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The objective of an oceanographic survey is to obtain the best understanding of the phenomena under study for a given amount of expended effort. This problem is complicated by the fact that the ocean usually evolves on a time scale comparable to (or faster than) the survey time. The ideal survey would be accomplished instantaneously and with infinite resolution. However, as platform limitations preclude such synoptic surveys, compromises between resolution, total survey time, and vehicle speed must be made. This paper presents a framework for optimizing uniform surveys of temporally evolving scalar fields under platform introduced constraints. Knowledge of the statistical characteristics of the ocean and the dominant physical processes are assumed. Advection is assumed to be negligible as a driving factor in temporal variations. The survey error, given by the squared difference between the true and reconstructed field, is determined as a function of the survey parameters. These in turn are subject to the physical limitations of the vehicle. Combining these constraints, we arrive at a tool which can be used to maximize survey efficiency and to assess relative efficiencies of various adaptive sampling techniques.
Bellingham et al. (Mon,) studied this question.