A bottom-up approach to segment individual deciduous trees using leaf-off lidar point cloud data

By Xingcheng Lu, Qinghua Guo, Wenkai Li, J. Flanagan. 2014

187 citations recorded by the source corpus.

Subfields: Environmental Engineering, Insect Science, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/146c98f96c4b1783b36b83714a58d9db06e8074d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Lianjun Zhang
2. Zhen Zhen
3. Hans-Gerd Maas
4. A. Bienert
5. Lindi J. Quackenbush
6. Shenglian Guo
7. Vijay P. Singh
8. Shih-Chieh Kao

In Insect Science

1. Zhen Zhen
2. Lianjun Zhang
3. Lindi J. Quackenbush

In Nature and Landscape Conservation

1. Zhen Zhen
2. Lianjun Zhang
3. Hans-Gerd Maas
4. A. Bienert
5. Lindi J. Quackenbush
6. J. Gove
7. M. Mathur

Citations in the corpus

• Trends in Automatic Individual Tree Crown Detection and Delineation - Evolution of LiDAR Data (2016, methodology): “[28] also proposed a bottom-up method based on the intensity and 3D structure of leaf-off LiDAR point data, and found that it was more efficient to extract tree trunks using their bottom-up method than to detect deciduous tree tops using the more common “top-down” method.”
• Comparison and Combination of Mobile and Terrestrial Laser Scanning for Natural Forest Inventories (2018, methodology): “When using ALS, the analysis of the digital crown model is the commonly used approach [26].”