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Scientia Silvae Sinicae ›› 2012, Vol. 48 ›› Issue (2): 54-62.doi: 10.11707/j.1001-7488.20120208

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Monitoring Forest Growth Disturbance Using Time Series MODIS EVI Data

Liu Lijuan1,2,3, Pang Yong1, Zhang Xiaoyang4, Svein Solberg5, Fan Wenyi3, Li Zengyuan1, Li Mingze3   

  1. 1. Institute of Forest Resources Information Techniques,CAF Beijing 100091;2. Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University Hangzhou 310036;3. College of Forestry, Northeast Forestry University Harbin 150040;4. NOAA/DESDIS/STAR,5200 AUth RD, Camp Springs,MD 20746 United States;5. Norwegian Forest and Landscape Institute, Postboks 115, 1431ÅS, Norway
  • Received:2010-05-24 Revised:2010-07-26 Online:2012-02-25 Published:2012-02-25

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Abstract:

Forest growth is mainly currently monitored using in-situ measurements in northeast of China. To effectively monitor forest growth disturbance at large scale, we attempted to use remote sensing technique, particularly, time series MODIS data from 2004 to 2006. The annual time series of 8-day enhanced vegetation index (EVI) dataset was generated and smoothed using a Savitzky-Golay filter. The EVI trajectory during growth season was simulated using a logistic model. From the simulated trajectory, the EVI area of growth season and annual EVI entropy were calculated. These two factors were combined to map the disturbance regions of forest growth. Finally, the disturbance regions were verified using a set of random samples. The result indicates that the disturbance points have distinctively higher entropy and lower peak. Some of these points also show abrupt EVI decline during the midseason of the peak phases or double peaks. This approach is demonstrated to be feasible for disturbance monitoring of forest growth.

Key words: time series, MODIS EVI, growth season area, entropy, disturbance monitoring

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