{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T08:38:01Z","timestamp":1775723881282,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,11]],"date-time":"2021-01-11T00:00:00Z","timestamp":1610323200000},"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\/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>Individual tree extraction is an important process for forest resource surveying and monitoring. To obtain more accurate individual tree extraction results, this paper proposed an individual tree extraction method based on transfer learning and Gaussian mixture model separation. In this study, transfer learning is first adopted in classifying trunk points, which can be used as clustering centers for tree initial segmentation. Subsequently, principal component analysis (PCA) transformation and kernel density estimation are proposed to determine the number of mixed components in the initial segmentation. Based on the number of mixed components, the Gaussian mixture model separation is proposed to separate canopies for each individual tree. Finally, the trunk stems corresponding to each canopy are extracted based on the vertical continuity principle. Six tree plots with different forest environments were used to test the performance of the proposed method. Experimental results show that the proposed method can achieve 87.68% average correctness, which is much higher than that of other two classical methods. In terms of completeness and mean accuracy, the proposed method also outperforms the other two methods.<\/jats:p>","DOI":"10.3390\/rs13020223","type":"journal-article","created":{"date-parts":[[2021,1,11]],"date-time":"2021-01-11T11:36:11Z","timestamp":1610364971000},"page":"223","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Individual Tree Extraction from Terrestrial LiDAR Point Clouds Based on Transfer Learning and Gaussian Mixture Model Separation"],"prefix":"10.3390","volume":"13","author":[{"given":"Zhenyang","family":"Hui","sequence":"first","affiliation":[{"name":"Faculty of Geomatics, East China University of Technology, Nanchang 330013, China"},{"name":"School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5108-4828","authenticated-orcid":false,"given":"Shuanggen","family":"Jin","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China"}]},{"given":"Dajun","family":"Li","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 Mineral Resources Technology, University of Mines and Technology, Tarkwa 999064, Ghana"}]},{"given":"Bo","family":"Liu","sequence":"additional","affiliation":[{"name":"Faculty of Geomatics, East China University of Technology, Nanchang 330013, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,11]]},"reference":[{"key":"ref_1","unstructured":"Shan, J., and Toth, C.K. 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