The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
undulation could dramatically bias the reflectances of targets
and further seriously attenuate the unmixing result for LSMM,
and on the other hand, it also validate the effectiveness of C
correction method on removing terrain undulation effect again.
(at)
FI = 1. 3138HDVI + 0. 048
E? = 0.7774
l
* o.a
0.6
0.0
o.z
Jim
0.2 0.4 0.6 0.3
-0.4
HDTI
Cbl)
Ct2)
Figure 5 (al),(a2) Relationships between vegetation abundances and NDVI for pre-C corrected and post-C corrected ASTER
imagery. (bl),(b2) Relationships between vegetation abundances and MVI for pre-C corrected and post-C corrected ASTER imagery.
5. SUMMARIES AND CONCLUSIONS
This paper has investigated the impact of terrain undulation on
LSMM with reference to unmixing vegetation abundances using
LSMM. C correction was used to remove or minimize terrain
effects of the original ASTER data and the result showed that
the C method was reasonable and effective. The endmember
selection procedures such as minimum noise fraction (MNF),
pixel purity index(PPI) and n-dimensional visualization were
implemented respectively to pre-corrected and post-corrected
ASTER data to determine the endmembers effectively. A full
constrained least square LSMM was applied to the two data sets
and the vegetation abundance images were sequentially
derived .Multi-regression analysis between vegetation
abundance and vegetation indexes which was employed to
validate and estimate the terrain undulation impact on LSMM
indicated that terrain undulation could constrain the application
of LSMM, typically the unmixing precision was improved
17.6% and 18.6% in R2 value for NDVI and MVI by
minimizing or even removing terrain undulation effect using C
correction method in our study. So specially effective removal
or minimization of terrain impact was essential for LSMM
applications in moderate or small-scale mountainous areas. The
results not only proved the terrain undulation could dramatically
bias the reflectances of targets and further seriously attenuate
the unmixing result for LSMM but also validate the
effectiveness of C correction method on removing terrain
undulation impact again.
Though we took vegetation abundance as a case study, it should
be envisioned that the similar result for other endmember types
(water, barren soil, impervious area and so on )could be achieve
because of the same impact mechanism of terrain undulation
and the identical unmixing procedure with LSMM. However
further studies of different area different types of imagery and
other endmembers are recommended with purpose to inspect the
validation and applicability of our results and conclusions. In
addition, to acquire specific unmixing precision the accurate
and quantitative ground data should be collected. In fact, the
atmospheric scattering and scales of the imagery can also
behave negative impact on LSMM, to quantitatively evaluate
the impacts is our further work in the future.
ACKNOWLEDGEMENTS
the authors like to extend our appreciations to College of
Geographical Sciences ,Fujian Normal University, Fujian
provincial department of science & technology for their
foundation support. We also want to gratefully acknowledge all
the anonymous reviewer for reviewing the manuscript.
REFERENCES
Adams, J. B., Sabol, D. E., Kapos, V., Almeida, R., Roberts, D.
A., Smith, M.O., et al. (1995). Classification of multispectral
images based on fractions of endmembers—Application to
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