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The Vegetation Coverage Dynamic Coupling with Climatic Factors in Northeast China Transect
Authors:Qin Nie  Jianhua Xu  Minhe Ji  Lei Cao  Yang Yang  Yulian Hong
Institution:The Research Center for East-West Cooperation in China, The Key Lab of GIScience of the Education Ministry PRC, East China Normal University, Shanghai, 200062, China.
Abstract:Based on SPOT-VGT images and meteorological data, this paper applied an integrated method to investigate the vegetation dynamic and its response to climate factors during 1998-2008 in Northeast China Transect, one of 15 ecological transects listed in the International Geosphere-Biosphere Programme. The main findings are as follows: (1) The NDVI time series presented nonlinear patterns that vary with timescales. The series fluctuated greatly at the smallest timescale (20?days), showing no salient trend, whereas a trend manifested itself more and more with the increase of time scale and finally stabilized at the 320-day scale. Little difference was found between vegetation types about the NDVI periodicity, as they occurred on either a 280-day or a 290-day cycle. (2) NDVI exhibited a significant correlation with temperature, precipitation, and sunshine hours. Overall, the correlation between NDVI and temperature was the highest, followed by precipitation, sunshine hours, and relative humidity. For different vegetation types, the correlations between NDVI and climate variables diversified, increasing from desert steppe to typical steppe, meadow steppe, and forest. (3) The periodicity of temperature and precipitation occurred in either a 280-day or 290-day cycle, which was approximately coincident with that of NDVI. This further supported the significant relationship between NDVI and these two climate factors. (4) At all the time scales under examination, NDVI and temperature and precipitation are significantly, positively correlated, especially at the 160-day scale, which can be regarded as the most suitable time scale for investigating the responses of vegetation dynamics to climate factors at most stations.
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