The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
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explicit connection with the structural configurations but, in 
turn, also leads to low BRF . Considering the CV Cab , a shape 
similar to leaf level appeared but then with a markedly higher 
magnitude (around 35-40%), which can be fully explained by 
absence of any other confounding factor. 
Figure 2. a) BRF with interpolated Ca6-induced SD (grey 
band), b) associated CV Ca b at canopy level as simulated by 
FLIGHT (crown LAI: 2.5; PV: 70%; CC: 60%). 
To exploit the propagated variability along gradients of canopy 
variables, we chose one specific wavelength where the subtle 
Cab signal is prominently expressed. Wavelengths associated 
with chlorophyll content are to be found in the 550 or 700 nm 
regions, where higher contents of chlorophyll b and chlorophyll 
a, respectively, are required to saturate the absorptance 
(Thomas & Gausman, 1977). CHRIS wavebands associated 
with these chlorophyll regions are A^: 530, 551, 570 and 697, 
703, 709 nm respectively. For each of these wavebands the 
CV C ab were plotted along the NPV-PV gradient. The gradient 
starts from 0% NPV onwards whereby the proportion of canopy 
woody elements (NPV) gradually increases (figure 3). From 
this set of chlorophyll-sensitive wavebands, the A^ 531 nm 
band exhibited greatest decrease all along the NPV gradient 
implying greatest sensitivity to woody elements, while the A^ 
709 nm band gave sign of a flatter response implying certain 
robustness to woody elements. Since apart of chlorophyll, 
anthocyanin also absorbs around 550 nm (Sims et al., 2002), we 
opted to continue working with the radiant flux at 709 nm. 
Figure 3. Waveband-dependent trends of CV Cab (%) along the 
NPV gradient (%PV= 100-%NPV). Values were averaged over 
the gradients of crown LAI and crown closure. 
3.1 Detectability of chlorophyll content 
The applicability of observed trends in the context of real-world 
canopies is analyzed next. As pointed out above, woody parts 
can significantly govern the canopy cover of coniferous forests. 
Being aware of varying NPV fractions at sub-pixel level the 
underlying idea of this modelling exercise is that modelling 
results may provide canopy-specific indicators regarding the 
suitability of retrieving chlorophyll content from reflectance 
data. The Standard deviation (SD) indicates the absolute spread 
of the reflectance spectra. Due to the fixed Cab range the 
magnitude of the SD is explicitly governed by structural 
attributes. Consequently, given the assumption that a greater 
spectral spread allows easier detection and mapping of 
chlorophyll content, the SD results provides thus a theoretical 
indicator of the stand-dependent chlorophyll content 
detectability. To exemplify this, four structurally distinct real- 
world forests were selected (figure 4). 
Each of the coniferous stands holds near-optimal conditions to 
retrieve chlorophyll content in terms of CC and crown LAI with 
the exception of the heavily affected spruce stand in the 
Sumava Mountains. They encompass a CC of 60% or higher 
and a varying crown LAI. The homogenous, dense young 
spruce stand (figure 4a), for example, is characterized by high 
crown LAI value (7.8) which results into a slight suppressed SD 
as a consequence of the LAI-dependent chlorophyll absorptions. 
The other test sites encompass a lower LAI which implies a 
slightly greater spectral spread and thus detectability. 
When positioning the four stands along the NPV-PV gradient, 
however, only then the true Cab detection feasibility appears. 
The virtual absence of woody cover in the outer canopy of the 
young spruce stand implies that the full Cab-related variability 
can reach a sensor without any contamination. Canopy structure 
such as the high LAI would be the limiting factor here, but only 
to a minor extent (figure 4e). By contrast, the old-growth forest 
in SNP gave sign of a more complicated canopy structure and 
composition (figure 4b). As a consequence of dead and partly 
dead trees a fractional NPV cover may reach up to 30% at 
CHRIS pixel resolution. Due to the scattered woody parts 
within the canopy, PV and NPV of this stand are 
heterogeneously arranged in a quasi-random manner. The 
modeling results indicate that such woody contribution may 
suppress the chlorophyll-dependent spectral spread with 28% 
given the SNP structural configurations (CC: 0.60; LAI: 2.5). 
However, note that the canopy throughout the test site is rather 
open meaning that in reality understory, which is again a 
mixture of PV and NPV, will partly contribute to the 
chlorophyll signal as well. 
Contrarily to the latter, the infested stands in British Columbia 
(figure 4c) and in the Bohemian Forest (figure 4d) are from 
another order of woodiness. The British Columbian stand shows 
mixtures of green trees, red-attack trees and grey-attack trees 
throughout the forest (figure 4d). Subsequently, the spatial 
distribution of NPV fractional cover varies dramatically. Such 
spatial PV-NPV variation implies that relationships between 
reflectance spectra and the needle pigment concentrations of 
remaining foliage are perturbed in a pixel-specific way. The 
presented results of the rapid declining SD along the NPV-PV 
gradient indicate the magnitude of change (figure 4f, g). Finally, 
the example of the Bohemian Forest reflects the worst case 
situation: virtually the complete stand suffers from insect 
defoliation. Only small patches and a few isolated trees are left 
unaffected. What is left of the signal from remaining green 
cover is in consequence heavily suppressed by dominating NPV 
cover. No structural assessments have been carried out in this 
region. With a visually assessed of remaining 40% PV and 50% 
CC the modeling results indicated that only 58% of the full Cab 
spread is left over. 
4. CONCLUSIONS 
Natural forests go through development stages with increasing 
heterogeneity in the distribution of foliage and woody parts. 
The direct observable effects of these trajectories are that 
structural variables such as fractional cover, LAI and the 
amount and arrangement of woody elements alter over time. 
For instance, the old-growth forest of Swiss National Park that