{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T10:10:30Z","timestamp":1767262230827,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,1,14]],"date-time":"2023-01-14T00:00:00Z","timestamp":1673654400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2019YFB2102503","2019YFB2102500","LMEE-KF2021002","42201331","AR2111"],"award-info":[{"award-number":["2019YFB2102503","2019YFB2102500","LMEE-KF2021002","42201331","AR2111"]}]},{"name":"Open Fund of Key Laboratory of Monitoring, Evaluation and Early Warning of Territorial Spatial Planning Implementation, Ministry of Natural Resources","award":["2019YFB2102503","2019YFB2102500","LMEE-KF2021002","42201331","AR2111"],"award-info":[{"award-number":["2019YFB2102503","2019YFB2102500","LMEE-KF2021002","42201331","AR2111"]}]},{"name":"National Natural Science Foundation of China","award":["2019YFB2102503","2019YFB2102500","LMEE-KF2021002","42201331","AR2111"],"award-info":[{"award-number":["2019YFB2102503","2019YFB2102500","LMEE-KF2021002","42201331","AR2111"]}]},{"name":"Chinese Academy of Surveying and Mapping Basic Research Fund Program","award":["2019YFB2102503","2019YFB2102500","LMEE-KF2021002","42201331","AR2111"],"award-info":[{"award-number":["2019YFB2102503","2019YFB2102500","LMEE-KF2021002","42201331","AR2111"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Spatial clustering is dependent on spatial scales. With the widespread use of web maps, a fast clustering method for multi-scale spatial elements has become a new requirement. Therefore, to cluster and display elements rapidly at different spatial scales, we propose a method called Multi-Scale Massive Points Fast Clustering based on Hierarchical Density Spanning Tree. This study refers to the basic principle of Clustering by Fast Search and Find of Density Peaks aggregation algorithm and introduces the concept of a hierarchical density-based spanning tree, combining the spatial scale with the tree links of elements to propose the corresponding pruning strategy, and finally realizes the fast multi-scale clustering of elements. The first experiment proved the time efficiency of the method in obtaining clustering results by the distance-scale adjustment of parameters. Accurate clustering results were also achieved. The second experiment demonstrated the feasibility of the method at the aggregation point element and showed its visual effect. This provides a further explanation for the application of tree-link structures.<\/jats:p>","DOI":"10.3390\/ijgi12010024","type":"journal-article","created":{"date-parts":[[2023,1,16]],"date-time":"2023-01-16T03:10:34Z","timestamp":1673838634000},"page":"24","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Multi-Scale Massive Points Fast Clustering Based on Hierarchical Density Spanning Tree"],"prefix":"10.3390","volume":"12","author":[{"given":"Song","family":"Chen","sequence":"first","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100830, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fuhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100830, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiran","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Monitoring, Evaluation and Early Warning of Territorial Spatial Planning Implementation, Ministry of Natural Resources, Chongqing 401147, China"},{"name":"School of Earth Sciences and Engineering, Xi\u2019an Shiyou University, Xi\u2019an 710065, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siyi","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Economic and Management, Shanghai University of Sport, 650 Qingyuanhuan Rd, Shanghai 200438, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Agen","family":"Qiu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100830, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shangqin","family":"Liu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100830, China"},{"name":"Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5519-934X","authenticated-orcid":false,"given":"Xizhi","family":"Zhao","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100830, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.trc.2019.01.017","article-title":"Feature extraction and clustering analysis of highway congestion","volume":"100","author":"Nguyen","year":"2019","journal-title":"Transp. 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