Investigation of Vegetation Dynamics of Mongolia Using Time Series of NDVI in Response to Temperature and Precipitation

Climate is one of the most important factors affecting the condition of vegetation. Plants are highly sensitive to climate change and display the most sensitive response to the effect of the climate change and environment, most particularly seen in the annual and seasonal alternations of vegetation productivity. Through the analysis of remotely sensed images, it is proved that vegetation indices can give signifi cant information regarding vegetation. The main purpose of this study was to estimate the infl uences of precipitation and temperature on spatio-temporal pattern of vegetation dynamics in Mongolia using MODIS sensor derived NDVI images over the course of 10 years. The correlation coeffi cient showed that mean growing season NDVI was correlated with both climatic factors, but more signifi cantly correlated with precipitation ( r 2 =0.92, p =0.000) than temperature ( r 2 =0.55, p =0.013). Growing season precipitation slightly decreased with an annual average decrement of 0.2 mm ( r 2 =0.06). Meanwhile, the growing season mean temperature slightly increased over 10 years, with an annual average increment of 0.01°C per year ( r 2 =0.003) from 2000 to 2009. However, the relationship between NDVI and climatic factors, and their change trends have been varied spatially and temporally.

Abstract licence: CC BY-NC-ND

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