Abstract
In recent years, demands for electronic nautical chart have increased significantly in various fields of applications, where sounding is one of the main features, and a large number of studies have been conducted toward sounding generalization. However, most automatic sounding generalization methodologies are focused on navigation safety aspects yet seldom consider the depiction function to submarine topography. To address this limitation, we propose a novel approach, termed as sounding generalization maintaining submarine topography (SGMST), that can maintain the submarine terrain as well as observe other generalization rules. Based on the topographic recognition, a new index (the importance values of soundings) was developed to measure the significance of each sounding and then indicate the generalization process. To verify the effectiveness of our method, we applied SGMST on a multibeam sounding experimental dataset and compared it with the influence circle algorithm (ICa) as a baseline. Experimental results showed advantages of our approach meeting the sounding generalization requirements, and the undersea surface modeled by generalized results raises by 0.27 m and 0.37 m through SGMST and ICa, respectively. The new method provides an alternative to future applications involving automatic sounding generalization.
Highlights
IN the Electronic Nautical Charts (ENC), sounding is one of the most important features that provides mariners with key information such as the shape of the ocean bottom together with chart depth contours
There are thousands of soundings in a chart but only a few of them are critical in depicting the structure of submarine topography and guarantee the navigation safety [1]
Motivated by the Tobler's first law of geography (TFL) where near things are assumed with a high correlation than distant things [22] - [24], we model our importance value with the spatial proximity between soundings and these feature points, and the closer, the more important
Summary
IN the Electronic Nautical Charts (ENC), sounding is one of the most important features that provides mariners with key information such as the shape of the ocean bottom together with chart depth contours. There are thousands of soundings in a chart but only a few of them are critical in depicting the structure of submarine topography and guarantee the navigation safety [1]. Compilation of a nautical chart from a large scale to a finer scale needs a substantial amount of manual operations to select proper soundings, which is quite time- and costconsuming. It is necessary to carry out research in automatic sounding generalization methods to meet the growing requirements in ENC. Sounding generalization is a complex process that needs to take both geometric and semantic levels into account, which involves delicate considerations of several constraints and regulations. There are some generally known principles to follow from International Hydrographic Organization (IHO) standards [2] and literatures [3], [5] in this field:
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