{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T01:24:36Z","timestamp":1783733076928,"version":"3.55.0"},"reference-count":57,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T00:00:00Z","timestamp":1654819200000},"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":["32192435"],"award-info":[{"award-number":["32192435"]}],"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":["31870533"],"award-info":[{"award-number":["31870533"]}],"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":["CAS-WX2021PY-0108"],"award-info":[{"award-number":["CAS-WX2021PY-0108"]}],"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":["XDA19030204"],"award-info":[{"award-number":["XDA19030204"]}],"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":["LC-1-01"],"award-info":[{"award-number":["LC-1-01"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Application and Demonstration Project of Network Security and Informatization Technology, Chinese Academy of Sciences","award":["32192435"],"award-info":[{"award-number":["32192435"]}]},{"name":"Application and Demonstration Project of Network Security and Informatization Technology, Chinese Academy of Sciences","award":["31870533"],"award-info":[{"award-number":["31870533"]}]},{"name":"Application and Demonstration Project of Network Security and Informatization Technology, Chinese Academy of Sciences","award":["CAS-WX2021PY-0108"],"award-info":[{"award-number":["CAS-WX2021PY-0108"]}]},{"name":"Application and Demonstration Project of Network Security and Informatization Technology, Chinese Academy of Sciences","award":["XDA19030204"],"award-info":[{"award-number":["XDA19030204"]}]},{"name":"Application and Demonstration Project of Network Security and Informatization Technology, Chinese Academy of Sciences","award":["LC-1-01"],"award-info":[{"award-number":["LC-1-01"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["32192435"],"award-info":[{"award-number":["32192435"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["31870533"],"award-info":[{"award-number":["31870533"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["CAS-WX2021PY-0108"],"award-info":[{"award-number":["CAS-WX2021PY-0108"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19030204"],"award-info":[{"award-number":["XDA19030204"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["LC-1-01"],"award-info":[{"award-number":["LC-1-01"]}]},{"name":"National Forestry and Grassland Administration independent RESEARCH and Development Program","award":["32192435"],"award-info":[{"award-number":["32192435"]}]},{"name":"National Forestry and Grassland Administration independent RESEARCH and Development Program","award":["31870533"],"award-info":[{"award-number":["31870533"]}]},{"name":"National Forestry and Grassland Administration independent RESEARCH and Development Program","award":["CAS-WX2021PY-0108"],"award-info":[{"award-number":["CAS-WX2021PY-0108"]}]},{"name":"National Forestry and Grassland Administration independent RESEARCH and Development Program","award":["XDA19030204"],"award-info":[{"award-number":["XDA19030204"]}]},{"name":"National Forestry and Grassland Administration independent RESEARCH and Development Program","award":["LC-1-01"],"award-info":[{"award-number":["LC-1-01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate individual tree segmentation (ITS) is fundamental to forest management and to the studies of forest ecosystem. Unmanned Aerial Vehicle Light Detection and Ranging (UAV-LiDAR) shows advantages for ITS and tree height estimation at stand and landscape scale. However, dense deciduous forests with tightly interlocked tree crowns challenge the performance for ITS. Available LiDAR points through tree crown and appropriate algorithm are expected to attack the problem. In this study, a new UAV-LiDAR dataset that fused leaf-off and leaf-on point cloud (FULD) was introduced to assess the synergetic benefits for ITS and tree height estimation by comparing different types of segmentation algorithms (i.e., watershed segmentation, point cloud segmentation and layer stacking segmentation) in the dense deciduous forests of Northeast China. Field validation was conducted in the four typical stands, including mixed broadleaved forest (MBF), Mongolian oak forest (MOF), mixed broadleaf-conifer forest (MBCF) and larch plantation forest (LPF). The results showed that the combination of FULD and the layer stacking segmentation (LSS) algorithm produced the highest accuracies across all forest types (F-score: 0.70 to 0.85). The FULD also showed a better performance on tree height estimation, with a root mean square error (RMSE) of 1.54 m at individual level. Compared with using the leaf-on dataset solely, the RMSE of tree height estimation was reduced by 0.22 to 0.27 m, and 12.3% more trees were correctly segmented by the FULD, which are mainly contributed by improved detection rate at nearly all DBH levels and by improved detection accuracy at low DBH levels. The improvements are attributed to abundant points from the bole to the treetop of FULD, as well as each layer point being included for segmentation by LSS algorithm. These findings provide useful insights to guide the application of FULD when more multi-temporal LiDAR data are available in future.<\/jats:p>","DOI":"10.3390\/rs14122787","type":"journal-article","created":{"date-parts":[[2022,6,12]],"date-time":"2022-06-12T23:55:24Z","timestamp":1655078124000},"page":"2787","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":62,"title":["Individual Tree Segmentation and Tree Height Estimation Using Leaf-Off and Leaf-On UAV-LiDAR Data in Dense Deciduous Forests"],"prefix":"10.3390","volume":"14","author":[{"given":"Qingda","family":"Chen","sequence":"first","affiliation":[{"name":"Qingyuan Forest CERN, National Observation and Research Station, Shenyang 110016, China"},{"name":"CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2804-4780","authenticated-orcid":false,"given":"Tian","family":"Gao","sequence":"additional","affiliation":[{"name":"Qingyuan Forest CERN, National Observation and Research Station, Shenyang 110016, China"},{"name":"CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaojun","family":"Zhu","sequence":"additional","affiliation":[{"name":"Qingyuan Forest CERN, National Observation and Research Station, Shenyang 110016, China"},{"name":"CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fayun","family":"Wu","sequence":"additional","affiliation":[{"name":"Academy of Inventory and Planning, National Forestry and Grassland Administration, Beijing 100714, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiufen","family":"Li","sequence":"additional","affiliation":[{"name":"Agronomy College, Shenyang Agricultural University, Shenyang 110866, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deliang","family":"Lu","sequence":"additional","affiliation":[{"name":"Qingyuan Forest CERN, National Observation and Research Station, Shenyang 110016, China"},{"name":"CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengyuan","family":"Yu","sequence":"additional","affiliation":[{"name":"Qingyuan Forest CERN, National Observation and Research Station, Shenyang 110016, China"},{"name":"CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4010","DOI":"10.3390\/rs4124010","article-title":"Plant Species Richness is Associated with Canopy Height and Topography in a Neotropical Forest","volume":"4","author":"Wolf","year":"2012","journal-title":"Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.gene.2017.09.040","article-title":"Involvement of Caspase3 in the Acute Stress Response to High Temperature and Elevated Ammonium in Stony Coral Pocillopora Damicornis","volume":"637","author":"Yu","year":"2017","journal-title":"Gene"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1080\/07038992.2019.1612738","article-title":"Ecologically-Based Metrics for Assessing Structure in Developing Area-Based, Enhanced Forest Inventories from LiDAR","volume":"45","author":"Ayrey","year":"2019","journal-title":"Can. 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