Acta Geographica Sinica ›› 2019, Vol. 74 ›› Issue (3): 534-543.doi: 10.11821/dlxb201903010

• Climate Change and Surface Process • Previous Articles     Next Articles

Revealing the climatic impacts on spatial heterogeneity of NDVI in China during 1982-2013

Jiangbo GAO1(), Kewei JIAO1,2, Shaohong WU1,3   

  1. 1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, CAS, Shenyang 110016, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-08-21 Revised:2018-12-06 Online:2019-03-25 Published:2019-03-19
  • Supported by:
    National Natural Science Foundation of China, No.41530749, No.41671098;Strategic Priority Research Program of the Chinese Academy of Sciences, No.XDA20020202;National Basic Research Program of China, No.2015CB452702;National Key R&D Program of China, No.2018YFC1508801


Climate change is a major driver of vegetation activity, and thus its complex processes become a frontier and difficulty in global change research. To understand the complex relationship between climate change and vegetation activity, the spatial distribution and dynamic characteristics of the response of NDVI to climate change from 1982 to 2013 in China were investigated by the geographically weighted regression (GWR) model. The GWR was run based on the combined datasets of satellite vegetation index (GIMMS NDVI) and climate observation (temperature and moisture) from meteorological stations nationwide. The results noted that the spatial non-stationary relationship between NDVI and surface temperature has appeared in China. The significant negative temperature-vegetation relationship was distributed in northeast, northwest and southeast parts of the country, while the positive correlation was more concentrated from southwest to northeast. And then, by comparing the normalized regression coefficients for different climate factors, regions with moisture dominants for NDVI were observed in North China and the Tibetan Plateau, and regions with temperature dominants for NDVI were distributed in the East, Central and Southwest China, where the annual mean maximum temperature accounts for the largest areas. In addition, regression coefficients between NDVI dynamics and climate variability indicated that the higher warming rate could result in the weakened vegetation activity through some mechanisms such as enhanced drought, while the moisture variability could mediate the hydrothermal conditions for the variation of vegetation activity. When the increasing rate of photosynthesis exceeded that of respiration, there was a positive correlation between vegetation dynamics and climate variability. However, the continuous and dynamic responding process of vegetation activity to climate change will be determined by spatially heterogeneous conditions in climate change and vegetation cover. Furthermore, the description of climate-induced vegetation activity from its rise to decline in different regions is expected to provide a scientific basis for initiating ecosystem-based adaptation strategies in response to global climate change.

Key words: NDVI, climate change, spatial heterogeneity, GWR, China