1004 
It may be that new developments will witness the emergence of yet other approaches. For example, 
expert systems (whether rule-based or using neural networks) may both integrate much of the knowledge 
gathered with the models described above and provide alternative ways to analyze remote sensing data, 
as explained by Kimes et al. (1994). The validation of the models and relations used in remote sensing 
remains a major challenge, mostly due to the lack of appropriate data sets. High priority should be given 
to combined laboratory and field campaigns, where both remote sensing and in situ data are collected from 
the same targets concurrently. 
Last but not least, it has been argued that the exploitation of the directional variance in the measured 
signals should precede their spectral analysis. This has significant implications on the priorities for further 
research and the development of future sensors, especially because the current focus on high spectral resolu 
tion. In this respect, the selection of MISR on NASA’s EOS-AM platform and POLDER on Japan’s ADEOS 
constitutes an original and most promising development. 
ACKNOWLEDGMENTS 
The authors are grateful to Pasquale Nardone (IRSA) for insightful discussions and comments on a draft of 
this paper. 
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