| GIS中线元的误差熵带研究 |
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| 引用本文： | 李大军,龚健雅,谢刚生,杜道生.GIS中线元的误差熵带研究[J].武汉大学学报(信息科学版),2002,27(5):462-466. |
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| 作者姓名： | 李大军 龚健雅 谢刚生 杜道生 |
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| 作者单位： | 1. 武汉大学测绘遥感信息工程国家重点实验室,武汉市珞喻路129号,430079
2. 华东理工学院测量系,江西抚州市环城西路14号,344000 |
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| 基金项目： | 国家自然科学基金资助项目 (4 60 710 68)。 |
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| 摘 要： | 基于现有的线元位置不确定性模型大多与置信水平的选取有关,而置信水平的选取带有一定程度的主观性,因而不能惟一确定,引入信息熵理论,提出了线元的误差熵带模型,并将它与“E－带”进行了比较,计算了落入其内的概率。该模型根据联合熵惟一确定,与置信水平的选取无关。
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| 关 键 词： | GIS 线元 位置不确定性 联合熵 误差熵圆 误差熵带 地理信息系统 |
| 文章编号： | 1000-050X(2002)05-0462-05 |
| 修稿时间： | 2002年2月5日 |
Error Entropy Band for Linear Segments in GIS |
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| LI Dajun,GONG Jianya,XIE Gangsheng,DU Daosheng.Error Entropy Band for Linear Segments in GIS[J].Geomatics and Information Science of Wuhan University,2002,27(5):462-466. |
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| Authors: | LI Dajun GONG Jianya XIE Gangsheng DU Daosheng |
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| Institution: | LI Dajun 1 GONG Jianya 1 XIE Gangsheng 2 DU Daosheng 1 |
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| Abstract: | Uncertainty of spatial data in GIS can be in the aspect of position,attribution,temporary,logical relation and completeness.Among them,positional uncertainty of linear segments is an important aspect.There are uncertainty models of linear segments,such as " E _band"," g _band" and so on,in some confidence bands,and they are relevant to different confident levels,but choice of confident levels exists a certain extent subjectivity and therefore cannot be completely determined. In this paper,on the basis of union entropy and maximum entropy theorem in information theory,an error entropy band is put forward and the comparison between error entropy band and " E _band" is given,and then the probability of falling into it is calculated.Finally,some conclusions are drawn as follows: 1) Error entropy band for linear segment is an average uncertainty measure of linear segments,and can be solely determined by union entropy and is independent of the choice of confident level.Therefore,it is a comparatively impersonal index. 2) The ratio of band width between error entropy band and E _band is e times,and the ratio of area is about times,and the probability of falling into them is 99.87%. 3) Information theory can provide a new approach for solving uncertainty problems in GIS. |
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| Keywords: | line segments positional uncertainty union entropy entropy circle error entropy band |
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