Data Processing, Quality Control, and Validation
Data Processing, Quality Control, and Validation
The data processing workflow includes data cleaning, filtering, sound velocity correction, tide reduction, positioning adjustment, and gridding. Candidates must understand QC procedures: statistical analysis (mean, standard deviation), visual inspection (swath editor, 3D views), cross-line comparison, overlap analysis, and uncertainty estimation. Know the IHO S-44 standards for survey orders (Special, 1a, 1b, 2) and their accuracy and feature detection requirements. Be familiar with total propagated uncertainty (TPU) and error budgets. Also understand validation against independent data (e.g., previous surveys, Lidar, satellite).
Traps: Questions may test the difference between precision and accuracy in QC. Another trap is over-reliance on automated filters; always visually inspect data. Be careful with tide reduction errors; use appropriate tide stations and models. Also, sound velocity errors can create depth biases that are not obvious in statistical checks. Remember that S-44 specifies total vertical uncertainty (TVU) as a function of depth: TVU = sqrt(a^2 + (b*d)^2), where a and b depend on survey order.
Rule of thumb: Always compare cross-lines; discrepancies should be within the allowed uncertainty. Worked example: For S-44 Special Order, a=0.25 m, b=0.0075. At depth d=100 m, TVU = sqrt(0.25^2 + (0.0075*100)^2) = sqrt(0.0625 + 0.5625) = sqrt(0.625) ≈ 0.79 m. Ensure 95% of soundings meet this.
Key terms: QC, cross-lines, overlap, S-44, TPU, TVU, error budget, tide reduction, sound velocity correction, validation.