Dynamic Changes of NDVI in the Growing Season of the Tibetan Plateau During the Past 17 Years and Its Response to Climate Change.

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2019
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Abstract
The fragile alpine vegetation in the Tibetan Plateau (TP) is very sensitive to environmental changes, making TP one of the hotspots for studying the response of vegetation to climate change. Existing studies lack detailed description of the response of vegetation to different climatic factors using the method of multiple nested time series analysis and the method of grey correlation analysis. In this paper, based on the Normalized Difference Vegetation Index (NDVI) of TP in the growing season calculated from the MOD09A1 data product of Moderate-resolution Imaging Spectroradiometer (MODIS), the method of multiple nested time series analysis is adopted to study the variation trends of NDVI in recent 17 years, and the lag time of NDVI to climate change is analyzed using the method of Grey Relational Analysis (GRA). Finally, the characteristics of temporal and spatial differences of NDVI to different climate factors are summarized. The results indicate that: (1) the spatial distribution of NDVI values in the growing season shows a trend of decreasing from east to west, and from north to south, with a change rate of -0.13/10° E and -0.30/10° N, respectively. (2) From 2001 to 2017, the NDVI in the TP shows a slight trend of increase, with a growth rate of 0.01/10a. (3) The lag time of NDVI to air temperature is not obvious, while the NDVI response lags behind cumulative precipitation by zero to one month, relative humidity by two months, and sunshine duration by three months. (4) The effects of different climatic factors on NDVI are significantly different with the increase of the study period.
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huang2019dynamicinternational Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Huang, Xianglin;Zhang, Tingbin;Yi, Guihua;He, Dong;Zhou, Xiaobing;Li, Jingji;Bie, Xiaojuan;Miao, Jiaqing;
Journal International journal of environmental research and public health
Year 2019
DOI
E3452
URL
Keywords
climate change ndvi grey relational analysis (gra) multiple nested times series analysis (mntsa) tibetan plateau

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