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JOURNAL OF DESERT RESEARCH ›› 2018, Vol. 38 ›› Issue (1): 17-29.DOI: 10.7522/j.issn.1000-694X.2017.00086

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Process, Spatial Pattern and Driving Mechanisms of the Aeolian Desertification in the Alxa Plateau from 1975 to 2015

Wan Wei1,2, Yan Changzhen1, Xiao Shengchun1, Xie Jiali1, Qian Dawen1,2   

  1. 1. Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-10-10 Revised:2017-12-10 Online:2018-01-20 Published:2018-01-20

Abstract: A total of 7 dataset were obtained about genetic types and degree of aeolian desertification in 1975, 1990, 1995, 2000, 1995, 2010 and 2015 in the Alxa Plateau using Remote Sensing (RS) images and Geographic Information System (GIS). We analyzed the genetic types, area and spatial distribution changing about degree of aeolian desertification in the Alxa Plateau in recent 40 years. And we investigated aeolian desertification degree in the Alxa Plateau with aeolian desertification index (ADI) quantificationally, which suggested that it was deteriorative before 2000 and then began to take a favorable turn after 2000. Besides, the spatial variation patterns about the different types of aeolian desertification was investigated by the model of center of gravity migration, and the hotspots distribution of aeolian desertification dynamics by overlay analysis in the Alxa Plateau. Finally, natural and human driving factors were quantified and identified with principal component analysis (PCA). The results showed that in recent 40 years (especially since 2000), human factors, including population pressure, animal husbandry and cultivation, afforestation, industrial and mining exploitation, were major driving factors influencing the aeolian desertification dynamics in the Alxa Plateau. Another critical driver was climate change (rainfall, temperature and the maximum wind speed) in this region.

Key words: Alxa Plateau, aeolian desertification, driving mechanism, remote sensing monitoring, process and pattern

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