{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T15:32:08Z","timestamp":1766158328049,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2019,5,21]],"date-time":"2019-05-21T00:00:00Z","timestamp":1558396800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41471386","41801396"],"award-info":[{"award-number":["41471386","41801396"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The spatial pattern is a kind of typical structural knowledge that reflects the distribution characteristics of object groups. As an important semantic pattern of road networks, the city center is significant to urban analysis, cartographic generalization and spatial data matching. Previous studies mainly focus on the topological centrality calculation of road network graphs, and pay less attention to the delineation of main centers. Therefore, this study proposes an automatic recognition method of main center pattern in road networks. We firstly extract the main clusters from road nodes by improving the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) with fuzzy set theory. Moreover, the center area is generated with road meshes according to the area ratio with the covering discs of the main clusters. This proposed algorithm is applied to the road networks of a monocentric city and polycentric city respectively. The results show that our method is effective for identifying the main center pattern in the road networks. Furthermore, the contrast experiments demonstrate our method\u2019s higher accuracy.<\/jats:p>","DOI":"10.3390\/ijgi8050238","type":"journal-article","created":{"date-parts":[[2019,5,21]],"date-time":"2019-05-21T10:52:51Z","timestamp":1558435971000},"page":"238","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Extracting Main Center Pattern from Road Networks Using Density-Based Clustering with Fuzzy Neighborhood"],"prefix":"10.3390","volume":"8","author":[{"given":"Xiaojie","family":"Cui","sequence":"first","affiliation":[{"name":"Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Jiayao","family":"Wang","sequence":"additional","affiliation":[{"name":"Henan University, Kaifeng 475001, China"}]},{"given":"Fang","family":"Wu","sequence":"additional","affiliation":[{"name":"Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Jinghan","family":"Li","sequence":"additional","affiliation":[{"name":"Xi\u2019an Surveying and Mapping Technical Center, Xi\u2019an 710054, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6184-1300","authenticated-orcid":false,"given":"Xianyong","family":"Gong","sequence":"additional","affiliation":[{"name":"Information Engineering University, Zhengzhou 450001, China"}]},{"given":"Yao","family":"Zhao","sequence":"additional","affiliation":[{"name":"Information Engineering University, Zhengzhou 450001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4552-8223","authenticated-orcid":false,"given":"Ruoxin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Chair of Cartography, Technical University of Munich, Munich 80333, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,21]]},"reference":[{"key":"ref_1","unstructured":"Mackaness, W., and Edwords, G. 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