最优信息熵约束的居民地点状要素选取方法  

Selection Method of Residential Point Features Constrained by Optimal Information Entropy

作　　者：刘万增[1] 陆辰妮 霍亮 吴晨琛[1] 赵婷婷[1] 朱秀丽[1] LIU Wanzeng;LU Chenni;HUO Liang;WU Chenchen;ZHAO Tingting;ZHU Xiuli(National Geomatics Center of China,Beijing 100830,China;National Quality Inspection and Testing Center for Surveying and Mapping Products,Beijing 100830,China;School of Geomatics and Urban Spatial Informatics,Beijing University of Civil Engineering and Architecture,Beijing 102616,China)

机构地区：[1]国家基础地理信息中心,北京100830 [2]国家测绘产品质量检验测试中心,北京100830 [3]北京建筑大学测绘与城市空间信息学院,北京102616

出　　处：《武汉大学学报（信息科学版）》2021年第8期1178-1185,共8页Geomatics and Information Science of Wuhan University

基　　金：国家重点研发计划(2018YFC0807005)。

摘　　要：实现多种约束下的地图信息的负载均衡是制图综合的难点之一。在中小比例尺地图中,对于乡镇及村庄居民点进行尺度转换,需要综合考虑其行政级别、拓扑和度量关系,以使地图信息负载量在一定尺度下达到合理。提出一种基于最优信息熵约束的居民地点状要素选取方法,在最优信息熵约束下,调整度量关系约束,优先考虑语义关系,保留行政级别高的居民点,对行政级别低的居民点,如果不是道路端点,且不满足度量关系约束,则删除该点,不断迭代,直到满足最优信息熵约束。采用1∶250000居民地点数据进行实验,实现了维护拓扑一致性、级别优先性、度量合理性的居民地点状要素选取,在有效地保持地图的负载均衡和可读性的同时,实现了地图有效信息量的最大化。采用最优信息熵约束进行居民点选取,在整体上可以保留居民点群空间分布的疏密特征,效果上能够达到图幅信息量的负载均衡。Objectives:The load balancing of map information under multiple constraints is one of the diffi-culties in cartographic generalization.In small and medium-scale maps,it is necessary to comprehensively consider their administrative levels,topologies and metric relationships for the scale conversion of town-ships and village residential point features to make the map information load reasonable at a certain scale.Methods:This paper proposes a method for selecting residential point features based on optimal informa-tion entropy constraints.Under the constraints of optimal information entropy,the metric relationship con-straints are adjusted,the semantic relationships are prioritized,the residential point features with higher ad-ministrative levels are reserved,and for the residential point features with lower administrative levels,if they are not the endpoints of the road and do not satisfy the metric relationship constraint,then the points are deleted,and the process is iterated until the optimal information entropy constraint is satisfied.Results:Experiments with 1∶250000 residential point data have realized the selection of residential location ele-ments that maintain topological consistency,level priority,and metric rationality.The load balancing and readability of the map are effectively maintained,meanwhile,the amount of effective information of the map is maximized based on the algorithm.Conclusions:The optimal information entropy constraint is adopted for the selection of residential points,which can retain the density characteristics of the spatial distribution of the residential point group as a whole,and achieve the load balancing of map information in effect.

关 键 词：点状要素选取 地图制图 最优信息熵约束 DELAUNAY三角网 VORONOI图 

分 类 号：P283[天文地球—地图制图学与地理信息工程]