{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T11:31:34Z","timestamp":1760441494095,"version":"build-2065373602"},"reference-count":20,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2018,5,29]],"date-time":"2018-05-29T00:00:00Z","timestamp":1527552000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2016YFF0201305"],"award-info":[{"award-number":["2016YFF0201305"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Agglomeration operations are a core component of the automated generalization of aggregated area groups. However, because geographical elements that possess agglomeration features are relatively scarce, the current literature has not given sufficient attention to agglomeration operations. Furthermore, most reports on the subject are limited to the general conceptual level. Consequently, current agglomeration methods are highly reliant on subjective determinations and cannot support intelligent computer processing. This paper proposes an automated processing method for agglomeration areas. Firstly, the proposed method automatically identifies agglomeration areas based on the width of the striped bridging area, distribution pattern index (DPI), shape similarity index (SSI), and overlap index (OI). Next, the progressive agglomeration operation is carried out, including the computation of the external boundary outlines and the extraction of agglomeration lines. The effectiveness and rationality of the proposed method has been validated by using actual census data of Chinese geographical conditions in the Jiangsu Province.<\/jats:p>","DOI":"10.3390\/ijgi7060204","type":"journal-article","created":{"date-parts":[[2018,5,30]],"date-time":"2018-05-30T03:04:27Z","timestamp":1527649467000},"page":"204","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["An Automated Processing Method for Agglomeration Areas"],"prefix":"10.3390","volume":"7","author":[{"given":"Chengming","family":"Li","sequence":"first","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100830, China"},{"name":"College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Yin","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100830, China"},{"name":"College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoli","family":"Liu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100830, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengda","family":"Wu","sequence":"additional","affiliation":[{"name":"Chinese Academy of Surveying and Mapping, Beijing 100830, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1871","DOI":"10.1080\/13658810903401008","article-title":"Area aggregation in map generalisation by mixed-integer programming","volume":"24","author":"Haunert","year":"2010","journal-title":"Int. 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