期刊文献+

Overlay Generalization of Polygons Based on Fuzzy-Voronoi

Overlay Generalization of Polygons Based on Fuzzy-Voronoi
下载PDF
导出
摘要 The analysis of an overlaid map with different attributes has a very important function in GIS. In an overlaid map, approximately half of the constructed polygons are tiny and only account for less than 5% of the total area. In subsequent analysis of an overlaid map, a tiny polygon may require the same amount of computing time and memory space as any large one. In addition, in most cases it is meaningless to treat such polygons as distinct analysis units. So eliminating the tiny polygons is useful to improve efficiency. Now we often use the methods of “boundary comparison” and “fuzzy discriminance” to merge tiny polygons. But in the boundary comparison method, a polygon may be merged into a neighbor of quite different attribute values. In the second method, when the fuzzy grades of two boundary lines are almost the same and their lengths are different, this can lead to large error. In this paper, the partition principle of fuzzy Voronoi (F V) is proposed based on the characteristic of fuzzy boundary and the contiguity of Voronoi diagram. The bigger tiny polygons are divided by Voronoi diagram, and then are merged to neighbor polygon according to contiguity. The F V principle and arithmetic are presented in detail. In the end, an experiment is given; the result has proved that error in the F V method, compared with the two other methods, is only about 30%. The analysis of an overlaid map with different attributes has a very important function in GIS. In an overlaid map, approximately half of the constructed polygons are tiny and only account for less than 5% of the total area. In subsequent analysis of an overlaid map, a tiny polygon may require the same amount of computing time and memory space as any large one. In addition, in most cases it is meaningless to treat such polygons as distinct analysis units. So eliminating the tiny polygons is useful to improve efficiency. Now we often use the methods of “boundary comparison” and “fuzzy discriminance” to merge tiny polygons. But in the boundary comparison method, a polygon may be merged into a neighbor of quite different attribute values. In the second method, when the fuzzy grades of two boundary lines are almost the same and their lengths are different, this can lead to large error. In this paper, the partition principle of fuzzy Voronoi (F V) is proposed based on the characteristic of fuzzy boundary and the contiguity of Voronoi diagram. The bigger tiny polygons are divided by Voronoi diagram, and then are merged to neighbor polygon according to contiguity. The F V principle and arithmetic are presented in detail. In the end, an experiment is given; the result has proved that error in the F V method, compared with the two other methods, is only about 30%.
出处 《International Journal of Mining Science and Technology》 SCIE EI 2000年第2期15-20,共6页 矿业科学技术学报(英文版)
基金 Supported by the National Natural Science Foundation of China(No.6983 3 0 10 )
关键词 FUZZY BOUNDARY FUZZY VORONOI OVERLAY GENERALIZATION fuzzy boundary fuzzy Voronoi overlay generalization
  • 相关文献

参考文献6

  • 1史文中,刘文宝.GIS中线元位置不确定性的随机过程模型[J].测绘学报,1998,27(1):37-44. 被引量:32
  • 2刘大杰,华慧.GIS线要素不确定性模型的进一步探讨[J].测绘学报,1998,27(1):45-49. 被引量:30
  • 3D Altman.Fuzzy set theoretic approaches for handling imprecision in spatial analysis. International Journal of Geographical Information System . 1994
  • 4D G Brown.Classification and boundary vagueness in mapping presettlement forest types. International Journal of Geographical Information Science . 1998
  • 5Martien Molenaar.The extensional uncertainty of spatial objects, advances in GIS research II. The Netherlands . 1996
  • 6T J Davis,C P Keller.Modelling uncertainty in natural resource analysis using fuzzy sets and Monte Carlo simulation:slope stability prediction. International Journal of Geographical Information Science . 1997

二级参考文献10

  • 1朱光.GIS中的误差与不确定性问题[J].武测科技,1994(2):45-48. 被引量:3
  • 2李德仁,彭美云,张菊清.GIS中线要素的定位不确定性模型研究[J].武汉测绘科技大学学报,1995,20(4):283-288. 被引量:28
  • 3史文中,ITC Publication,1994年,2期
  • 4Zhang J X,A strategy for Built-in Error Modelling in a GIS,1992年
  • 5申鼎煊,随机过程,1990年
  • 6团体著者,数学手册,1984年
  • 7於宗俦,测量平差基础,1983年
  • 8黄幼才,GIS空间数据误差分析和处理,1995年
  • 9Shi Wenzhong,Modeling Positional and Thematic Uncertainties in Intergration of remote sensing and GIS,1994年
  • 10刘文宝,1995年

共引文献53

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部