{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T14:12:02Z","timestamp":1771683122000,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T00:00:00Z","timestamp":1632096000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2019M661858"],"award-info":[{"award-number":["2019M661858"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41801325"],"award-info":[{"award-number":["41801325"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41861052"],"award-info":[{"award-number":["41861052"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004479","name":"Natural Science Foundation of Jiangxi Province","doi-asserted-by":"publisher","award":["20192BAB217010"],"award-info":[{"award-number":["20192BAB217010"]}],"id":[{"id":"10.13039\/501100004479","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009102","name":"Education Department of Jiangxi Province","doi-asserted-by":"publisher","award":["GJJ170449"],"award-info":[{"award-number":["GJJ170449"]}],"id":[{"id":"10.13039\/501100009102","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Laboratory for Digital Land and Resources of Jiangxi Province","award":["DLLJ201806"],"award-info":[{"award-number":["DLLJ201806"]}]},{"name":"East China University of Technology Ph. D. Project","award":["DHBK2017155"],"award-info":[{"award-number":["DHBK2017155"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Building extraction from airborne Light Detection and Ranging (LiDAR) point clouds is a significant step in the process of digital urban construction. Although the existing building extraction methods perform well in simple urban environments, when encountering complicated city environments with irregular building shapes or varying building sizes, these methods cannot achieve satisfactory building extraction results. To address these challenges, a building extraction method from airborne LiDAR data based on multi-constraints graph segmentation was proposed in this paper. The proposed method mainly converted point-based building extraction into object-based building extraction through multi-constraints graph segmentation. The initial extracted building points were derived according to the spatial geometric features of different object primitives. Finally, a multi-scale progressive growth optimization method was proposed to recover some omitted building points and improve the completeness of building extraction. The proposed method was tested and validated using three datasets provided by the International Society for Photogrammetry and Remote Sensing (ISPRS). Experimental results show that the proposed method can achieve the best building extraction results. It was also found that no matter the average quality or the average F1 score, the proposed method outperformed ten other investigated building extraction methods.<\/jats:p>","DOI":"10.3390\/rs13183766","type":"journal-article","created":{"date-parts":[[2021,9,21]],"date-time":"2021-09-21T22:35:20Z","timestamp":1632263720000},"page":"3766","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Building Extraction from Airborne LiDAR Data Based on Multi-Constraints Graph Segmentation"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1377-2558","authenticated-orcid":false,"given":"Zhenyang","family":"Hui","sequence":"first","affiliation":[{"name":"Faculty of Geomatics, East China University of Technology, Nanchang 330013, China"}]},{"given":"Zhuoxuan","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Geomatics, East China University of Technology, Nanchang 330013, China"}]},{"given":"Penggen","family":"Cheng","sequence":"additional","affiliation":[{"name":"Faculty of Geomatics, East China University of Technology, Nanchang 330013, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9940-1845","authenticated-orcid":false,"given":"Yao Yevenyo","family":"Ziggah","sequence":"additional","affiliation":[{"name":"Faculty of Geosciences and Environmental Studies, University of Mines and Technology, Tarkwa 999064, Ghana"}]},{"given":"JunLin","family":"Fan","sequence":"additional","affiliation":[{"name":"Jiangxi Nuclear industry Surveying and Mapping Institute Group Co., Ltd., Nanchang 330038, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.isprsjprs.2017.06.005","article-title":"Automatic building extraction from LiDAR data fusion of point and grid-based features","volume":"130","author":"Du","year":"2017","journal-title":"ISPRS J. 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