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A comparison of different methods for forest resource
ORIGINAL PAPER
A comparison of different methods for forest resource
estimation using information from airborne laser scanning
and CIR orthophotos
Christoph Straub ? Holger Weinacker ?
Barbara Koch
Received: 26 March 2009 / Revised: 26 March 2010 / Accepted: 16 April 2010 / Published online: 26 May 2010
Springer-Verlag 2010
Abstract This article compares three methods for forest
resource estimation based on remote sensing features
extracted from Airborne laser scanning and CIR ortho-
photos. The estimation was made exemplarily for the total
stem volume of trees for a given area, measured in cubic
metres per hectare [m3 ha-1] (as one of the most important
quantitative parameters to characterise a forest stand). The
following methods were compared: Regression Analysis
(RA), k-NN (nearest neighbour) method and a method that
utilises regional yield tables, referred to as the yield table
method (YT-method). The estimation of stem volume was
examined in a mixed forest in Southern Germany using 300
circular inventory plots, each with a size of 452 m2.
Remote sensing features relating to vegetation height and
structures were extracted and used as input variables in the
different approaches. The accuracy of the estimation was
analysed using scatter plots and quantified using absolute and
relative root mean square errors (RMSE). The comparison
was made for all plots, as well as for averaged plot values
located within forest stands that have the same age class. On
‘‘plot level’’ the RMSE yielded 79.79 m3 ha-1 (RA), 81.93
m3 ha-1 (k-NN) and 81.78 m3 ha-1 (YT-method) and for the
averaged values 35.75 m3 ha-1 (RA), 35.06 m3 ha-1 (k-NN)
and 42.98 m3 ha-1 (YT-method). Advantages and disad-
vantages, as well as requirements, of the methods are
discussed.
Keywords Forest inventory Airborne laser scanning
Orthophotos Regression analysis k-NN method
Yield tables
Introduction
Forest inventories assess the quantity and quality of forest
resources and are the bases for forest
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