Marine Geoscience Data System
SOTW06WT Navigation
SOTW06WT Deep Tow vehicle navigation, South Tow leg 6 (1972)
This data set consists of Deep Tow vehicle navigation files for Galapagos Spreading Centre 1972 cruise SOTW06WT. These ASCII navigation files were generated by Neil Mitchell at the University of Manchester as follows. According to Klitgord & Mudie (1974), a network of six bottom transponders was originally deployed for the survey. Acoustic ranging between them, the Deep Tow vehicle and the ship enabled their relative positions to be calculated for most of the survey duration, with an internal accuracy of ~40 m. For the remaining one-third of the survey, it is unclear how the vehicle position was calculated although a cable trajectory model is mentioned in Klitgord and Mudie (1974) for a line over the northerly flank, which may have been used more widely. In addition, satellite fixes of the vessel allowed the survey to be placed in a geographic framework with an accuracy of ~0.5 km (after digitising accuracy is included, position accuracy will be somewhat poorer than this). A vehicle track map originally produced by Bob Detrick was digitised to generate (x, y, survey time) and these values were merged with digital data files obtained from the Marine Physical Laboratory at Scripps Institution of Oceanography to produce (x, y, Deep Tow vehicle depth, bathymetry at the Deep Tow position, survey time). The navigation files presented here contain these positional values updated with geographical coordinates that were obtained from longitude = X * 7.963700000000E-06 - 86.179455500; latitude = Y * 8.728372093023E-06 + 0.56179069767, where X and Y are the local coordinates in meters. That is, a flat-Earth approximation is used and is justified given the small geographical area and the age of the data (position uncertainty is larger than projection error). The X and Y values are also in the files.
Device Info
Navigation
Platform
Deep Tow (Sled)
SIO
Quality
0
Data have not been processed or modified since acquisition (e.g. Realtime navigation or sonar data, raw images etc.).

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