{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T11:37:44Z","timestamp":1763552264985,"version":"build-2065373602"},"reference-count":63,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,8]],"date-time":"2023-06-08T00:00:00Z","timestamp":1686182400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"R&amp;D Program of Beijing Municipal Education Commission","award":["KZ202210028045","05-Y30B01-9001-19\/20"],"award-info":[{"award-number":["KZ202210028045","05-Y30B01-9001-19\/20"]}]},{"name":"Special Project of High-Resolution Earth Observation System (HREOS)","award":["KZ202210028045","05-Y30B01-9001-19\/20"],"award-info":[{"award-number":["KZ202210028045","05-Y30B01-9001-19\/20"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate diameter at breast height (DBH) and tree height (H) information can be acquired through terrestrial laser scanning (TLS) and airborne LiDAR scanner (ALS) point cloud, respectively. To utilize these two features simultaneously but avoid the difficulties of point cloud fusion, such as technical complexity and time-consuming and laborious efforts, a feature-level point cloud fusion method (FFATTe) is proposed in this paper. Firstly, the TLS and ALS point cloud data in a plot are georeferenced by differential global navigation and positioning system (DGNSS) technology. Secondly, point cloud processing and feature extraction are performed for the georeferenced TLS and ALS to form feature datasets, respectively. Thirdly, the feature-level fusion of LiDAR data from different data sources is realized through spatial join according to the tree trunk location obtained from TLS and ALS, that is, the tally can be implemented at a plot. Finally, the individual tree parameters are optimized based on the tally results and fed into the binary volume model to estimate the total volume (TVS) in a large area (whole study area). The results show that the georeferenced ALS and TLS point cloud data using DGNSS RTK\/PPK technology can achieve coarse registration (mean distance \u2248 40 cm), which meets the accuracy requirements for feature-level point cloud fusion. By feature-level fusion of the two point cloud data, the tally can be achieved quickly and accurately in the plot. The proposed FFATTe method achieves high accuracy (with error of 3.09%) due to its advantages of combining different LiDAR data from different sources in a simple way, and it has strong operability when acquiring TVS over large areas.<\/jats:p>","DOI":"10.3390\/rs15122995","type":"journal-article","created":{"date-parts":[[2023,6,9]],"date-time":"2023-06-09T01:32:34Z","timestamp":1686274354000},"page":"2995","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A Feature-Level Point Cloud Fusion Method for Timber Volume of Forest Stands Estimation"],"prefix":"10.3390","volume":"15","author":[{"given":"Lijie","family":"Guo","sequence":"first","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China"},{"name":"Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0939-3288","authenticated-orcid":false,"given":"Yanjie","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China"},{"name":"Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4574-7381","authenticated-orcid":false,"given":"Lei","family":"Deng","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"},{"name":"Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China"},{"name":"Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China"}]},{"given":"Peng","family":"Hou","sequence":"additional","affiliation":[{"name":"Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5272-1158","authenticated-orcid":false,"given":"Jun","family":"Zhai","sequence":"additional","affiliation":[{"name":"Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment, Beijing 100094, China"}]},{"given":"Yan","family":"Chen","sequence":"additional","affiliation":[{"name":"Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment, Beijing 100094, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1016\/j.rse.2016.10.023","article-title":"Quantification of hidden canopy volume of airborne laser scanning data using a voxel traversal algorithm","volume":"194","author":"Schneider","year":"2017","journal-title":"Remote Sens. 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