侯学会等：Phenology of Forest Vegetation in Northeast of China in Ten Years Using Remote Sensing

Phenology of Forest Vegetation in Northeast of China in Ten Years Using Remote Sensing
作者:Hou, XH (Hou Xue-hui)[ 1 ] ; Niu, Z (Niu Zheng)[ 1 ] ; Gao, S (Gao Shuai)[ 1 ]
SPECTROSCOPY AND SPECTRAL ANALYSIS
卷: 34  期: 2  页: 515-519
DOI: 10.3964/j.issn.1000-0593(2014)02-0515-05
出版年: FEB 2014

摘要
Plant phenology is the best indicator of terrestrial ecosystem response to climate change and it becomes a hot issue in the study of global change. The forest in northeast of China plays an important part in global forest ecosystem. In this paper, yearly integrated Normalized Difference Vegetation Index (NDVI) of forest vegetation in northeast China was calculated based on Spot Vegetation datasets from 2001 similar to 2010, which has been filtered using Savtiky-Galoy method. And then, the yearly integrated NDVI profile was fitted using a logistic model. Two key parameters of forest phenology (start of season, SOS; end of season, EOS) were extracted according to the greatest rate of curvature of fitted cumulative NDVI and the length of forest phenology (length of season, LOS) was also analyzed. The main conclusions of this paper are (1) SOS mainly occurs in the 110th similar to 140th day and EOS in 260th and 290th day. SOS displays a marked delayed from south to north while EOS gradually advances. However, the changes of SOS and EOS in ten years are not obvious. (2) Corresponding to the SOS and EOS, LOS of forest in study area mainly occurs in the 120th similar to 160th day; however, it is spatially heterogeneous. LOS of forest in Greater Khingan Mountains is shorter (about 120 similar to 140 day) than forests in Xiao Hinggan Ling and Changbai Mountains (about 160 day). The results in this paper are concordant with records of phenology in situ measurements and previous researches in the same area. It indicates that forest phenophases using method in this paper from Spot Vegetation dataset is feasible.

通讯作者地址: Niu, Z (通讯作者)
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China