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Assessment of the Forest Damage by Typhoon Saomai Using Remote Sensing and GIS


Affiliations
1 Research Institute of Subtropical Forestry, The Chinese Academy of Forestry, Fuyang 311400, Zhejiang Province, China
 

Saomai (August 10, 2006) was one of the most significant typhoons to hit the coast in southeast China. Quantitative assessment of forest disturbances is important for improving management strategies. This study used remote sensing techniques to investigate vegetation changes after Saomai in Changnan county. Two landsat ETM+ satellite images were acquired before and after landfall. The results showed that averaged NDVI values decreased by 17.8% after Saomai. Elevation and relative aspect present strong influence on the typhoon damage. These results provide insight into the sensitivity of coastal vegetation from the interactions of both tropical cyclones and long-term environmental conditions.

Keywords

Forest Disturbance, Typhoon Saomai, Remote Sensing, NDVI.
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  • Assessment of the Forest Damage by Typhoon Saomai Using Remote Sensing and GIS

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Authors

Xiaoming Wang
Research Institute of Subtropical Forestry, The Chinese Academy of Forestry, Fuyang 311400, Zhejiang Province, China
Benzhi Zhou
Research Institute of Subtropical Forestry, The Chinese Academy of Forestry, Fuyang 311400, Zhejiang Province, China

Abstract


Saomai (August 10, 2006) was one of the most significant typhoons to hit the coast in southeast China. Quantitative assessment of forest disturbances is important for improving management strategies. This study used remote sensing techniques to investigate vegetation changes after Saomai in Changnan county. Two landsat ETM+ satellite images were acquired before and after landfall. The results showed that averaged NDVI values decreased by 17.8% after Saomai. Elevation and relative aspect present strong influence on the typhoon damage. These results provide insight into the sensitivity of coastal vegetation from the interactions of both tropical cyclones and long-term environmental conditions.

Keywords


Forest Disturbance, Typhoon Saomai, Remote Sensing, NDVI.