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

Abstract

ABSTRACT 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.