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16 October 2013Mapping tropical rainforest canopies using multi-temporal spaceborne imaging spectroscopy
The use of imaging spectroscopy for florisic mapping of forests is complicated by the spectral similarity among coexisting
species. Here we evaluated an alternative spectral unmixing strategy combining a time series of EO-1 Hyperion
images and an automated feature selection strategy in MESMA. Instead of using the same spectral subset to unmix each
image pixel, our modified approach allowed the spectral subsets to vary on a per pixel basis such that each pixel is
evaluated using a spectral subset tuned towards maximal separability of its specific endmember class combination or
species mixture. The potential of the new approach for floristic mapping of tree species in Hawaiian rainforests was
quantitatively demonstrated using both simulated and actual hyperspectral image time-series. With a Cohen’s Kappa
coefficient of 0.65, our approach provided a more accurate tree species map compared to MESMA (Kappa = 0.54). In
addition, by the selection of spectral subsets our approach was about 90% faster than MESMA. The flexible or adaptive
use of band sets in spectral unmixing as such provides an interesting avenue to address spectral similarities in complex
vegetation canopies.
Ben Somers andGregory P. Asner
"Mapping tropical rainforest canopies using multi-temporal spaceborne imaging spectroscopy", Proc. SPIE 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, 888704 (16 October 2013); https://doi.org/10.1117/12.2028508
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Ben Somers, Gregory P. Asner, "Mapping tropical rainforest canopies using multi-temporal spaceborne imaging spectroscopy," Proc. SPIE 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, 888704 (16 October 2013); https://doi.org/10.1117/12.2028508