Towards accurate individual tree parameters estimation in dense forest: optimized coarse-to-fine algorithms for registering UAV and terrestrial LiDAR data

Yuting Zhaoa Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin, P.R. ChinaView further author information

Jungho Imb Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan, South KoreaView further author information

Zhen Zhena Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin, P.R. ChinaCorrespondence[email protected]

https://orcid.org/0000-0001-9281-4260 View further author information

Yinghui Zhaoa Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin, P.R. ChinaCorrespondence[email protected]
View further author information

Towards accurate individual tree parameters estimation in dense forest: optimized coarse-to-fine algorithms for registering UAV and terrestrial LiDAR data

Supplemental Material

Information for

Open access

Opportunities

Help and information

Your download is now in progress and you may close this window

Login or register to access this feature

Towards accurate individual tree parameters estimation in dense forest: optimized coarse-to-fine algorithms for registering UAV and terrestrial LiDAR data

Supplemental Material

Related research

To cite this article:

Download citation

Information for

Open access

Opportunities

Help and information

Keep up to date