New Model Sheds Light on Grassland Desertification Dynamics
Dec 21, 2023
In a recent study published in Remote Sensing on December 13, scientists from the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences（CAS）have employed a Desertification Difference Index (DDI) model to better understand and combat global grassland desertification. The research, centered in Xilingol, northern China’s Inner Mongolia，focused on extracting desertification information using albedo-EVI, revealing insights into the spatial and temporal dynamics of desertified grasslands (DGLs).
Spatially, Xilingol's DGL displayed a zonal distribution, while temporally, the degree of desertification decreased significantly. Severely and moderately desertified areas reduced from 51.77% in 2000 to 37.23% in 2020, showing a positive trend. Concurrently, non-desertified and healthy areas increased from 17.85% in 2000 to 37.40% in 2020, underscoring the importance of comprehending conversion patterns among different desertification levels.
Transition intensities among various desertification levels were more pronounced during 2000–2012 but stabilized during 2012–2020, providing optimism for the implementation of sustainable management practices. The study identified meteorological factors and soil conditions as primary drivers of DDI spatial distribution. Notably, evapotranspiration emerged as the most influential factor, underscoring the critical role of natural processes.
Intriguingly, human activities were found to dominate interannual DDI variations, emphasizing the need for comprehensive prevention and control measures. The study's findings offer insights into the intricate interplay of natural and anthropogenic factors contribute to grassland desertification. By unraveling the complexities of conversion patterns and identifying the driving forces in both spatial and temporal dimensions, this research is expected to provide valuable clues for targeted strategies to mitigate the global ecological concern of grassland desertification.
Researchers conduct grassland sampling surveys in Xilingol. (Image by AIR)
Contact: luyq@aircas.ac.cn
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