Aerodromes protection zones are defined by plans that are determined by three-dimensional (3D) limiting surfaces, which establish the airspace that must remain clear of obstacles, imposing some restrictions on land use. The objective of this paper is to generate 3D models of the surrounding area of Salgado Filho International Airport, considering the constructive altimetric limit established in the Aerodrome Protection Zone Basic Plan (PBZPA), to identify and quantify obstacles related to plots (urban land parcels) and buildings. The adopted methodology includes the analysis and selection of geospatial data, data modeling and performing spatial analysis on the generated 3D models. The results showed that out of a total of 106,838 plots, covering an area of 69.68 km², 4,826 plots (4.52%) exceeded the limiting surface and 1,054 plots (0.99%) represent critical areas where constructions may not be allowed. And, out of a total of 200,573 buildings, 26,418 of them (13.17%) exceeded the limit imposed by PBZPA's. Also, the methodology is valid for detecting and quantifying critical areas concerning the constructive viability of the plots, affected areas regarding the height of the plots and buildings, and for identifying obstacles to aerodromes according to their respective airspace laws.
Aerodromes protection zones are defined by plans that establish the limits that objects can project into airspace without affecting the safety and regularity of air operations. These plans are composed of a set of imaginary threedimensional surfaces that impose restrictions on the use of properties within the protection zones. Our research problem is how to classify the risk of obstacles in aerodromes protection zones. In this paper, we propose a methodology to obtain an obstacle risk classification model. We defined the risk factors and applied a questionnaire to an expert in civil aviation. The obstacle risk classification model resulted from the specialist analysis and by applying the analytic hierarchy process (AHP) for multi-criteria decision analysis. The advantage of the AHP in studies that use specialists' empiric knowledge for risk modeling is the treatment of uncertainties, and the use of tangibles and intangibles criteria. The results showed that the most significant influence on the risk of an obstacle is how much that obstacle protrudes the limiting surfaces, followed by the distance between the obstacle and the nearest airport runway threshold, the limiting surface in which the obstacle is, and the nature of the obstacle.
envolve erros derivados dos instrumentos, do operador, dos processos de medida, etc. Os erros presentes nos dados gravimétricos se propagam na determinação do modelo do geóide, por isso a sua identificação é de fundamental importância. Os objetivos desse trabalho consistiram na integração das informações gravimétricas coletadas por três Instituições e na detecção e remoção dos possíveis erros grosseiros desse banco de dados. Das observações que constituem o banco de dados gravimétricos do Estado do Rio Grande do Sul, 2.480 vieram do IAG/USP, 950 do IBGE e 6.071 observações do IG/UFRGS. O Estudo foi dividido em três etapas: verificação de dados duplicados (primeira etapa), onde foram identificadas 225 observações; análise da distribuição geográfica dos pontos (segunda etapa), onde foram encontradas 37 observações (0,60% do banco de dados) com erro no posicionamento planimétrico; análise estatística (terceira etapa) baseada no desvio padrão dos dados. Os testes altimétricos e gravimétricos identificaram 284, 256 e 172 pontos suspeitos de conterem erros grosseiros, respectivamente, para as análises Global (4,58% do banco de dados), Regional (4,13% do banco de dados) e Local (2,77% do banco de dados). Nos três tipos de análises realizadas, ou seja, Global, Regional e Local sete pontos foram identificados por dois testes. Palavras-chave: erro grosseiro, análise estatística, gravidade, altimetria.ABSTRACT -The act of measurement is, essentially, an act of comparing that involves errors derivatives of instruments, operator, processes of measurement, etc. The errors presents in the gravimetric data propagate on determination of the geoid model, so their identification is crucial. The objectives of this work consisted in integration of the gravimetric information collected by three Institutions and also in the detection and removal of possible blunders presents in this database. From observations that constitute the gravity database of Rio Grande do Sul, 2,480 came from IAG/USP, 950 from IBGE and 6,071 observations from IG/UFRGS. The Study was divided into three steps: check duplicate data (first step), which identified 225 observations; geographical distribution analysis of points (second step), where it was found 37 observations (0.60% of database) with planimetric positioning error; statistical analysis (third step) based on the standard deviation of the data. The altimetric and gravimetric tests have identified 284, 256 e 172 points suspects of present blunders, respectively, for the analysis (4.58% of database), Regional (4.13% of database) and Local (2.77% of database). In the three types of analyzes, in other words, Global, Regional and Local seven points were identified by two tests. Keywords: blunder, statistical analysis, gravity, altimetry. INTRODUÇÃOOs dados de gravidade são importantes nos estudos que visam o conhecimento da forma, da estrutura, das propriedades físicas e dos processos dinâmicos da Terra. Assim, a medida da gravidade, obtida na superfície da Terra, contém informações sobre o ponto onde a med...
A correção de terreno é uma das reduções gravimétricas aplicadas ao valor da aceleração da gravidade. O objetivo desse trabalho consistiu na comparação do desempenho dos programas TC2DFTPL e TCFOUR para verificar se há diferenças significativas entre eles no cálculo da correção de terreno para o Estado do Rio Grande do Sul. Os resultados obtidos para os programas TC2DFTPL e TCFOUR foram iguais. No entanto, o programa TCFOUR apresentou efeito de borda, ao contrário do programa TC2DFTPL. Notou-se uma incompatibilidade entre as escalas de variação da correção de terreno dos modelos derivados do SRTM e do ASTER com resoluções de 2 km e 1 km calculados pelos dois programas. Concluiu-se que essa incompatibilidade se deva à necessidade de compartimentar a área de estudo para as maiores resoluções e também às diferenças altimétricas entre os dois modelos digitais do terreno, mais evidentes nas regiões de maiores altitudes, como é o caso da Serra do RS.
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