Resumo em Inglês:

Abstract: Due to waterway transport efficiency, mainly for commercial trades, the use of sea/river routes has grown recently. So, the importance of producing high quality nautical charts stands out. A nautical chart is the hydrographic survey final product and its accuracy depends on data quality collected, primarily of the vertical quality (depth). In this sense, despite the theoretical and practical difficulty in obtaining homologous points in hydrographic surveys, even when performing check lines, bathymetric data must always be delivered with a statistically proven confidence level. Thus, this study has two main objectives: i) to propose a method, called Point to Point (P2P), for obtaining “homologous points” for hydrographic surveys carried out with multibeam systems, without resorting to mathematical and/or statistical interpolations, called Point to Point (P2P); ii) to quantify the magnitude of the difference between the statistical evaluation using check lines (CL) and by overlapping successive sounding lines (SL), applying the P2P method. The results showed that P2P is easy to application, provide low computation effort, is robust and consistent. Besides that, was possible to applied successive regular lines to get a validation of the hydrographic survey.

Resumo em Inglês:

Abstract: This study investigates the potential use of close-range and low-cost terrestrial RGB imaging sensor for fruit detection in a high-density apple orchard of Fuji Suprema apple fruits (Malus domestica Borkh). The study area is a typical orchard located in a small holder farm in Santa Catarina’s Southern plateau (Brazil). Small holder farms in that state are responsible for more than 50% of Brazil’s apple fruit production. Traditional digital image processing approaches such as RGB color space conversion (e.g., rgb, HSV, CIE L*a*b*, OHTA[I 1 , I 2 , I 3 ]) were applied over several terrestrial RGB images to highlight information presented in the original dataset. Band combinations (e.g., rgb-r, HSV-h, Lab-a, I” 2 , I” 3 ) were also generated as additional parameters (C1, C2 and C3) for the fruit detection. After, optimal image binarization and segmentation, parameters were chosen to detect the fruits efficiently and the results were compared to both visual and in-situ fruit counting. Results show that some bands and combinations allowed hits above 75%, of which the following variables stood out as good predictors: rgb-r, Lab-a, I” 2 , I” 3 , and the combinations C2 and C3. The best band combination resulted from the use of Lab-a band and have identical results of commission, omission, and accuracy, being 5%, 25% and 75%, respectively. Fruit detection rate for Lab-a showed a 0.73 coefficient of determination (R2), and fruit recognition accuracy rate showed 0.96 R2. The proposed approach provides results with great applicability for small holder farms and may support local harvest prediction.

Resumo em Inglês:

Abstract: Object detection in high resolution images is a new challenge that the remote sensing community is facing thanks to introduction of unmanned aerial vehicles and monitoring cameras. One of the interests is to detect and trace persons in the images. Different from general objects, pedestrians can have different poses and are undergoing constant morphological changes while moving, this task needs an intelligent solution. Fine-tuning has woken up great interest among researchers due to its relevance for retraining convolutional networks for many and interesting applications. For object classification, detection, and segmentation fine-tuned models have shown state-of-the-art performance. In the present work, we evaluate the performance of fine-tuned models with a variation of training data by comparing Faster Region-based Convolutional Neural Network (Faster R-CNN) Inception v2, Single Shot MultiBox Detector (SSD) Inception v2, and SSD Mobilenet v2. To achieve the goal, the effect of varying training data on performance metrics such as accuracy, precision, F1-score, and recall are taken into account. After testing the detectors, it was identified that the precision and recall are more sensitive on the variation of the amount of training data. Under five variation of the amount of training data, we observe that the proportion of 60%-80% consistently achieve highly comparable performance, whereas in all variation of training data Faster R-CNN Inception v2 outperforms SSD Inception v2 and SSD Mobilenet v2 in evaluated metrics, but the SSD converges relatively quickly during the training phase. Overall, partitioning 80% of total data for fine-tuning trained models produces efficient detectors even with only 700 data samples.

Resumo em Inglês:

Abstract The words "environment" and "space" demonstrate distinct spatial units. It must be questioned whether the internal space, seen as an analytical subcategory of space, adds specificities of this type of designation. Therefore, if indoor is a subcategory of space, then its characteristics and types of representation must be observed and analyzed considering aspects of space. The purpose of this article is to present the characteristics of the indoor space unit as a subcategory of space. The “space” terminology applied to specify the indoor spatial unit has some features of spatial analysis that allow a broader and deeper spectrum as an object of study. Compared to space, the "environment" proves to be limited to represent the characteristics of the indoor. The intern must be understood as a space within a space, inserting a subcategory of the urban space, however, it is never seen as in its entirety. The totality does not observe space as it is, but everything within it. Space, as a creation of man, allows the creation of subspaces with no connection to the outside, in the category called indoor contributing to the analysis procedures based on the understanding of their relationships.

Resumo em Português:

Resumo: O método da interseção à vante já é bastante empregado no levantamento geodésico de coordenadas de pontos inacessíveis, principalmente, quando se dispõe apenas de medições de ângulos, neste caso, também denominado método da triangulação. Entretanto, a solução matemática da interseção à vante 3D com a definição analítica de retas espaciais, resolvida pelo Método das Distâncias Mínimas, ainda é pouco difundido no ambiente acadêmico e profissional. Esta modelagem matemática determina as coordenadas 3D de um ponto localizado no meio da distância mínima entre duas ou mais retas espaciais, que se “interceptam” espacialmente em direção ao ponto de observação. Esta solução é mais acurada que outras apresentadas na literatura por resolver simultaneamente o problema da determinação 3D de um ponto pelo Método dos Mínimos Quadrados (MMQ), além de fornecer as precisões das coordenadas, as quais são inerentes ao processo de ajustamento. Este trabalho, portanto, tem o objetivo de explanar o Método das Distâncias Mínimas para a interseção espacial de visadas medidas com estação total a partir de dois ou mais pontos de observação conhecidos para a determinação 3D de pontos inacessíveis situados em quinas de edificações. Para a análise do método foi desenvolvida uma ferramenta em Python para o QGIS que calcula as coordenadas 3D e gera o relatório de processamento do ajustamento, sendo aplicada com observações reais do levantamento geodésico do prédio da SUDENE, em Recife-PE. A metodologia desenvolvida neste trabalho se mostrou adequada para medições de grandes estruturas, alcançando precisões esféricas melhores que ±1,0 cm e atendendo as normas nacionais para cadastro urbano.

Resumo em Inglês:

Abstract: The forward intersection method is already widely used in the geodetic survey of coordinates of inaccessible points, especially when only angle measurements are available, in this case, also called the triangulation method. However, the mathematical solution of the 3D forward intersection with the analytical definition of spatial lines, resolved by the Minimum Distances Method, is still not widespread in the academic and professional environment. This mathematical modeling determines the 3D coordinates of a point located in the middle of the minimum distance between two or more spatial lines, which spatially "intersect" towards the observation point. This solution is more accurate than others presented in the literature because it simultaneously solves the problem of 3D determination of a point by the method of least squares, in addition to providing an estimate of the coordinate precision, which are inherent to the adjustment. This work, therefore, has the objective of explaining the Minimum Distances Method for the spatial intersection of targeted measurements with a Total Station from two or more known observation points for the 3D determination of inaccessible points located in corners of buildings. For the analysis of the method, a Python tool was developed for QGIS that calculates the 3D coordinates and generates the adjustment processing report, being applied with real observations of the Geodetic survey of the SUDENE building, in Recife-PE. The methodology developed in this work proved to be suitable for measurements of large structures, achieving spherical precision better than ±1.0 cm, following the Brazilian standards for urban cadastre.

Resumo em Português:

Resumo A combinação entre as altitudes físicas e geométricas, necessárias para fins geodésicos, utiliza Modelos Global do Geopotencial (MGGs), ou modelos geoidal e quase geoidal locais. A ondulação geoidal e a anomalia de altura, fornecidas pelos MGGs, não são acuradas o suficiente para a maioria das aplicações de engenharia. Considerando o atual sistema de altitude normal do Brasil e os conceitos físicos das superfícies de referência envolvidas, um modelo quase-geoidal é mais apropriado que o atual modelo geoidal brasileiro, MAPGEO2015. Este trabalho mostra a determinação dos modelos geoidal e quase-geoidal para o estado de São Paulo utilizando os dados gravimétricos atualizados e o novo sistema de altitude normal da realização de 2018 da Rede Vertical de Referência do Brasil (RVRB). O cálculo do modelo quase-geoidal foi realizado por integração numérica através da Transformada Rápida de Fourier (FFT). A anomalia de gravidade de Molodensky foi determinada em uma grade 5' e reduzida e restaurada usando a técnica Residual Terrain Model (RTM) e o MGG XGM2019e com ordem e grau 250 e 720. O modelo geoidal foi derivado das anomalias de Bouguer. A validação do modelo quase-geoidal apresentou Root Mean Square (RMS) da diferença de 18 cm comparado às medidas Global Positioning System (GPS) na rede de nivelamento.

Resumo em Inglês:

Abstract The combination of physical and geometric heights, required for geodetic purposes, uses Global Geopotential Models (GGMs), local geoid, or quasigeoid models. The geoid height and the height anomaly, provided by GGMs, are not accurate enough for most engineering applications. Considering the normal height system of Brazil and the physical concepts of the involved reference surfaces, a quasigeoid model is more appropriate than the current Brazilian geoid model MAPGEO2015. This paper shows the determination of the geoid and the quasigeoid models for São Paulo state using the updated gravimetric data and the new system of the normal height of the 2018 Brazilian Vertical Reference Frame (BVRF). The computation of the quasigeoid model was performed by numerical integration through the Fast Fourier Transform (FFT). The Molodensky gravity anomaly was determined in a 5’ grid and reduced and restored using the Residual Terrain Model (RTM) technique and the XGM2019e GGM truncated at degree and order 250 and 720. The geoid model was derived from the Bouguer gravity anomalies. The quasigeoid model validation has shown a Root Mean Square (RMS) difference of 18 cm compared with the Global Positioning System (GPS) measurements in the levelling network.

Resumo em Inglês:

Abstract Travel demand models have been developed and refined over the years to consider a characteristic normally found in travel data: spatial autocorrelation. Another important feature of travel demand data is its multivariate nature. However, regarding the public transportation demand, there is a lack of multivariate spatial models that consider the scarce nature of travel data, which generally are expensive to collect, and also need an appropriate level of detail. Thus, the main aim of this study was to estimate the Boarding variable along a bus line from the city of São Paulo - Brazil, by means of a multivariate geostatistical modeling at the bus stop level. As specific objectives, a comparative analysis conducted by applying Universal Kriging, Ordinary Kriging and Ordinary Least Squares Regression for the same travel demand variable was proposed. From goodness-of-fit measures, the results indicated that Geostatistics is a competitive tool comparing to classical modeling, emphasizing the multivariate interpolator Universal Kriging. Therefore, three main contributions can be highlighted: (1) the methodological advance of using a multivariate geostatistical approach, at the bus stop level, on public transportation demand modeling; (2) the benefits provided by the models regarding the land use and bus network planning; and (3) resource savings of field surveys for collecting travel data.

Resumo em Inglês:

Abstract: Technological improvement in sensors and the use of computer vision algorithms made possible the generation of high accuracy mapping products (cm level) using data acquired by low-cost Unmanned Aerial Vehicles (UAV). However, the procedure to optimally set the aerial block configuration is not well understood for some users mainly due to the popularization of the UAV and its use by non-specialists. This study aims to contribute to this aspect, investigating and highlighting the influence of flight parameters, camera calibration and number of Ground Control Points (GCP) on generating digital terrain models and orthomosaic. To address this issue, several field experiments and data processing were carried out. The quality was assessed by calculating the Root Mean Square Error (RMSE) together with a bias evaluation (t-Student test at 90% confidence level). The results suggest that an optimum block configuration for accurate and unbiased products is achieved by surveying at rates of 80%/60% (forward and sidelap, respectively), with an average Ground Sample Distance (GSD) of around 1 cm at a flight height of 31 m, using a pre-calibrated camera and 5 GCP at least.