Response of vegetation ecosystem to climate change based on remote sensing and information entropy: a case study in the arid inland river basin of China

Vegetation is sensitive to regional climate change especially in the arid area, and the effects of global warming on regional climate and ecological vegetation are complex and varied. Spatio-temporal variation of vegetation is closely related to the changing climate, detecting the correlation between the variation of climate and vegetation characteristics in time and spatial dimension is important for understanding the effects of climate change on vegetation ecosystem. Therefore, remote sensing and information entropy were proposed in the study to estimate the spatio-temporal variation of vegetation with normalized difference vegetation index (NDVI) and meteorological elements in the Nalenggele river basin, northwest China. The average NDVI value of the study area showed an increasing trend but more than 40% of the vegetation characteristic in this area showed a worse trend from 1987 to 2016. Temperature is the relatively prominent factor that affects the vegetation variation in this area, but only 12.25% of the vegetation showed strong correlation with temperature. The increasing temperature promoted the growth of vegetation in the oasis region and also caused the degradation of vegetation in the Gobi desert region to some extent. The variation of precipitation and humidity are not the key factors that control vegetation growth, less than 2% of the vegetation showed strong correlation with these two meteorological elements. The results of this study support the conclusion that the fragile vegetation ecosystem in the vast Gobi desert areas shows deteriorating trend in the past several decades closely to the changing climate.