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30 October 2009 Time lag responses of Gurbantonggut Desert vegetation to meteorological factors
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Proceedings Volume 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications; 74980I (2009) https://doi.org/10.1117/12.829389
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
Abstract
Time lag responses of Gurbantonggut desert vegetation to meteorological factors are analyzed by using NOAA / AVHRR NDVI time series data from 1982 to 2003 and meteorological factors such as temperature, precipitation, sunshine hours. Conclusions are drawn as follows: in recent 22 years, NDVI trend in Gurbantonggut desert is generally upward; its monthly average values are symmetrically presented with a single peak. From the view of inter-annual changes, annual precipitation, relative humidity, maximum winter snow depth and NDVI obviously have a positive correlation; annual evaporation, sunshine hours, maximum frozen soil depth and NDVI significantly have a negative correlation; annual average temperature, ground temperature and NDVI have no obvious relationship. From the view of different stages of vegetation growing season, in early and late growing season, vegetation growth and pre-period heat accumulation are closely related, while vegetation growth and precipitation mostly have a negative correlation. In the middle of growing season, high temperature will increase water evaporation, vegetation growth is slow due to water shortage; precipitation and vegetation growth obviously have a positive correlation, its impacts on vegetation growth is significantly lagging, the previous one and two month precipitation influences vegetation growth obviously.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yang Li, Na Lin, Yan Liu, and Pu Zhang "Time lag responses of Gurbantonggut Desert vegetation to meteorological factors", Proc. SPIE 7498, MIPPR 2009: Remote Sensing and GIS Data Processing and Other Applications, 74980I (30 October 2009); doi: 10.1117/12.829389; https://doi.org/10.1117/12.829389
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