A progressive method for the collapse of river representation considering geographical characteristics

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.