A scalable approach for tree segmentation within small-footprint airborne LiDAR data

@article{Hamraz2017ASA,
  title={A scalable approach for tree segmentation within small-footprint airborne LiDAR data},
  author={Hamid Hamraz and Marco A. Contreras and Jun Zhang},
  journal={ArXiv},
  year={2017},
  volume={abs/1701.00180}
}

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References

SHOWING 1-10 OF 54 REFERENCES

A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data

A New Method for Segmenting Individual Trees from the Lidar Point Cloud

Light Detection and Ranging (lidar) has been widely applied to characterize the 3-dimensional (3D) structure of forests as it can generate 3Dpoint data with high spatial resolution and accuracy.

Detection of individual tree crowns in airborne lidar data

Laser scanning provides a good means to collect information on forest stands. This paper presents an approach to delineate single trees automatically in small footprint light detection and ranging

Isolating individual trees in a savanna woodland using small footprint lidar data

This study presents a new method of detecting individual treetops from lidar data and applies marker-controlled watershed segmentation into isolating individual trees in savanna woodland. The

PTrees: A point-based approach to forest tree extraction from lidar data

A Lidar Point Cloud Based Procedure for Vertical Canopy Structure Analysis And 3D Single Tree Modelling in Forest

A procedure for both vertical canopy structure analysis and 3D single tree modelling based on Lidar point cloud is presented in this paper, and important parameters such as crown height range, crown volume and crown contours at the different height levels can be derived.

Improving the efficiency and accuracy of individual tree crown delineation from high-density LiDAR data

Algorithm for Extracting Digital Terrain Models under Forest Canopy from Airborne LiDAR Data

The algorithm presented in this paper is more tolerant to low data density compared to the other two algorithms and shows that with decreasing point density, the differences between the three algorithms dramatically increased from about 0.5m to over 10m.
...