Abstract

Gridding heterogeneous bathymetric data sets for the compilation of Digital bathymetric models (DBMs), poses specific problems when there are extreme variations in source data density. This requires gridding routines capable of subsampling high-resolution source data while preserving as much as possible of the small details, at the same time as interpolating in areas with sparse data without generating gridding artifacts. A frequently used gridding method generalizes bicubic spline interpolation and is known as continuous curvature splines in tension. This method is further enhanced in this article in order to specifically handle heterogeneous bathymetric source data. Our method constructs the final grid through stacking several surfaces of different resolutions, each generated using the splines in tension algorithm. With this approach, the gridding resolution is locally adjusted to the density of the source data set: Areas with high-resolution data are gridded at higher resolution than areas with sparse source data. In comparison with some of the most widely used gridding methods, our approach yields superior DBMs based on heterogeneous bathymetric data sets with regard to preserving small bathymetric details in the high-resolution source data, while minimizing interpolation artifacts in the sparsely data constrained regions. Common problems such as artifacts from ship tracklines are suppressed. Even if our stacked continuous curvature splines in tension gridding algorithm has been specifically designed to construct DBMs from heterogeneous bathymetric source data, it may be used to compile regular grids from other geoscientific measurements.

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