Z»nl» 
Zenith 
à<fii 
where: 
i and r = denotes 
the incident and the 
reflected radiation, 
respectively 
d 0 = the element of 
the radiant power 
propagating within 
the element of solid 
angle d 
ft = zenith angle 
7 = azimuth angle 
Fig. 1 (from Boehnel et al 1978) shows the geometry 
of reflection: 
R(A) 
and: 
L Ar 
L A‘ wL* Cf 
Table 3. Damage classes. 
Healthy = 0-10% needleloss 
Sickly = 11 - 25% 
Damaged = 26 - 60% " 
Severely damaged = more than 60% " 
3.1 The spectral reflectance signature in the visible 
region 
The reflection curves of healthy spruce, fir trees 
and stands differ clearly in the visible region iron 
those slightly or severely damaged and from dead Fir, 
spruce trees. 
Fig. 2-10 show that damaged trees or stands have a 
continually higher reflection between the visible 
channels 3-7 than the vigorous trees. This is due 
to lower chlorophyl amounts which turn the color of 
the needles to yellow or brown and therefore a higher 
reflection in the visible region. 
The data in Fig. 7 represent an average reflection 
value of many (3-4) stands. 
L Ar = (GV ~ ~ bbl) 
L À r • wL = ^ ~ BBL ^ * C// ^ ~ BBL ^ * * ^ 3.2 Spectral reflectance in near infrared 
where: 
R(^) = spectral reflectance factor 
L^ r = object radiance 
GV = grey value (digital number) 
BEL = blackbody low of the MSS 
C = calibration value of the MSS 
RL = reference lamp of the MSS 
A A = spectral band width 
L Ar wl = re ^ erence panel radiance = global radia 
tion 
Cf = correction factor of reference panel 
The Landsat 5 (TM) data is also converted from grey 
value (digital numbers) to reflected radiance in 
W/m 2 .sr.mic. as follows: 
L^ r = (GW - OF) / (GN 4* AA) 
where: 
L^ r = reflected radiance 
GW = grey value (digital number) 
CF = detector offset (digital number) 
QSI = gain 
£ X = spectral band width 
3 RESULTS 
The test site is mountainous and therefore single 
trees, groups of trees or stands will not be illumi 
nated equally by the sun's radiation. This means that 
the reflected radiance from similar objects in diffe 
rent exposition has various intensities. The reflec 
ted radiance from a single tree depends on the den 
sity of the foliage and in the case of a damaged tree 
(loss of needles or leaves) the detected radiance may 
be reflected from the soil or ground vegetation 
through the tree crown. This is quite often the case 
with damaged tree crowns. 
Because of the resolution cell size, this study, as 
most studies, evaluated the integrated reflected com 
ponent of the...ground area which includes tree canopy, 
soils, lower vegetation and shadow. All damaged fo 
rest stands are located on ridge tops and healthy 
stands are generally on the lower slopes and in the 
valley. This distribution of stands also affects the 
reflected radiance values. 
The reflection in this spectral region is indepen 
dent of the plant pigmentation. The intensity of the 
reflection depends rather on the vitality of the ve 
getation, vigorous trees and stands reflect more than 
damaged (Fig. 2 - 10), but the reflectance curves 
(Fig. 7) from this study show that the damaged stands 
have higher reflection in channels 8, 9 and 10. 
This spectral reflectance behaviour was not expected. 
There are many possible factors which could explain 
this phenonena e.g. the data in Fig. 7 are collected 
by aircraft at 1000 m altitude above ground, and the 
location of the damaged stands are in the middle of 
the test strip on the top of the mountain whereas 
the healthy stands are downslope and in the valley. 
The observation is therefore different, and the re 
flected intensity will be different. 
Beech trees or stands always reflect more near IR 
radiation than the coniferous types (Fig. 2, 5-9). 
3.3 Spectral reflectance in middle infrared 
Middle IR data are available for altitudes of 1000 m, 
3000 m and Landsat 5 (TM) . The reflection in this 
region depends on the water content of the vegeta 
tion. Damaged vegetation usually has a lower water 
content because of decreased evaporation (defolia 
tion and dry branches) and therefore reflects more 
radiation than healthy vegetation. 
Fig. 7 and 10 show clearly the differences in the 
reflection between healthy and damaged stands. 
4 CONCLUSION 
Knowledge about the spectral reflectance signatures 
of forest stands (healthy and damaged) using multi- 
spectral data is very important for quantification, 
classification and monitoring of forest areas which 
show various degrees of damage. 
The evaluated data in this study which were collected 
from different altitudes show clear differences in 
spectral Signatures, in the visible near IR and 
middle IR regions of the electromagnetic spectrum 
especially in the near IR region. That indicates 
the possibility for a computer aided classification 
of the .forest damage inventory task.