期刊
REMOTE SENSING
卷 9, 期 5, 页码 -出版社
MDPI
DOI: 10.3390/rs9050479
关键词
Landsat time series; LandTrendr algorithm; forest disturbance and recovery; drought
类别
资金
- National Natural Science Foundation of China [41571411]
- Zhejiang Agriculture and Forestry University's Research and Development Fund [2013FR052]
Detection of forest disturbance and recovery has received much attention during the last two decades due to its important influence on forest carbon budget estimation. This research used Landsat time-series data from 1984 to 2015 to examine forest disturbance and recovery in a subtropical region of eastern Zhejiang Province, China, through the LandTrendr algorithm. Field inventory data and high spatial resolution images were used to evaluate the disturbance and recovery results. This research indicates that high producer and user accuracies for both disturbance and recovery classes were obtained and three levels of disturbance and recovery each can be detected. Through incorporation of climate data and disturbance results, drought events also can be successfully detected. More research is needed to incorporate multisource data for detection of forest disturbance types in subtropical regions.
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