近五年发表的一作和通讯作者的学术论文
1.Yun T, Jiang K, Li G, et al. Individual tree crown segmentation from airborne LiDAR data using a novel Gaussian filter and energy function minimization-based approach [J]. Remote Sensing of Environment, 2021, 256: 112307. (中科院一区,测绘学排名一)(高被引)
2.Yun T, Cao L, An F, et al. Simulation of multi-platform LiDAR for assessing total leaf area in tree crowns [J]. Agricultural and Forest Meteorology, 2019, 276: 107610. (中科院一区)
3.Xue X.B., Yun T*. Shortwave radiation calculation for forest plots using airborne LiDAR data and computer graphics, Plant phenomics. Volume 2022.(指导硕士生)(中科院一区)
4.Zhang B., Yun T*. Simulating Wind Disturbances over Rubber Trees with Phenotypic Trait Analysis Using Terrestrial Laser Scanning, Forests. 2022 (指导本科生)
5.丁竹娴,云挺*.基于深度学习与激光点云的橡胶林枝干重建及参数反演[J].农业工程学报, 2022, 38(08):187-199.(中国期刊卓越计划)(指导本科生)
6.Chen, X., Yun, T*. Individual Tree Crown Segmentation Directly from UAV-Borne LiDAR Data Using the PointNet of Deep Learning [J], Forests, 2021. 12(2): 131. (指导硕士生)(高被引)
7.Sun C, Yun T*, Individual Tree Crown Segmentation and Crown Width Extraction From a Heightmap Derived From Aerial Laser Scanning Data Using a Deep Learning Framework. Front. Plant Sci. 2022. 13:914974.(指导本科生)(中科院二区)
8.Zhou Y, Yun, T*. Individual tree crown segmentation based on aerial image using superpixel and topological features [J]. Journal of Applied Remote Sensing, 2020, 14(2): 022210. (指导硕士生)
9.Huang Z, Yun, T*. Retrieval of aerodynamic parameters in rubber tree orest based on the computer simulation technique and terrestrial laser scanning data [J]. Remote Sensing, 2020, 12(8): 1318. (指导硕士生) (中科院二区)
10.Yun T, Jiang K, Hou H, An F, Chen B, Jiang A, Li W, Xue L. Rubber Tree Crown Segmentation and Property Retrieval Using Ground-Based Mobile LiDAR after Natural Disturbances. Remote Sensing. 2019; 11(8):903. (中科院二区)
11.Wang, J, Yun, T*, “Individual Rubber Tree Segmentation Based on Ground-Based LiDAR Data and Faster R-CNN of Deep Learning [J],” Forests. 2019, 10(9): 793 (指导本科生)
12.Xu, Q.F., Yun, T*. "Extraction of Leaf Biophysical Attributes Based on a Computer Graphic-based Algorithm Using Terrestrial Laser Scanning Data [J]." Remote Sensing. 2019 11(1), 15. (指导硕士生)(中科院二区)
13.Yun T, An F, Li W, et al. A novel approach for retrieving tree leaf area from ground-based LiDAR [J]. Remote Sensing, 2016, 8(11): 942. (中科院二区)
14.Xu, S., Yun, T*. Separation of Wood and Foliage for Trees from Ground Point Clouds using a Novel Least-cost Path Model [J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021, 14: 6414.
15.Yun, T., et al., Using point cloud data for tree organ classification and real leaf surface construction, Bulgarian Chemical Communications. 49(1), 2017.
16.Yun, T., Study of Subtropical Forestry Index Retrieval Using Terrestrial Laser Scanning and Hemispherical Photography, Mathematical Problems in Engineering. 2015.
17.Yun, T., et al., Leaf model reconstruction and mechanical deformation based on laser point cloud, International Journal Bioautomation, 11(10), 5600-5608, 2014.
18.Yun, T., Semi-supervised Ultrasound Image Segmentation Based on Direction Energy and Texture Intensity, Appl. Math. Inf. 6(3), 737-743, Sep 2012.
19.陈帮乾,云挺,安锋,寇卫利,李海亮,罗红霞,杨川,王琴飞,孙瑞,吴志祥.基于Landsat和Sentinel-2时间序列影像的海南西部橡胶林龙卷风灾情评估[J].遥感学报,2021,25(03):816-829.
20.黄笑,云挺*,薛联凤,胡春华,陈帮乾.基于流体运动仿真的不同林冠形状抗风强度分析[J].南京林业大学学报(自然科学版),2019,43(02):107-113.
21.云挺,张艳侠,王佳敏,薛联凤.基于移动激光扫描的橡胶林风害相关参数精准反演[J].光谱学与光谱分析,2018,38(11):3452-3463.SCI.
22.卢晓艺,云挺,薛联凤,徐强法,曹林.基于树木激光点云的有效特征抽取与识别方法[J].中国激光,2019,46(05):411-422.EI.
23.陈向宇,云挺,薛联凤,刘应安.基于激光雷达点云数据的树种分类[J].激光与光电子学进展,2019,56(12):203-214.
近五年授权部分专利
1.云挺,(1/3). A method of Individual tree crown segmentation from airborne LiDAR data using a novel Gaussian filter and energy function minimization.PCT international application. Submission number:364931, application number: CN2020/119150. 国际PCT专利
2.云挺,(1/6).Leaf surface reconstruction and physically based deformation simulation based on the point cloud data. Patent number: 2020103131,Innovation patent of Australian. 澳大利亚发明
3.云挺,(1/3). 基于超像素与拓扑特性的航拍图像单株树冠分割算法[P]. 申请日 2020.3, 专利号ZL202010218236.8, 授权公告日2023.7, 授权公告号CN111340826B。(发明专利)
4.云挺,(1/4). 面向机载激光点云的倒水蔓延与能量函数控制的单株树冠分割方法[P]. 申请日2019.7, 专利号ZL201910632238.9, 授权公告日2023.6, 授权公告号CN110598707B。(发明专利)
5.云挺,(1/4). 基于Faster R-CNN的面向激光点云的单木分割方法[P]. 申请日 2019.6, 专利号ZL201910551190.9, 授权公告日2023.6, 授权公告号CN110378909B。(发明专利)
6.云挺,(1/4). 一种基于激光点云的活立木叶属性精准估测方法[P]. 申请日 2019.2, 专利号ZL201910130528.3, 授权公告日2023.4, 授权公告号CN109961470B。(发明专利)
7.云挺,(1/5). 基于激光点云与空气动力学的活立木抗风性能分析方法[P]. 申请日 2018.11, 专利号ZL201811322277.0, 授权公告日2022.12, 授权公告号CN109446691B。(发明专利)
8.云挺,(1/4).一种面向树木激光点云的有效特征抽取与树种识别方法.申请日 2018.10,专利号ZL201811263570.4, 授权公告日2021.9,授权公告号CN109446986B, (发明专利)
9.云挺,(1/4).一种基于激光雷达点云数据的树种分类方法.申请日 2018.10,专利号ZL201811263568.7,授权公告日2021.8,授权公告号CN109409429B, (发明专利)
10.云挺,(1/4). 激光点云中林木参数评估方法[P].申请日 2017.10,专利号ZL201710955957.5, 授权公告日2020.10,授权公告号CN107705309B, (发明专利)
11.云挺,(1/3). 一种基于激光点云数据的真实阔叶树器官分类识别方法[P].申请日 2014.8, 专利号ZL201410436294.2, 授权公告日2019.4, 授权公告号CN105373814B。(发明专利)
12.云挺,(2/3). 面向激光点云数据的阔叶树真实叶片建模与形变方法[P]. 申请日 2014.9, 专利号ZL201410436293.8,批准年份2019.1, 授权公告号CN105654543B, (发明专利)
13.云挺,(1/3). 基于激光扫描数据的树木冠层叶面积计算方法[P]. 申请日 2016.5, 专利号ZL201610350345.9, 授权公告日2018.8, 授权公告号CN105806266B。(发明专利)