Applying quantitative structure models to plot-based terrestrial laser data to assess dendrometric parameters in dense mixed forests

Jan Hackenberg,Ugo Chiavetta,Chiara Torresan

doi:10.5424/fs/2018271-12658

Jan Hackenberg, Ugo Chiavetta + Show 1 more

Open Access

https://doi.org/10.5424/fs/2018271-12658

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Abstract

Aim of study: To assess terrestrial laser scanning (TLS) accuracy in estimating biometrical forest parameters at plot-based level in order to replace manual survey for forest inventory purposes.Area of study: Monte Morello, Tuscany region, ItalyMaterial and methods: In 14 plots (10 m radius) in dense Mediterranean mixed conifer forests, diameter at breast height (DBH) and height were measured in Summer 2016. Tree volume was computed using the second Italian National Forest Inventory (INFC II) equations. TLS data were acquired in the same plots and quantitative structure models (QSMs) were applied to TLS data to compute dendrometric parameters. Tree parameters measured in field survey, i.e. DBH, height, and computed volume, were compared to those resulting from TLS data processing. The effect of distance from the plot boundary in the accuracy of DBH, height and volume estimation from TLS data was tested.Main results: TLS-derived DBH showed a good correlation with the traditional forest inventory data (R2=0.98, RRMSE=7.81%), while tree height was less correlated with the traditional forest inventory data (R2=0.60, RRMSE=16.99%). Poor agreement was observed when comparing the volume from TLS data with volume estimated from the INFC II prediction equations.Research highlights: The study demonstrated that the application of QSM to plot-based terrestrial laser data generates errors in plots with high density of coniferous trees. A buffer zone of 5 m would help reduce the error of 35% and 42% respectively in height estimation for all trees and in volume estimation for broadleaved trees.

Highlights

Terrestrial laser scanning (TLS), known as ground-based Light Detection and Ranging (LiDAR), is an active remote sensing technique that acquires dense 3D point clouds from object surfaces using laser scanner
A sample of plots differentiated in terms of structural and specific characteristics provides a good chance to represent local considerations and determine whether the rate of detection is eventually influenced by those aspects
The application of quantitative structure models (QSMs) in TLS data allowed for the extraction of single trees and the assessment of tree variables at plot level in mixed forests

Summary

Introduction

Terrestrial laser scanning (TLS), known as ground-based Light Detection and Ranging (LiDAR), is an active remote sensing technique that acquires dense 3D point clouds from object surfaces using laser scanner. The emphasis shifted to evaluating the capability of TLS to estimate stem and branch volume (Holopainen et al, 2011; Dassot et al, 2012), and biomass (Calders et al, 2015; Ishak et al, 2015; Rahman et al, 2017) and important forest attributes not directly measured in conventional forest inventories, such as the volume of parts of trunk with certain radii and the branches of certain size (Raumonen et al, 2013; Hackenberg et al, 2015a) These later studies demonstrated that the precision of volume predictions from TLS were similar to those of predictions from allometric models

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