摘要
针对方向关系矩阵模型对同一方向片区内方向变化识别能力不足、对不同方向片区间基准方向距离定义不完备、对任意方向关系矩阵间距离计算不够精确等问题,本文提出一种方向关系二元组模型,结合格网方向关系矩阵与质心方向关系矩阵,顾及对象的分布比例及质心位置变化,区分同一方向片区内的方向关系差异。同时,基于人类空间认知优化传统邻域图,建立适用于任意方向关系间基准距离度量的质心方向距离,通过EMD(Earth mover's distance)距离进一步提升方向关系二元组间距离计算的精确度。试验结果表明,本文方法简单可行,度量结果更符合人类认知,可应用于制图综合结果评估等任务。
Aiming at problems that in direction relation matrix model, recognition ability for distinguishing direction changes in the same cardinal direction is insufficient, the direction distance references for different cardinal directions are defined incompletely, and the distance calculation between arbitrarily direction relation matrices is not accurate enough, this paper proposes a direction relation two-tuple model, which combines grid-based direction relation matrix and centroid-based direction relation matrix to concern both distribution ratio variations and centroid position variations for objects, thus distinguishing the direction difference in the same cardinal direction. Meanwhile, the traditional neighborhood graph is optimized based on human spatial cognition, and a centroid direction distance reference suitable for arbitrarily direction relationships is established. Finally the Earth mover's distance(EMD) is utilized to further improve the accuracy of distance calculation between direction relation two-tuples. Experiments indicate the method is simple and feasible, the measurement results are more consistent with human cognition, and can be better applied to tasks like cartographic generalization results evaluation.
作者
龚希
谢忠
周林
何占军
GONG Xi;XIE Zhong;ZHOU Lin;HE Zhanjun(Department of Information Engineering, China University of Geosciences, Wuhan 430074, China;College of Computer, Hubei University of Education, Wuhan 430074, China;National Engineering Research Center of Geographic Information System, Wuhan 430074, China)
出处
《测绘学报》
EI
CSCD
北大核心
2021年第12期1705-1716,共12页
Acta Geodaetica et Cartographica Sinica
基金
国家重点研发计划(2018YFB0505500,2018YFB0505504)
地质探测与评估教育部重点实验室开放基金(GLAB2020ZR05)。
关键词
空间方向
相似性度量
格网方向关系矩阵
质心方向关系矩阵
EMD距离
spatial direction
similarity measurement
grid-based direction relation matrix
centroid-based direction relation matrix
Earth mover's distance
