Unsupervised detection of opium poppy fields in Afghanistan from E0-1 Hyperion data
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Date
2013
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University of New Brunswick
Abstract
Satellite remote sensing has special advantages for monitoring the extent of illegal
drug production that causes serious problems to the global society. Although remote
sensing has been used to monitor opium poppy fields, the main data employed were
high-resolution images (:S I m) like pan-sharpened IKONOS, QuickBird, etc. These
images are costly, making the full coverage of the crop fields in a large area an
expensive exercise. As an alternative, the imagery acquired by E0-1 Hyperion, the only
available spacebome hyperspectral sensor currently, is free. However, its spatial
resolution is coarser (30 m). Until now, there is little evidence that poppy fields have
been identified from aerial or satellite hyperspectral images. This thesis proposed two
unsupervised methods (i.e., a MESMA-based one and a MTMF-based one), that could
detect poppy fields in Afghanistan from Hyperion data directly. Comparing the two
methods, the MTMF-based one has much higher computational efficiency. Moreover,
the MTMF-based method performed well in both of the two main environments in
Afghanistan. In addition, it was found that the moderate spatial resolution E0-1
Advanced Land Imager (ALI) multispectral data could not produce reasonable detection
of poppy fields in Afghanistan.