A Novel Framework to Automatically Fuse Multiplatform LiDAR Data in Forest Environments Based on Tree Locations
文献类型：期刊论文
| 作者 | Guan, Hongcan5; Su, Yanjun5; Hu, Tianyu5; Wang, Rui5; Ma, Qin2,5; Yang, Qiuli5; Sun, Xiliang5; Li, Yumei5; Jin, Shichao5; Zhang, Jing5 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2020 |
| 卷号 | 58期号:3页码:2165-2177 |
| 关键词 | Vegetation Laser radar Forestry Tin Three-dimensional displays Unmanned aerial vehicles Registers Forest multiplatform light detection and ranging (LiDAR) registration tree location |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2019.2953654 |
| 文献子类 | Article |
| 英文摘要 | The emerging near-surface light detection and ranging (LiDAR) platforms [e.g., terrestrial, backpack, mobile, and unmanned aerial vehicle (UAV)] have shown great potential for forest inventory. However, different LiDAR platforms have limitations either in data coverage or in capturing undercanopy information. The fusion of multiplatform LiDAR data is a potential solution to this problem. Because of the complexity and irregularity of forests and the inaccurate positioning information under forest canopies, current multiplatform data fusion still involves substantial manual efforts. In this article, we proposed an automatic multiplatform LiDAR data registration framework based on the assumption that each forest has a unique tree distribution pattern. Five steps are included in the proposed framework, i.e., individual tree segmentation, triangulated irregular network (TIN) generation, TIN matching, coarse registration, and fine registration. TIN matching, as the essential step to find the corresponding tree pairs from multiplatform LiDAR data, uses a voting strategy based on the similarity of triangles composed of individual tree locations. The proposed framework was validated by fusing backpack and UAV LiDAR data and fusing multiscan terrestrial LiDAR data in coniferous forests. The results showed that both registration experiments could reach a satisfying data registration accuracy (horizontal root-mean-square error (RMSE) < 30 cm and vertical RMSE < 20 cm). Moreover, the proposed framework was insensitive to individual tree segmentation errors, when the individual tree segmentation accuracy was higher than 80%. We believe that the proposed framework has the potential to increase the efficiency of accurately registering multiplatform LiDAR data in forest environments. |
| 学科主题 | Geochemistry & Geophysics ; Engineering, Electrical & Electronic ; Remote Sensing ; Imaging Science & Photographic Technology |
| 出版地 | PISCATAWAY |
| 电子版国际标准刊号 | 1558-0644 |
| WOS关键词 | TERRESTRIAL LASER SCANS ; POINT CLOUD REGISTRATION ; AIRBORNE LIDAR ; INDIVIDUAL TREES ; SEGMENTATION ; ALGORITHM ; BIOMASS ; SURFACE ; MODELS ; CROWNS |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000519598700051 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Program of China [2016YFC0500202] ; Key Research Program of the Chinese Academy of Science [KFZD-SW-319-06] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41871332, 0011107] ; CAS Pioneer Hundred Talents Program |
| 源URL | [http://ir.ibcas.ac.cn/handle/2S10CLM1/21861]  |
| 专题 | 植被与环境变化国家重点实验室 |
| 作者单位 | 1.Mississippi State Univ, Dept Forestry, Mississippi State, MS 39762 USA 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Natl Forestry & Grassland Adm, Acad Inventory & Planning, Beijing 100714, Peoples R China 4.Natl Forestry & Grassland Adm, China Natl Forestry Econ & Dev Res Ctr, Beijing 100714, Peoples R China 5.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China |
| 推荐引用方式 GB/T 7714 | Guan, Hongcan,Su, Yanjun,Hu, Tianyu,et al. A Novel Framework to Automatically Fuse Multiplatform LiDAR Data in Forest Environments Based on Tree Locations[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2020,58(3):2165-2177. |
| APA | Guan, Hongcan.,Su, Yanjun.,Hu, Tianyu.,Wang, Rui.,Ma, Qin.,...&Guo, Qinghua.(2020).A Novel Framework to Automatically Fuse Multiplatform LiDAR Data in Forest Environments Based on Tree Locations.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,58(3),2165-2177. |
| MLA | Guan, Hongcan,et al."A Novel Framework to Automatically Fuse Multiplatform LiDAR Data in Forest Environments Based on Tree Locations".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 58.3(2020):2165-2177. |
入库方式： OAI收割
来源：植物研究所
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