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Assessment of forest damage due to ice storm using image thresholding techniques: A case study of Yunnan Province

Date: 2018-06-08      View counts: 490    

Label:

Language
Chinese
Author
WU Jiansheng, CHEN Sha, PENG Jian
Journal
PROGRESS IN GEOGRAPHY
Class
The damaged vegetation detection
Year
2008
Paper Keyword
image thresholding techniques; forest; SPOT NDVI; ice storm; Yunnan Province
Abstract
Ice storms are one of the severe disruptions to forest ecological systems, causing vegetation loss and reduction of the ecological systems' functions. For this reason it is vital to assess the damages to forests after ice storms. Using SPOT Normalized Difference Vegetation Index(NDVI) time serial images of Yunnan Province of China during 2000-2011, forest damage caused by ice storms in 2008 was assessed based on image thresholding techniques of post-storm NDVI time series after Savitzky-Golay filtering by TIMESAT software. The damage threshold was determined by the difference of standard deviation between the years with ice storms and those without, which eventually turned out to be 21%. The range of extracted forest damage is almost consistent with the ice storm extent of Yunnan in the national monthly disaster report, therefore the result is reliable. The destroyed vegetation accounted for 12.09% of the total area of forest. Forest within Diqing County and Nujiang County, in northwest Yunnan, suffered the most losses. On the whole, seven counties took the worst hit by the natural adversity, while thirteen were moderately affected and forty five slightly affected. The most severe damage of forest occurred at the elevation of 3300 m to 4000 m, the slope of 5 to 15 degree, the middle slope position and the east or northeast aspect. Even so, it had little to do with slope position because the most of vegetation is located in the middle slope position. In-situ measurement was not employed here to verify the results because of time and money limits, which compromised the overall accuracy. However, with the acceptable precision, the research method can be used as a real-time forest loss assessment, which is of great significance for taking effective measures to avoid secondary impacts and starting the process of recovery.
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