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Title
Remote sensing for resources development and environmental management
Author
Damen, M. C. J.

469
Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986
Experiences in application of multispectral scanner-data
for forest damage inventory
A.Kadro & S.Kuntz
Department of Photointerpretation and Remote Sensing, University of Freiburg, FR Germany
ABSTRACT: For testing the potential use of multispectral scanner data for the inventory of forest damages in
large areas five test sites in South-west Germany were sensed at three flight altitudes with an 11-channel
scanner. At the same time, ground truth information in these test sites were obtained and the actual state
of the forest stands was documented with color infrared (CIR) aerial photographs. The test sites differ in
morphology, forest types and degree of the actual forest damage.The acquired data were evaluated with a com
puter aided supervised classification using the maximum-1ikehood method. For verification of the classification
results for both single trees and stands, the terrestrial ground truth and the CIR-photographs were used.
This paper presents the classification results and discusses the problems of a computer aided forest damage
inventory/.
1 INTRODUCTION
Since the late 1970's a regional decline affecting
many tree species has occured in Europe. The urgent
need for detailed information about the actual si
tuation of the forests in Germany are of vital in
terest for both government and forest departments.
So aerial and ground survey methods have been used
to get this information.
But for large areas these methods are time-consuming
and expensive. So in 1983 a project started at the
Department of Photointerpretation and Remote Sen
sing, University of Freiburg, to evaluate multispec
tral scanner data for forest damage inventory. For
this purpose data were collected in July 1984 and
August 1985 on 5 test areas in South-west Germany
with a Bendix-M2S-Scanner flown by the DFVLR Ober
pfaffenhofen. This scanner was modified (Table 1 )
by the DFVLR to simulate the Thematic Mapper in Land-
sat 5 (Table 2). The data were collected at altitudes
of 300 m, 1000 m and 3000 m. A Landsat 5 image from
nearly the same time, recording the same areas was
also evaluated.
Table 1. Spectral channels and wavelengths of the
modified Bendix -Scanner
median
range
median
range
channel
Ann*
channel A tun
3
515
50
9
720
40
4
560
40
10
1015
90
5
600
40
5TM
1650
200
6
640
40
7TM
2210
270
7
680
40
11
11000
6000
8
720
40
Table
2. Spectral channels and
wavelengths of Land-
sat 5
(TM)
median
range
median
range
channel Ann»
Alum
channel
A H»m
Alnm
1
485
70
5
1650
200
2
560
80
6
11450
2100
3
660
60
7
2215
270
4
830
140
the different altitudes have the following ground
resolution (pixel size):
at 300 m altitude
at 1000 m "
at 3000 m "
at 705 km "
0,75 X 0,75 m
2.5 X 2,5 m
7.5 X 7,5 m
30 X 30 m
(aircraft MSS)
If
(Landsat 5)
Fran the 300 m altitude pixels numbering up to 100
represent one single tree crown. Fran 1000 m and
3000 m one can evaluate only groups of trees or
stands and from Landsat images only large stands
can be evaluated.
The test site iron which results will be presented
is mountainous and contains mostly coniferous trees
(spruce mixed with fir) and some smaller stands of
deciduous trees (mostly beech). The main interest in
this project was focused on coniferous trees because
they are of major interest in german forestry al
though in a continuing project deciduos species also
will be investigated.
The computer aided classification of different damage
classes is based on the differences in reflection of
healthy and damaged vegetation in the spectral re
gion of the visible, near infrared and middle infra
red part of the electromagnetic spectrum. These spec
tral differences are assumed for a computer classi
fication to operate, so the first step was the eva
luation of the spectral signatures of differently
damaged tree species. The results of this evaluation
are presented in a special paper at this symposium
(Kadro, 1986). For the supervised classification
and presentation of results special software was de
veloped at the department. The classification algo
rithm is a combined box and maximum-1 ikelyhood
classifier which can also analyse additional infor
mation given by the user. For example: terrain model,
masks, modification of the covariance matrix, a pri
ori probabilities and permanent or temporary condi
tions for including or excluding pixels during the
classification process.
2 RESULTS OF THE COMPUTER AIDED CLASSIFICATION!
2.1 Frcm 300 m altitude
The test sites differ in morphology, forest types and
degree of the actual forest damage to simulate all
possible inventory problems. The data collected frcm
For checking the classification from 300 m altitude
a crown map drawn with a Bausch and Lomb Zocm-Trans-
ferscope was digitized and used as an overlay (photo
1).