Effects of pulse density on predicting characteristics of individual trees of Scandinavian commercial species using alpha shape metrics based on airborne laser scanning data

By Jari Vauhkonen, Timo Tokola, Matti Maltamo, Petteri Packalen. 2008

63 citations recorded by the source corpus.

Subfields: Environmental Engineering, Geology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/65aac59590ba2af108a85341a72c897bb5ad774b

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In Environmental Engineering

In Geology

In Nature and Landscape Conservation

Citations in the corpus

Trends in Automatic Individual Tree Crown Detection and Delineation - Evolution of LiDAR Data (2016, methodology): “[85–88] applied the alpha shape technique to select tree objects for predicting a range of parameters including crown base height, species and crown volume, and found that the approach is sensitive to the applied point density.”
Estimation of tree crown volume from airborne lidar data using computational geometry (2013, methodology): “Techniques based on for example, the use of voxels (Popescu and Zhao 2008), alpha shapes (Vauhkonen et al. 2008), and level set functions (Tang, Dong, and Buckles 2013) have been proposed for this purpose.”
Predicting Tree Attributes and Quality Characteristics of Scots Pine Using Airborne Laser Scanning Data (2009, methodology): “Vauhkonen et al. (2008) employed the alpha shape concept, a computational geometry technique introduced by Edelsbrunner and Mücke (1994), to construct tree crown approximations from ALS point clouds.”
Non-parametric prediction of diameter distributions using airborne laser scanner data (2009, background): “However, boreal conifer tree species can also be separated using high pulse density ALS data (Holmgren & Persson, 2004; Vauhkonen et al., 2008).”
Estimation of stem attributes using a combination of terrestrial and airborne laser scanning (2012, methodology): “Previous studies have achieved slightly higher accuracy for estimation of tree level DBH, tree height, and stem volume from ALS data (e.g., Persson et al. 2002; Solberg et al. 2006; Vauhkonen et al. 2008, 2010).”
High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision (2013, background): “, 2011), and for individual tree extraction by species (Falkowski et al., 2008; Vauhkonen et al., 2008) among many other scientific and management applications.”
Comparing individual tree detection and the area-based statistical approach for the retrieval of forest stand characteristics using airborne laser scanning in Scots pine stands (2011, methodology): “In the Nordic countries, for example, ITD requires approximately 3 pulses/m2 for predicting tree characteristics (Vauhkonen et al. 2008), but typically 5 to 10 pulses/m2 for delineating trees (Hyyppä and Inkinen 1999; Persson et al.”