Avaliação do potencial das imagens quickbird ortorretificadas para o mapeamento das propriedades localizadas na área de expansão e vazios urbanos

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

A semi-automatic method for indirect orientation of aerial images using ground control lines extracted from airborne laser scanner data

This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.

Proposta para a estimativa da acurácia de redes geodésicas horizontais integrando análise de robustez e de covariância

The goal of this paper is to present a methodology for quality control of horizontal geodetic networks through robustness and covariance analysis. In the proposed methodology, the positional accuracy of each point is estimated by a possible bias in their position (based on robustness analysis), in addition to its own positional precision (uncertainty) (through covariance analysis), being a measure independently from the choice of the datum. Besides presenting the theoretical development of the method, its application is demonstrated in a numerical example. The results indicate that, in general, the greater the distance of an unknown point to the control(s) point(s) of the network, the greater is the propagation of random errors on this unknown point, and the smaller the number of redundant observations around a unknown point, the greater the influence of possible (undetected) non-random errors on this point.