Abstract

Inner Mongolia is one of the most sensitive regions to global change with vegetation significantly affected by global warming and human activities. Therefore, exploring the dynamic change of vegetation and its impact mechanism is of great significance for guiding the protection ecosystem and policy formulation. Based on the 1982–2015 growing season and the interannual normalized difference vegetation index (NDVI), simultaneous temperature and precipitation data sets, we extracted the characteristic components of the NDVI and climatic factors by the Variational Mode Decomposition (VMD) methods. And the periodic characteristics of the NDVI in Inner Mongolia and its relationship with climate over a period of 34 years were analyzed. The results show that: 1) The VMD algorithm overcomes the “mode aliasing” problem of Empirical Mode Decomposition (EMD) and can more accurately extract the periodic information of long time series vegetation NDVI dataset containing complex frequencies.; 2) the NDVI in the growing season of Inner Mongolia has main change cycles of one growing season (7 months) and half a growing season, and temperature and NDVI have the same double-cycle relationship, whereas precipitation has a periodic change of one growing season; 3) the NDVI cycle change of Inner Mongolia vegetation from 1982 to 2015 shows multiple time scales, showing 16.95a, 6.8a, 4.85a, 4.25a, 3.4a and 2.83a change cycles; 4) vegetation NDVI in Inner Mongolia from 1982 to 2015 has a good correlation with climate factors, and the partial correlation coefficients are different in Inner Mongolia and three sampling areas. NDVI and precipitation have relatively good periodic consistency, and there is a significant positive correlation between vegetation NDVI and temperature and precipitation before and after removing the interference of periodic variables. In general, temperature and precipitation jointly affect the NDVI cyclical changes of Inner Mongolia. The VMD algorithm has significant effects on determining the cyclic dynamic changes of NDVI and climatic factors.

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