Performance Evaluation of Direction Cosine Matrix and Madgwick’s as 3D Orientation Estimation Algorithm for Estimating Ground Contour

Contour interval is elevation difference between two contour lines that are adjacent and parallel. Ground Contour interval is an important information that must be provided in a construction. Ground contour interval estimation problem could be viewed as a 3D trajectory estimation problem. One framework, called dead reckoning, is often used for motion (position and orientation) tracking of a mobile systems over time. Dead reckoning requires a precise 3D orientation estimation algorithm. Two competing algorithms are Direction Cosine Matrix and Madgwick’s. To ensure the 3D trajectory estimation gives an accurate result, these two algorithms must be carefully and thoroughly evaluated. This research is part of a complete research on the development of a ground contour estimation and only focuses on comparison between two 3D orientation estimation algorithm.

Fish Habitat: Essential Fish Habitat and Rehabilitation

<em>Abstract.</em> —The American lobster <em>Homarus americanus </em> is usually associated with rocky substrate that provides or can be modified into shelter and that may be an essential habitat to early benthic-phase juveniles. The dependence on shelter-providing habitat not only makes possible the definition of essential habitat for lobsters but also permits the assessment of abundance based on the areal extent of habitat. Here, we describe such a habitat-based assessment, performed in response to an oil spill on the coast of Rhode Island, USA. Results from a side-scan sonar survey performed after the spill indicated that the amount of lobster habitat affected by the oil was approximately 9.8 km2 along nearly 15 km of coastline. Postspill lobster density ranged from 0.24 lobsters m22 in the impact region to 1.63 lobsters m22 in the control region. Qualitative (map contours of lobster density) and quantitative (statistical tests) approaches suggested a significant effect of the spill had been detected by our sampling. An estimate of the total number of lobsters killed was required to scale restoration efforts. We calculated the total number of lobsters in the area by overlaying contours of lobster density on a habitat map generated by side-scan sonar, then multiplying the density of lobsters in each contour interval by the area of appropriate lobster habitat (cobble and boulder) in the contour interval. To calculate loss, we subtracted postspill abundance from prespill abundance. Prespill density was estimated to be 1.76 m22, which is an adjusted average of airlift samples taken at six Rhode Island sites four months prior to the spill. Calculations of loss based on habitat-specific density estimates were adjusted to reflect undersampling. The loss was estimated to be to be 9.0 × 106 lobsters. Variability associated with this loss estimate is large; 95% confidence intervals estimated that between 6.7 × 106 and 15.6 × 106 lobsters were lost. The calculated loss was very sensitive to changes in prespill density estimates; a change of 0.1 lobsters m22 resulted in a change of 0.75–0.9 × 106 lobsters lost. Habitatbased assessment of lobster population size is possible but requires detailed habitat maps and accurate density estimates. Natural variability and sampling limitations give such assessment a wide range of possible values. Nevertheless, the airlift sampling technique, together with sidescan sonar maps of habitat, could provide a powerful tool for estimating the abundance of inshore lobsters.