Unsupervised detection of opium poppy fields in Afghanistan from EO-1 hyperion data
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 (≤ 1 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 EO-1 Hyperion, the only available spaceborne 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 EO-1 Advanced Land Imager (ALI) multispectral data could not produce reasonable detection of poppy fields in Afghanistan.