Full text: Papers accepted on the basis of peer-reviewed abstracts (Part B)

In: Wagner W., Székely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
experimental data themselves using the leave-one-out method 
(Figure 5). Figure 6 shows that we get a slight overestimation of 
CWC in this way. 
Figure 5. Relationship between first derivative of canopy 
reflectance over the interval 1015 - 1050 nm and 
CWC at the Achterhoek site in 2008. At the 
background the simulated relationship of Figure 3 is 
shown. 
Figure 6. Comparison between CWC measurements from field 
samples and CWC estimations using PROSAIL 
simulations of the relationship between CWC and 
the spectral derivative over the 1015 - 1050 nm 
interval. 
4. CONCLUSIONS 
Results presented in this paper show that the spectral 
derivatives for wavelengths on the right slope of the water 
absorption feature at 970 nm can be used for estimating canopy 
water content (CWC). PROSAIL model simulations were 
performed using the improved PROSPECT-5 model as 
described by Feret et al. (2008). A linear relationship between 
first derivative over the 1015 - 1050 nm spectral interval and 
CWC was found, which was not very sensitive for leaf and 
canopy structure. Field spectroscopic measurements at a fen 
meadow confirmed the simulation results. The relationship 
between the first derivative over the 1015 - 1050 nm interval 
and CWC based on in-situ spectral measurements obtained in 
the field appeared to match the simulated relationship obtained 
from the PROSAIL model. This showed that one may transfer 
simulated results to real measurements obtained in the field, 
thus giving them a physical basis and more general 
applicability. 
Both simulated spectra and experimental FieldSpec spectra 
showed that the right slope of the 970 nm absorption feature is 
linear (constant) in the range from about 1015 nm up to about 
1050 nm. Due to this broad interval, the first derivative over 
this 1015 - 1050 nm interval can be measured more accurately 
than the derivative at a certain spectral position (or narrow 
interval). As a result, this derivative also is more robust and less 
susceptible to noise. Smoothing the spectral measurements did 
not give better results than non-smoothed measurements. 
Smoothing was necessary when using narrow intervals (Clevers 
et ah, 2008). 
The PROSAIL simulations performed in this study do not 
include an atmospheric model. When using remote sensing 
observations from an airborne or spacebome platform, one 
should also consider the water vapour absorption by the 
atmosphere. This occurs, for instance, at 940 nm and 1140 nm 
(Gao and Goetz, 1990; Iqbal, 1983), thus being shifted to 
shorter wavelengths as compared to the corresponding liquid 
water absorption features. This means that the effect of water 
vapour absorptions in the atmosphere occurs at the left slopes of 
the water absorption features used for estimating CWC. So, if 
one cannot correct well for the effects of atmospheric water 
vapour, it is recommended to use the first derivative, e.g., in the 
1015 - 1050 nm interval. 
Future work will continue focusing on higher spectral 
resolution instruments, in particular in the water absorption 
regions at 970 and 1200 nm. Instruments with a significantly 
higher spectral resolution would be able to assess separately 
water molecules in atmosphere and vegetation, allowing correct 
estimations for both atmospheric water vapour and liquid water 
in vegetation. 
ACKNOWLEDGEMENTS 
This work has been supported by the European Community’s 
Marie Curie Research Training Networks Programme under 
contract MRTN-CT-2006-035927, Hyperspectral Imaging 
Network (HYPER-I-NET). 
REFERENCES 
Clevers, J.G.P.W., Kooistra, L. and Schaepman, M.E., 2008. 
Using spectral information from the NIR water absorption 
features for the retrieval of canopy water content. International 
Journal of Applied Earth Observation and Geoinformation, 
10(3), pp. 388-397. 
Clevers, J.G.P.W., Kooistra, L. and Schaepman, M.E., 2010. 
Estimating canopy water content using hyperspectral remote 
sensing data. International Journal of Applied Earth 
Observation and Geoinformation, 12(2), pp. 119-125. 
Curran, P.J., 1989. Remote sensing of foliar chemistry. Remote 
Sensing of Environment, 30(3), pp. 271-278. 
Danson, F.M., Steven, M.D., Malthus, T.J. and Clark, J.A., 
1992. High-spectral resolution data for determining leaf water 
content. International Journal of Remote Sensing, 13(3), pp. 
461-470. 
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