文献类型： 外文期刊
作者： Yan, Yu 1 ; Sun, Ying 1 ; Wang, Shaobo 2 ; Lu, Yuefeng 1 ; Hu, Yulong 4 ; Lu, Miao 3 ;
作者机构： 1.Shandong Univ Technol, Sch Civil Engn & Geomat, Zibo 255049, Peoples R China
2.Zibo Nat Resources & Planning Bur Econ Dev Zone Br, Zibo 255000, Peoples R China
3.Natl Ctr Technol Innovat Comprehens Utilizat Salin, Dongying 257347, Peoples R China
4.Guojiao Spatial Informat Technol Beijing Co Ltd, Beijing 100011, Peoples R China
5.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arid & Semiarid A, Beijing 100081, Peoples R China
关键词： spatial relationships; ISOD descriptor; included angle chain; cambervariance; multi-scale road networks
期刊名称：ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION （ 影响因子：2.8； 五年影响因子：3.3 ）
ISSN：
年卷期： 2025 年 14 卷 7 期
页码：
收录情况： SCI
摘要： In geographic information data processing, the matching of road data at different scales is crucial. Due to scale differences, road features can change, posing a challenge to multi-scale matching. Spatial relationship is the key to matching because it remains stable at different scales. In this paper, we propose an improved summation product of direction and distance (ISOD) descriptor, which combines features such as included angle chain and camber variance with similarity features such as length, direction, and Hausdorff distance to construct an integrated similarity metric model for multi-scale road matching. The experiments proved that the model achieved 94.75% and 93.34% precision and recall in 1:50,000 and 1:10,000 scale road data matching and 86.39% and 94.06% in 1:250,000 and 1:50,000 scale road data matching, respectively. This proves the effectiveness and practicality of the method. The ISOD descriptor and integrated similarity metric model in this paper provide an effective method for multi-scale road data matching, which helps the integration and fusion of geographic information data, and has an important application value in the fields of intelligent transport and urban planning.
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