El 3D del Campus II de la Universidad Feevale

El trabajo fue desarrollado por el Laboratorio de Geoprocesamiento y Topografía la Universidad Feevale en la ciudad de Novo Hamburgo - RS, Brasil. La propuesta tiene como objetivo producir el Campus II de la Universidad Feevale en 3D (tres dimensiones), con la finalidad de facilitar la visualización de la infraestructura y ayudar en la necesidad de otros sectores de la institución, como prestar asistencia en la planificación y creación de nuevos proyectos de edificios, así como la disponibilidad de las informaciones en forma de videos, a través de la web en el link “Localize-se na Feevale”, para la navegación virtual en los edificios del Campus II. El proyecto se desarrolló a partir de los planos de los edificios existentes con los datos del levantamiento topográfico planialtimetric del Campus II, desarrollado por el laboratorio. Con los planos de los edificios se ha elaborado un modelo en 3D de cada uno de los edificios por separado, con el uso del software SketchUp, haciendo la unificación posterior de los datos en el modelo digital del terreno, creado a partir de datos levantados con topografía. El proyecto tiene como consecuencia de los resultados una mejor ubicación y visualización del Campus II para los nuevos académicos y también para la comunidad externa, así como la implementación del proyecto existente en la web (Localize-se na Feevale). Las informaciones generadas tiene permitido al sector del “Projetos e Obras” a criar nuevas propuestas del proyectos del edificaciones, así como hacer planificaciones del Campus II y también para locomoción de las personas. Con los datos generados fue posible hacer una planificación para el nuevo centro de eventos que se quedará terminado para el próximo año.The work was developed by the Laboratory of Geoprocessing and Surveying Feevale University in the city of Novo Hamburgo - RS, Brazil. The proposal aims to produce the University Campus II Feevale 3D (three dimensional), in order to facilitate the visualization of the infrastructure and assist in the need for other sectors of the institution, as assistance in planning and create new building projects and the availability of the information in the form of videos, in the web at the link "Localize-se na Feevale" to virtual navigation in buildings Campus II. The project was developed from drawings of the existing buildings with survey data planialtimetric Campus II, developed bu the laboratory. With the plans of the buildings has developed a 3D model of each building separately, using SketchUp software, making the subsequent unification of the data in the digital terrain model, created from data gathered with topography. The project is a consequence of the result a better location and visualization of the Campus II display for the new academic and also to the external community as well as the implementation of the existing plan on the web (Localize-se na Feevale). The information generated has enabled the sector's "Projetos e Obras" to raise new buildings project proposals and planning to Campus II and also for locomotion to the people. The data generated was possible to make a plan for the new events center to be completed in next year.Peer Reviewe

Georreferenciamento de imóveis rurais : análise de área entre topografia, RTK e sistema TM

O georreferenciamento de todos os imóveis rurais do Brasil é um dos principais objetivos do Instituto Nacional de Colonização e Reforma Agrária (INCRA), visando à organização e fiel localização destas propriedades no Sistema Geodésico Brasileiro. Executou-se no presente trabalho a metodologia presente na 3ª edição da Norma Técnica para Georreferenciamento de Imóveis Rurais do INCRA e seus manuais agregados, a fim de se realizar a validação de uma pequena propriedade rural situada no município de Capela de Santana – RS, através da ferramenta SIGEF. Devido aos diversos métodos de posicionamento presentes no Manual Técnico de Posicionamento do INCRA, foram escolhidos os dois mais usuais e então executada a comparação das coordenadas obtidas nos métodos RTK Convencional e Topografia Clássica, em que a diferença média nos três eixos (E, N e h) foi de 3,30 cm. Subsequente, analisou-se o comportamento da variação da área do imóvel nos diferentes sistemas SGL, STL, UTM, RTM e LTM, conforme o valor do coeficiente de distorção linear (K). A área no sistema RTM apresentou o valor mais próximo da área no STL (K=1), enquanto que a maior diferença foi apresentado no sistema UTM

Regional mapping of the Geoid Using GNSS (GPS) measurements and an artiticial neural network

The determination of the orthometric height from geometric leveling has practical difficulties that, despite a number of scientific and technological advances, passed a century without substantial modifications or advances. Currently, the Global Navigation Satellite System (GNSS) has been used with reasonable success for orthometric height determination. With a sufficient number of benchmarks with known horizontal and vertical coordinates, it is often possible to adjust using the least squares method mathematical expressions that allow interpolation of geoid heights. The objective of this study is to present an alternative method to interpolate geoid heights based on the technique of Artificial Neural Networks (ANNs). The study area is the Brazilian state of São Paulo, and for training the ANN the authors have used geoid height information from the EGM08 gravity model with a grid spacing of 10 minutes of arc. The efficiency of the model was tested at 157 points with known geoid heights distributed across the study area. The results were also compared with the Brazilian Geoid Model (MAPGEO2004). Based on those 157 benchmarks it was possible to verify that the model generated by ANNs provided a mean absolute error of 0.24 m in obtaining a geoid height value. Statistical tests have shown that there was no difference between the means from known geoid heights and geoid heights provided by the neural model for a significance level of 5%. It was also found that ANNs provided an improvement of 2.7 times in geoid height estimates when compared with the MAPGEO2004 geoid model