relative position and orientation between cameras are stable during image acquisition and, consequently, these constraint can be included in the calibration step. This constraint is acceptable because estimates of the relative orientation (RO) parameters between cameras, from previously estimated exterior orientation parameters, present higher and significant deviations than the expected physical variations, due to error propagation. In order to solve this problem, this work presents an approach based on simultaneous calibration of two or more cameras using constraints that state that the relative rotation matrix and the distance between the cameras head are stable. Experiments with images acquired by an arrangement of two Hasselblad H2D cameras were accomplished, without and with the mentioned constraints. The experiments showed that the calibration process with RO constraints allows better results than the approach based on single camera calibration, provided that the estimation has included only images with good target distribution.

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In Brazil, there have been several GPS applications and with the introduction of the Law 10.267/2001 that among other dispositions, deals with georeferencing of the rural parcels. However, most commercial softwares of processing and adjustment of GPS data don't let users to 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, a software for adjustment of GPS networks was developed, aiming at assisting the requirements of the Law 10.267/2001 in a reliable way. In this context, in this work it is analyzed the adjustments of GPS networks, by using absolute and relative constraints. In the latter, the adjustments were accomplished considering and not considering the correlations among the coordinate positions.

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In this paper, a methodology is proposed for the geometric refinement of laser scanning building roof contours using high-resolution aerial images and Markov Random Field (MRF) models. The proposed methodology takes for granted that the 3D description of each building roof reconstructed from the laser scanning data (i.e., a polyhedron) is topologically correct and that it is only necessary to improve its accuracy. Since roof ridges are accurately extracted from laser scanning data, our main objective is to use high-resolution aerial images to improve the accuracy of roof outlines. In order to meet this goal, the available roof contours are first projected onto the image-space. After that, the projected polygons and the straight lines extracted from the image are used to establish an MRF description, which is based on relations ( relative length, proximity, and orientation) between the two sets of straight lines. The energy function associated with the MRF is minimized by using a modified version of the brute force algorithm, resulting in the grouping of straight lines for each roof object. Finally, each grouping of straight lines is topologically reconstructed based on the topology of the corresponding laser scanning polygon projected onto the image-space. The preliminary results showed that the proposed methodology is promising, since most sides of the refined polygons are geometrically better than corresponding projected laser scanning straight lines.

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This article proposes a method for 3D road extraction from a stereopair of aerial images. The dynamic programming (DP) algorithm is used to carry out the optimization process in the object-space, instead of usually doing it in the image-space such as the DP traditional methodologies. This means that road centerlines are directly traced in the object-space, implying that a mathematical relationship is necessary to connect road points in object and image-space. This allows the integration of radiometric information from images into the associate mathematical road model. As the approach depends on an initial approximation of each road, it is necessary a few seed points to coarsely describe the road. Usually, the proposed method allows good results to be obtained, but large anomalies along the road can disturb its performance. Therefore, the method can be used for practical application, although it is expected some kind of local manual edition of the extracted road centerline.

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The Plant of Generic Values (PVG) is part of the cadastral system of a city hall and is about an important document or support for the urban planning. For its conception some stages are necessary, amongst which the most remarkable: the collection of information and the proper evaluation. A norm number 14653-2 of the ABNT recommends the application of the comparative method of data of market for the evaluation of lands values, but not always this procedure is possible due to absence of significant samples, as in urban areas densely constructed the real estate transactions is restricted, practically, to remarkable are the constructed ones. Thus, this work aims at showing which one, the sources of these data and the problematic found to get them. Moreover, a method is presented, that is an alternative to get the values of lands in the regions where yhere is scarcity of these data, so as to make the results beter. This method deals with the junction of other methods of evaluation to the comparative method of market data. The use of the methodology provided better performance in the procedures, having as a consequence bigger uniformity between the data, that is, the value of evaluation and the value of market equalize. Besides, the separation of the area of work in zones of homogeneous data made possible to generate more models, making use of fewes variables, due to the similarity among the data.

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Land cover mappings represent important tools for the regional planning. However, the current mappings are related to very specific purposes and, consequently, they are limited in their capacity to define the wide variety of existing types of land cover. In that context, this paper aims at developing a wide and including hierarchical classification system for land cover mapping in regional scale, which should contribute for a future standardization of classes. Besides, it is intended to test that system for a study case that contemplates the use of a classification method based on fuzzy approach, which has shown to be more appropriate than conventional approaches. Therefore, it was proposed a hierarchical classification system with three detailing levels and a study case was defined with the specification of the test area and of the classification project. Then, the georreferencing of a TM/Landsat-5 image that comprises the test area was carried out. Later, it was applied a fuzzy classification approach in the TM/Landsat-5 image, starting from images of probability for the mapped classes and an uncertainty image were generated. Finally, it was produced a conventional output that represents the thematic mapping of the test area.

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In this paper is a totally automatic strategy proposed to reduce the complexity of patterns ( vegetation, building, soils etc.) that interact with the object 'road' in color images, thus reducing the difficulty of the automatic extraction of this object. The proposed methodology consists of three sequential steps. In the first step the punctual operator is applied for artificiality index computation known as NandA ( Natural and Artificial). The result is an image whose the intensity attribute is the NandA response. The second step consists in automatically thresholding the image obtained in the previous step, resulting in a binary image. This image usually allows the separation between artificial and natural objects. The third step consists in applying a preexisting road seed extraction methodology to the previous generated binary image. Several experiments carried out with real images made the verification of the potential of the proposed methodology possible. The comparison of the obtained result to others obtained by a similar methodology for road seed extraction from gray level images, showed that the main benefit was the drastic reduction of the computational effort.

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In this work a method is proposed to allow the indirect orientation of images using photogrammetric control extracted through integration of data derived from Photogrammetry and Light Detection and Ranging (LiDAR) system. The photogrammetric control is obtained by using an inverse photogrammetric model, which allows the projection of image space straight lines onto the object space. This mathematical model is developed based on the intersection between the collinearity-based straight line and a DSM of region, derived from LiDAR data. The mathematical model used in the indirect orientation of the image is known as the model of equivalent t planes. This mathematical model is based on the equivalence between the vector normal to the projection plane in the image space and to the vector normal to the rotated projection plane in the object space. The goal of this work is to verify the quality, efficiency and potential of photogrammetric control straight lines obtained with proposed method applied to the indirect orientation of images. The quality of generated photogrammetric control was statistically available and the results showed that proposed method is promising and it has potential for the indirect orientation of images.

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This work presents a study on the generation of digital masks aiming at edge detection with previously known directions. This solution is important when edge direction is available either from a direction histogram or from a prediction based on camera and object models. A modification in the non-maximum suppression method of thinning is also presented enabling the comparison of local maxima for any edge directions. Results with a synthetic image and with crops of a CBERS satellite images are presented showing an example with its application in road detection, provided that directions are previously known.

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The so-called gravitomagnetic field arised as an old conjecture that currents of matter (no charges) would produce gravitational effects similar to those produced by electric currents in electromagnetism. Hans Thirring in 1918, using the weak field approximation to the Einsteins field equations, deduced that a slowly rotating massive shell drags the inertial frames in the direction of its rotation. In the same year, Joseph Lense applied to astronomy the calculations of Thirring. Later, that effect came to be known as the Lense- Thirring effect. Along with the de Sitter effect, those phenomena were recently tested by a gyroscope in orbit around the Earth, as proposed by George E. Pugh in 1959 and Leonard I. Schiff in 1960. In this dissertation, we study the gravitational effects associated with the rotation of massive bodies in the light of the Einsteins General Theory of Relativity. With that finality, we develop the weak field approximation to General Relativity and obtain the various associated gravitational effects: gravitomagnetic time-delay, de Sitter effect (geodesic precession) and the Lense-Thirring effect (drag of inertial frames). We discus the measures of the Lense-Thirring effect done by LAGEOS Satellite (Laser Geodynamics Satellite) and the Gravity Probe B - GPB - mission. The GPB satellite was launched into orbit around the Earth at an altitude of 642 km by NASA in 2004. Results presented in May 2011 clearly show the existence of the Lense-Thirring effect- a drag of inertial frames of 37:2 7:2 mas/year (mas = milliarcsec)- and de Sitter effect - a geodesic precession of 6; 601:8 18:3 mas/year- measured with an accuracy of 19 % and of 0.28 % respectively (1 mas = 4:84810��9 radian). These results are in a good agreement with the General Relativity predictions of 41 mas/year for the Lense-Thirring effect and 6,606.1 mas/year for the de Sitter effect.