关键词: 贝叶斯方法, 海岸线分段, 地图综合

Abstract: In line generalization, results depend very much on the characteristics of the line. For this reason it would be useful to obtain an automatic segmentation and enrichment of lines in order to apply to each section the best algorithm and the appropriate parameter. In this paper two factors of curves classification are discussed, which are directionality and sinuosity of curve, analyze the curve characteristic parameters with relation to these two dimensions and present a methodology for applying a line-classifying based on Bayesian method for a coastline segmentation task. The procedure is that 1） different sorts of curves are selected as training samples at first; 2） a moving window along the coastline is used to abstract curve parameters of curve segment within the window and to process these parameters using PCA method; 3） the statistical distribution functions of parameters of different sorts of curves are estimated and examined, and the curve segments within the window are classified base on Bayesian method; 4） these continuous curve units which belong to identical class are merged, and the points dividing different sorts of curves segment are regarded as the segmenting points of coastline. A test is performed over two coastline from a 1∶25 000 and 1∶1 000 000 scale mapwith a recommendation of the value of the parameters of the moving window, and segmentation results are reasonable and are consistent with human cognition.

Key words: Bayesian method, coastline segment, map generalization