RETRIEVING CANOPY CLUMPING INDEX FROM TERRESTRIAL LASER SCANNING DATA

被引：1
作者：
Xu, Yifan [1 ]
Li, Sen [3 ]
Li, Shihua [1 ,2 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Resources & Environm, 2006 Xiyuan Ave, Chengdu 611731, Peoples R China
[2] Univ Elect Sci & Technol China, Yangtze Delta Reg Inst Huzhou, Huzhou 313001, Peoples R China
[3] Hulunbuir Discipline Inspect Comm Communist Party, 189 Hailar St, Hulunbuir, Peoples R China
来源：
2021 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM IGARSS | 2021年
基金：
中国国家自然科学基金;
关键词：
canopy structure; clumping index; terrestrial laser scanning;
D O I：
10.1109/IGARSS47720.2021.9554772
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
The information about tree canopy structure is crucial for better understanding the process of radiation propagation. Clumping index (CI) describes the non-random distribution of foliage in canopy. Terrestrial laser scanning (TLS) has great advantages in obtaining high spatial resolution point cloud. In this paper, a point cloud projection and slicing algorithm was developed to retrieve CI from TLS data. The results were in good consistency with the CI derived from digital hemispherical photography (DHP). The TLS-based CIs had the highest correlation with the DHP-based CIs when the slice size is 0.1 degrees x0.2 degrees.
引用
收藏
页码：6708 / 6711
页数：4
相关论文
共 8 条
[1]   ESTIMATION OF CLUMPING INDEX AND LAI FROM TERRESTRIAL LIDAR DATA [J].
Bao, Yunfei .
2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, :747-750
[2]  
Chen J.Y., 2003, Los Alamos Natl. Lab., Prepr. Arch., P1
[3]   Effects of voxel size and sampling setup on the estimation of forest canopy gap fraction from terrestrial laser scanning data [J].
Cifuentes, Renato ;
Van der Zande, Dimitry ;
Farifteh, Jamshid ;
Salas, Christian ;
Coppin, Pol .
AGRICULTURAL AND FOREST METEOROLOGY, 2014, 194 :230-240
[4]  
GARCIAMIRELES GA, 2015, REMOTE SENS ENVIRON, P78
[5]  
Gonsamo A., 2010, CANADIAN J FOREST RE, P588
[6]  
Lang A. R. G., 2003, AGR FOREST METEOROL, P229
[7]  
Li SH, 2017, INT GEOSCI REMOTE SE, P5790, DOI 10.1109/IGARSS.2017.8128324
[8]  
Nilson T., 2003, AGR METEOROLOGY, P25
1