An automated approach for wood-leaf separation from terrestrial LIDAR point clouds using the density based clustering algorithm DBSCAN-Reference-Cited by-同舟云学术

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An automated approach for wood-leaf separation from terrestrial LIDAR point clouds using the density based clustering algorithm DBSCAN

Published:2018-11 Issue: Volume:262 Page:434-444
ISSN:0168-1923
Container-title:Agricultural and Forest Meteorology
language:en
Short-container-title:Agricultural and Forest Meteorology

Author:

Ferrara Roberto,Virdis Salvatore G.P.,Ventura Andrea,Ghisu Tiziano,Duce Pierpaolo,Pellizzaro Grazia

Publisher

Elsevier BV

Subject

Atmospheric Science,Agronomy and Crop Science,Global and Planetary Change,Forestry

Reference73 articles.

1. DBStrata: a system for density-based clustering and outlier detection based on stratification;Aliotta,2011

2. On seeing the wood from the leaves and the role of voxel size in determining leaf area distribution of forests with terrestrial LiDAR;Béland;Agric. Forest Meteorol.,2014

3. A model for deriving voxel-level tree leaf area density estimates from ground-based LiDAR;Béland;Environ. Modell. Softw.,2014

4. Estimating leaf area distribution in savanna trees from terrestrial LiDAR measurements;Béland;Agric. Forest Meteorol.,2011

5. Characterizing performance of environmental models;Bennett;Environ. Modell. Softw.,2013

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