During map generalization,the collapse of geometry,which is also called geometric dimension reduction,is a basic generalization operation.When the map scale decreases,rivers with long,shallow polygonal shapes,usually ...During map generalization,the collapse of geometry,which is also called geometric dimension reduction,is a basic generalization operation.When the map scale decreases,rivers with long,shallow polygonal shapes,usually require their dual-line representation to be collapsed to a single line.This study presents a new algorithm called superpixel river collapse(SURC)to convert dual-line rivers to single-line rivers based on raster data.In this method,dual-line rivers are first segmented at different levels of detail using a superpixel method called simple linear iterative clustering.Then,by connecting the edge midpoints and centre of mass of each superpixel,single-line rivers are preliminarily generated from dual-line rivers.Finally,an interpolation algorithm called polynomial approximation with an exponential kernel is applied to maintain the uniform distribution of the feature points of single-line rivers at different levels of detail(LOD).The presented method can progressively collapse the river during scale transformation to support the LOD representation in a highly sensitive way.The results show that compared with three typical thinning algorithms,the SURC method can generate smooth single-line rivers from dual-line rivers considering different river widths while effectively avoiding burrs and fractured intersections.展开更多
基金supported by the National Key Research and Development Program of China under grant 2017YFB0503500the National Natural Science Foundation of China under grant 41531180+2 种基金the National Key Research and Development Program of China under grant 2017YFB0503601 and 2017YFB0503502the National Natural Science Foundation of China under grant 41671448the Key Research and Development Program of Sichuan Province under grant 19ZDYF0839.
文摘During map generalization,the collapse of geometry,which is also called geometric dimension reduction,is a basic generalization operation.When the map scale decreases,rivers with long,shallow polygonal shapes,usually require their dual-line representation to be collapsed to a single line.This study presents a new algorithm called superpixel river collapse(SURC)to convert dual-line rivers to single-line rivers based on raster data.In this method,dual-line rivers are first segmented at different levels of detail using a superpixel method called simple linear iterative clustering.Then,by connecting the edge midpoints and centre of mass of each superpixel,single-line rivers are preliminarily generated from dual-line rivers.Finally,an interpolation algorithm called polynomial approximation with an exponential kernel is applied to maintain the uniform distribution of the feature points of single-line rivers at different levels of detail(LOD).The presented method can progressively collapse the river during scale transformation to support the LOD representation in a highly sensitive way.The results show that compared with three typical thinning algorithms,the SURC method can generate smooth single-line rivers from dual-line rivers considering different river widths while effectively avoiding burrs and fractured intersections.
