A Progressive Method of Simplifying Polylines with Multi-bends Simplification Templates

Polyline simplification is one of the most important and classic researches in multi-scale expression of cartography and GIS. Polyline simplification methods based on bend units get widespread attention recently. Having analyzed the bends composing characteristics and the manual simplification process of polylines, it is resonable to find that not all of invisible bend units are deleted directly. A new progressive simplification method based on multi-bends groups is proposed. Firstly, based on the threshold of the simplified scale, polylines are divided into multi-bends groups. Secondly, in order to avoid over-simplification, some reasonable bends deletion options which called multi-bends templates are proposed. However multi-bends templates is not steady and always related to the quantity of multi-bends uniquely. Considering of the minimal errors derived form polyline simplification, the best multi-bends template that result in the least displacement is selected to simplify muli-bends groups. Thirdly, polylines do not stop repeating the above two steps until all bend units of simplified polylines can be detected in the simplified scale. Experiments with real road-net data were implemented, and comparison with other algorithms is discussed. Results show advantages including: (i) The proposed algorithm is a progressive simplification process which is conform to human cognition. (ii) The proposed algorithm can preserve the main shape of the polyline with deleting invisible bend units enough. (iii) The proposed algorithm avoid unnecessary displacement by deleting bend units as little possible.

[1]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .

[2]  G. Jenks Geographic Logic In Line Generalization , 1989 .

[3]  Stan Openshaw,et al.  Algorithms for automated line generalization1 based on a natural principle of objective generalization , 1992, Int. J. Geogr. Inf. Sci..

[4]  J. D. Whyatt,et al.  Line generalisation by repeated elimination of points , 1993 .

[5]  A. Saalfeld Topologically Consistent Line Simplification with the Douglas-Peucker Algorithm , 1999 .

[6]  G. Dutton Scale, Sinuosity, and Point Selection in Digital Line Generalization , 1999 .

[7]  L. Hurni,et al.  A progressive line simplification algorithm , 2002 .

[8]  Max J. Egenhofer,et al.  Ontology-driven map generalization , 2005, J. Vis. Lang. Comput..

[9]  Wenzhong Shi,et al.  Performance Evaluation of Line Simplification Algorithms for Vector Generalization , 2006 .

[10]  Zhu Qiang Improvement and Assessment of Li-Openshaw Algorithm , 2007 .

[11]  William A. Mackaness,et al.  A functional perspective on map generalisation , 2009, Comput. Environ. Urban Syst..

[12]  Paulo Raposo Scale-specific automated line simplification by vertex clustering on a hexagonal tessellation , 2013 .

[13]  Kiyun Yu,et al.  Hybrid line simplification for cartographic generalization , 2011, Pattern Recognit. Lett..

[14]  Cao Shen-Zhou,et al.  Multi-way Trees Representation for Curve Bends , 2013 .

[15]  José L. G. Pallero,et al.  Robust line simplification on the plane , 2013, Comput. Geosci..

[16]  Christopher B. Jones,et al.  Map Generalization with a Triangulated Data Structure , 2013 .

[17]  T. Ai,et al.  A Simplification of Ria Coastline with Geomorphologic Characteristics Preserved , 2014 .

[18]  StefanakisEmmanuel,et al.  Contextual Douglas-Peucker Simplification , 2015 .

[19]  Fang Wu,et al.  A New Simplification Approach Based on the Oblique-Dividing-Curve Method for Contour Lines , 2016, ISPRS Int. J. Geo Inf..

[20]  Jingzhong Li,et al.  Envelope generation and simplification of polylines using Delaunay triangulation , 2017, Int. J. Geogr. Inf. Sci..