Research On Compression Algorithm For Vector Data In GIS

Vector data compression has always been a research hotspot in the field of GIS.By reducing the amount of data,vector graphics can satisfy the application requirements of different levels and scales,and reduce the data transmission,processing time and storage overhead,improve the graphics analysis,rendering the purpose.The study of history can be traced back to more than and 40 years ago.Many compression algorithms have appeared,such as Douglas-Peucker algorithm(DP algorithm),Lang method,Li-Openshaw algorithm,the compression algorithm based on wavelet analysis,and some compression algorithms combined with intelligent algorithms(such as genetic algorithms,dynamic programming algorithms,particle swarm algorithm).Although some achievements have been made in the research of this problem,some problems still exist in the field of vector data compression with the development of technology and the new demand.This paper have analyzed and optimized the problem of DP algorithm.Aiming at two kinds of topological alienation problems which may be lead in the processing of multi-vector data,it proposed an effective and feasible solution,to ensure the topological consistency of multi-vector graphics compression.The main work of the paper is as follows:(1)A segmented DP algorithm based on node importance is proposed,and a lot of experiments are carried out.The experimental results show that compared with the classical DP algorithm,the algorithm has improved the shape preserving degree and the time efficiency.(2)This paper proposes a new algorithm for extracting common edges based on scan line and Geohash index to solve the problem that the common edges of adjacent graphs are easy to crack.First we determine the intersection graph for each graph by using the monotone chain scan line algorithm.For the two graph of the intersection of the external rectangle,we use the Geohash index of the graph to quickly find the common points of the two graphs,extract the common edges and the non common edges,and mark the order of the vertices of the common edges.Finally mark the compressed public side,to ensure that the public side only once.The experimental results show that the algorithm can not only solve the problem of public edge cracks,but also has the advantage of time efficiency.(3)In this paper,we propose a fast processing algorithm based on Geohash index,which can deal with the problem of self intersection or disjoint topology dissimilation in the simplified dataset.Firstly,the polygonal region of the posterior curve siege is transformed into Geohash code.Usingthe Geohash coding set as a query condition to retrieve the corresponding point in the code itself and the associated graph.And then through the ray method to accurately determine whether these points are located in the pre-curve after the siege of the polygon area.If there exists a point located in the polygon area,that may occur from the intersection or crossing,for correction.The experimental results show that the algorithm can guarantee that there is no self intersection or disjoint topology dissimilation,and the time efficiency is high.(4)In Microsoft Visual Studio 2010 development environment,using C# programming language and object-oriented design,we developed a small software system as a test platform,and the test platform was tested.