Publications in Scientific Journals:

A. Jochem, M. Hollaus, M. Rutzinger, B. Höfle:
"Estimation of Aboveground Biomass in Alpine Forests: A Semi-Empirical Approach Considering Canopy Transparency Derived from Airborne LiDAR Data";
Sensors, 11 (2011), 278 - 295.

English abstract:
In this study, a semi-empirical model that was originally developed for stem
volume estimation is used for aboveground biomass (AGB) estimation of a spruce dominated
alpine forest. The reference AGB of the available sample plots is calculated from forest
inventory data by means of biomass expansion factors. Furthermore, the semi-empirical
model is extended by three different canopy transparency parameters derived from airborne
LiDAR data. These parameters have not been considered for stem volume estimation until
now and are introduced in order to investigate the behavior of the model concerning AGB
estimation. The developed additional input parameters are based on the assumption that
transparency of vegetation can bemeasured by determining the penetration of the laser beams
through the canopy. These parameters are calculated for every single point within the 3D
point cloud in order to consider the varying properties of the vegetation in an appropriate way.
Exploratory Data Analysis (EDA) is performed to evaluate the influence of the additional
LiDAR derived canopy transparency parameters for AGB estimation. The study is carried
out in a 560 km2 alpine area in Austria, where reference forest inventory data and LiDAR
Sensors 2011, 11 279
data are available. The investigations show that the introduction of the canopy transparency
parameters does not change the results significantly according to R2 (R2 = 0.70 to R2 = 0.71)
in comparison to the results derived from, the semi-empirical model, which was originally
developed for stem volume estimation.

airborne LiDAR; biomass; semi-empirical model; 3D point cloud; linear regression

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.