NDVI-Based Long-Term Vegetation Dynamics and Its Response to Climatic Change in the Mongolian Plateau

Abstract

Abstract:The response of vegetation to regional climate change was quantified between 1982 and 2010 in the Mongolian plateau by integrating the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) and the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI (2000NDVI ( -2010. Average NDVI values for the growing season (April-October) were extracted from the AVHRR and MODIS NDVI datasets after cross-calibrating and consistency checking the dataset, based on the overlapping period of 2000-2006. Correlations between NDVI and climatic variables (temperature and precipitation) were analyzed to understand the impact of climate change on vegetation dynamics in the plateau. The results indicate that the growing-season NDVI generally exhibited an upward trend with both temperature and precipitation before the mid-or late 1990s. However, a downward trend in the NDVI with significantly decreased precipitation has been observed since the mid-or late 1990s. This is an apparent reversal in the NDVI trend from 1982 to 2010. Pixel-based analysis further indicated that the timing of the NDVI trend reversal varied across different regions and for different vegetation types. We found that approximately 66% of the plateau showed an OPEN ACCESS Remote Sens. 2014, 6 8338 increasing trend before the reversal year, whereas 60% showed a decreasing trend afterwards. The vegetation decline in the last decade is mostly attributable to the recent tendency towards a hotter and drier climate and the associated widespread drought stress. Monitoring precipitation stress and associated vegetation dynamics will be important for raising the alarm and performing risk assessments for drought disasters and other related natural disasters like sandstorms.

Responses of Natural Vegetation Dynamics to Climate Drivers in China from 1982 to 2011

“…16.64% of areas have undergone slowed down NDVI trends, especially in northern grassland, which could be partly contributed by the slowed down trends of temperature in these areas since mid 1990s (Figure 10c,d). The study by Bao et al [20] also indicated the decreasing trends of NDVI in the Mongolian Plateau since mid or late 1990s. In some arid and semi-arid areas such as southern Tibetan and northern Xinjiang, speeded up temperature increment could limit the water availability for vegetation hence led to stalled NDVI trends [55].…”

“…The influence of climate on vegetation dynamics has drawn increasing attention in the past few decades [14][15][16][17][18][19][20]. Long-term remote sensing observations provide effective methods to investigate interannual vegetation dynamics.…”

“…Relationships between NDVI and climatic drivers were typically analyzed with regression method, indicating that NDVI was more sensitive to temperature than precipitation in North America and China and increased corresponding to global warming [2,32]. Most previous studies mainly focused on mean NDVI values within a fixed time period, such as the whole year or uniform growing season (April to October) [20,30,33], which may not properly reflect vegetation growth condition in the growing season that varies with region and vegetation types [34,35]. Especially for China, with its large land area and vegetation diversity, there can be significant difference among the growing seasons in different regions and vegetation types.…”

Spatio-temporal vegetation dynamics and relationship with climate over East Africa

“…Multispectral band combinations of these datasets have aided the retrieval of long time series of land surface variables widely used to examine trends in vegetation dynamics at global, regional and national scales (Bao et al, 2014;Julien and Sobrino, 2009), impacts of vegetation on water and energy flux (Hu 10 et al, 2009) as well as the correlation between vegetation and climate conditions (Bao et al, 2014). Particularly, Leaf Area Index (LAI), which is defined, in broadleaf canopies, as the one-sided green leaf area per unit vegetated ground area, and in coniferous canopies, as one-half the total needle surface area per unit vegetated ground area.…”

“…Terrestrial vegetation depend on and affect land surface-atmosphere interactions as the primary link for moisture 25 (evapotranspiration) and energy (latent) exchange through its physiological properties (Leaf Area Index-LAI, rooting depth and stomatal resistance), and its influence on surface roughness, and albedo (Arora, 2002;Bao et al, 2014;Ning et al, 2015). For instance, recent studies have reported a strong land-atmosphere coupling in West Africa, whereby vegetation dynamics play a significant role in regulating the West Africa monsoon and therefore rainfall distribution (Hales et al, 2006;Xue et al, 2012;Zheng and Eltahir, 1998).…”