Application of Remote Sensing to Land Cover Change Induced by Nargis Hurricane in Myanmar

In order to investigate the effects of the Nargis hurricane on the Ayeyarwady Delta in Myanmar, the ISODATA (iterative self-organizing data analysis techniques algorithm) unsupervised classification method and the Bayesian maximum-likelihood supervised-classification method were used to classify the land cover of the study area based on Myanmar ALOS/AVNIR-2 remote sensing data, and the quantitative changes of land cover in the Ayeyarwady Delta before and after the Nargis hurricane were obtained. In addition, the relationships between the Nargis hurricane disaster and the area and density of mangrove forests were investigated quantitatively. The research result shows that a mangrove forest with a large area and high density has a great effect to decrease a hurricane disaster such as the Nargis hurricane disaster.