Title of article :
Post-hurricane forest damage assessment using satellite remote sensing
Author/Authors :
Wanting Wang، نويسنده , , John J. Qu، نويسنده , , Xianjun Hao، نويسنده , , Yongqiang Liu، نويسنده , , John A. Stanturf، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
Pages :
11
From page :
122
To page :
132
Abstract :
This study developed a rapid assessment algorithm for post-hurricane forest damage estimation using moderate resolution imaging spectroradiometer (MODIS) measurements. The performance of five commonly used vegetation indices as post-hurricane forest damage indicators was investigated through statistical analysis. The Normalized Difference Infrared Index (NDII) was identified as the optimal damage indicator among these vegetation indices. An approach for detecting forest damage at a regional scale, without relying on ground inventory or sampling, was designed and validated. The validation showed that the relative change of pre- and post-hurricane NDII was linearly related to the damage severity estimated by the ground inventory with the coefficient of determination 0.79. This approach was applied to evaluate forest damage severity and the impacted region caused by Hurricane Katrina.
Keywords :
NDII , Vegetation index , MODIS , Algorithm , Forest disturbance
Journal title :
Agricultural and Forest Meteorology
Serial Year :
2010
Journal title :
Agricultural and Forest Meteorology
Record number :
964925
Link To Document :
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