多尺度地图空间居民地语义相似度计算方法

doi:10.11947/j.AGCS.2022.20210074

测绘学报 ›› 2022, Vol. 51 ›› Issue (1): 95-103.doi: 10.11947/j.AGCS.2022.20210074

多尺度地图空间居民地语义相似度计算方法

高晓蓉^1,2,3, 闫浩文^1,2,3, 禄小敏^1,2,3

1. 兰州交通大学测绘与地理信息学院, 甘肃兰州 730070;
2. 地理国情监测技术应用国家地方联合工程研究中心, 甘肃兰州 730070;
3. 甘肃省地理国情监测工程实验室, 甘肃兰州 730070

收稿日期:2021-02-05 修回日期:2021-09-28 发布日期:2022-02-15
通讯作者: 闫浩文 E-mail:yanhw@mail.lzjtu.cn
作者简介:高晓蓉(1983-),女,博士生,研究方向为面向地图综合的空间相似关系理论。E-mail:290119280@qq.com
基金资助:
国家自然科学基金（41930101）；兰州交通大学优秀平台（201806）；甘肃省教育厅：优秀研究生“创新之星”项目（2021CXZX-549）

Semantic similarity measurement for building polygon aggregation in multi-scale map space

GAO Xiaorong^1,2,3, YAN Haowen^1,2,3, LU Xiaomin^1,2,3

1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China;
2. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China;
3. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China

Received:2021-02-05 Revised:2021-09-28 Published:2022-02-15
Supported by:
The National Natural Science Foundation of China (No. 41930101); The Lanzhou Jiaotong University Excellent Platform (LZJTU EP) (No. 201806); Department of Education of Gansu Province:The Excellent Postgraduate Student "Innovation Star" Project (No. 2021CXZX-549)

摘要/Abstract

摘要： 地图综合的本质是一种空间相似变换，制图者在相似原则的指导下实施概括，读图者从包含相似性的地图中形成心象地图、重构现实世界。因此，多尺度地图空间中的相似关系研究非常重要。然而，由于相似的可计算性差，且其计算的目的在于揭示更深层次的信息，地图综合中相似关系尤其是语义相似关系的研究相对较少。针对这一问题，本文以语义功能区约束下的大比例尺街区式居民地合并（1∶1750至1∶4000）为例，基于匹配距离模型计算建筑物合并中的语义相似度，得到语义相似度在关键比例尺节点的值，并对结果进行分析、评价。试验表明，语义功能区约束下的建筑物合并符合读图者的地图认知需求，本文所述方法有助于地图更好地发挥信息传输载体的作用。

关键词: 语义相似度, 街区式居民地合并, 地图综合, 多尺度地图空间, 匹配距离模型

Abstract: Map generalization is a process of spatial similarity transformation in multi-scale map spaces. Cartographers generalize under the guidance of the similarity principle; at the same time, map readers form mental maps and reconstruct the real world from maps containing similarity. Thus, it is of great significance to study and measure the similarity relations with respect to the scale reduces in multi-scale map spaces. However, due to the poor computability of similarity and the purpose of its computation is to reveal deeper information, there are few achievements on similarity relations especially semantic relations in multi-scale map spaces. To solve this problem, semantic similarities in city block aggregation (from approximately 1:1750 to 1:14 000) under the constraint of semantic functional units are computed, and the method for measuring the semantic similarity is the matching-distance model based on ontology and set theory. By the experiment of different city block generalization, the semantic similarity values at key scales were obtained and the results were analyzed and evaluated. The experimental results have shown that the building aggregation under the constraint of semantic functional units is in accordance with map readers' cognitive needs. The method described in this paper is helpful for map to play a better role as a carrier of information transmission.

Key words: semantic similarity, city block settlement aggregation, map generalization, multi-scale map space, matching-distance model

中图分类号:

P208

高晓蓉, 闫浩文, 禄小敏. 多尺度地图空间居民地语义相似度计算方法[J]. 测绘学报, 2022, 51(1): 95-103.

GAO Xiaorong, YAN Haowen, LU Xiaomin. Semantic similarity measurement for building polygon aggregation in multi-scale map space[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(1): 95-103.

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多尺度地图空间居民地语义相似度计算方法

Semantic similarity measurement for building polygon aggregation in multi-scale map space

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