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作 者:Christos Kastrisios Brian Calder Giuseppe Masetti Peter Holmberg
机构地区:[1]Center for Coastal and Ocean Mapping/UNH-NOAA Joint Hydrographic Center,University of New Hampshire,Durham,NH,USA [2]U.S.Department of Commerce,National Oceanic and Atmospheric Administration,National Ocean Service,Office of Coast Survey,Hydrographic Survey Division,Seattle,WA,USA
出 处:《Geo-Spatial Information Science》2019年第4期290-303,I0006,共15页地球空间信息科学学报(英文)
基 金:This work is supported by the National Oceanic and Atmospheric Administration[grant number NA15NOS4000200].
摘 要:The nautical chart is one of the fundamental tools in navigation used by mariners to plan and safely execute voyages.Its compilation follows strict cartographic constraints with the most prominent being that of the safety.Thereby,the cartographer is called to make the selection of the bathymetric information for portrayal on charts in a way that,at any location,the expected water depth is not deeper than the source information.To validate the shoal-biased pattern of selection two standard tests are used,i.e.the triangle and edge tests.To date,some efforts have been made towards the automation of the triangle test,but the edge test has been largely ignored.In the context of research on a fully automated solution for the compilation of charts at different scales from the source information,this paper presents an algorithmic implementation of the two tests for the validation of selected soundings.Through a case study with real-world data,it presents the improved performance of the implementation near and within depth curves and coastlines and points out the importance of the edge test in the validation process.It also presents the,by definition,intrinsic limitation of the two tests as part of a fully automated solution and discusses the need for a new test that will complement or supersede the existing ones.
关 键 词:Automated nautical cartography nautical chart generalization chart safety constraint sounding generalization nautical surface test sounding selection category zone of confidence
分 类 号:P20[天文地球—测绘科学与技术]
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