혼합형 폴리라인 단순화 기법을 이용한 GIS 벡터맵 데이터 손실 압축

Abstract

The development of computer and mobile technology has arisen rapidly the interest on mobile GIS(geographic information system) and web GIS as well as the expansion of GIS service. But, the growth of GIS has required consistently the large capacity of GIS map data. Mobile or web GIS with mobility and real-time ability is a system that uses the geographical information through the mobile terminals or web. But mobile or web GIS has some limitations of the transmitted data capacity, the mobile terminal resources, and the restricted network bandwidth. These limitations have caused for the problem of the capacity of GIS map data. GIS vector map consists of a number of layers. A layer represents a specific theme, such as roads, railroads, contours, coastlines, boundaries, and so on, by data attributes of point, polyline, and polygon. Polyline is the most common representation of GIS vector map. Therefore, this paper presents the lossy data compression of GIS vector map using hybrid polyline simplification method. The proposed scheme extracts all layers that includes polylines in a GIS vector map and then compress polylines in each layer through two processes. The processes consist of hybrid polyline simplification and spatial data compression part. Firstly, the hybrid polyline simplification applies a combination of three line simplification algorithms, which are Douglas-Peucker algorithm, Sleeve-Fitting algorithm, and simplification using a turning function, on polylines and finds the fix points for the polyline segmentation. Then our simplification calculates MAE(minimum area error) for each segment in the polyline for allocating the existing algorithms with high performance and then simplifies the each segment with the allocated algorithm. Our simplification adjusts a degree of simplification through the weighting factor. Through the process, we can improve the compression efficiency and shape preservation of polyline data and make a variable precision map. Secondly, the spatial data compression is processed by an energy compaction method on spatial domain for the simplified polyline of the previous stage. Through this process, we maximize the compression efficiency. Our experiments evaluated the visual quality and the compression efficiency of our scheme and conventional schemes for compression and simplification. From experimental results, we verified that our scheme has more good visual quality and high compression than conventional schemes.