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Talks and Poster Presentations (with Proceedings-Entry):

A. Jochem, M. Hollaus, M. Rutzinger, B. Höfle, K. Schadauer, B. Maier:
"Estimation of aboveground biomass using airborne LiDAR data";
Poster: 10th International Conference on LiDAR Applications for Assessing Forest Ecosystems (Silvilaser 2010), Freiburg, Germany; 2010-09-14 - 2010-09-17; in: "Silvilaser 2010", (2010), 9 pages.



English abstract:
In this study a semi-empirical model that was originally developed for stem volume
estimation is used for aboveground biomass (AGB) estimation. The semi-empirical model is
based on the relative heights of first echo LiDAR point cloud data and assumes a linear
relationship between AGB and canopy volume. However, the usage of point cloud data leads
to a computationally demanding task when processing large point cloud datasets for the
generation of area-wide AGB maps. In the presented study the effects of using rasterized
LiDAR data as input for the AGB model are investigated in order to speed up processing and
to make use of the model on large spatial datasets. The canopy volumes are calculated from a
Canopy Height Model (CHM). The optimum resolution of the CHM is determined by
analyzing the effects of varying cell sizes (1.0 m, 1.5 m, 2.0 m, 3.0 m) on the achievable
accuracies. Calibrating the model with rasterized input data having a spatial resolution of
2.0 m instead of using first echo point cloud data leads to a slight increase of the coefficient of
determination (R2 = 0.70 to R2 = 0.72) and a slight decrease of the standard deviation of the
prediction errors. For calibrating the model reference AGB is calculated per sample plot from
local forest inventory data by means of averaged weighted (according to tree species and age
class composition) extension factors. The influence of using rasterized LiDAR input data on
the achievable accuracy of the assessed AGB is investigated for a coniferous dominated study
area in Vorarlberg, Austria.


Electronic version of the publication:
http://publik.tuwien.ac.at/files/PubDat_191757.pdf


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