Author
Listed:
- Xinyang Ji
(China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China)
- Jinzhong Yang
(China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China)
- Jianyu Liu
(China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China)
- Xiaomin Du
(China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China)
- Wenkai Zhang
(China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China)
- Jiafeng Liu
(China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China)
- Guangwei Li
(China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China)
- Jingkai Guo
(China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China)
Abstract
Desertification is one of the most critical environmental and socioeconomic issues in the world today. Located in the transitional region between the desert and the Loess Plateau, the Mu Us Sandy Land is one of the nine most environmentally sensitive areas in the world. Remote sensing provides an effective technical method for desertification monitoring. In order to analyze the spatiotemporal distribution of desertification in the Mu Us Sandy Land from 1991 to 2021, the “MSAVI-Albedo” model was employed to extract desertification data in 1991, 2002, 2009 and 2021. The clustering characteristics of desertification were analyzed based on Moran’s I statistic. Subsequently, the driving forces in desertification changes were investigated using a geographical detector to analyze the influence of soil, meteorology, and topography on desertification. Additionally, the impact of meteorological and human factors on desertification change in the Mu Us Sandy Land was assessed. From 1991 to 2021, the degree of desertification of the Mu Us Sandy Land showed an overall decreasing trend, and the percentage of land classified as undergoing extremely severe, severe, moderate and mild desertification was improved by 86.11%, 81.82%, 52.5% and 37.42%, respectively. The proportion of land classified as undergoing extremely severe desertification decreased from 29.22% to 5.62%, and the proportion of land undergoing no desertification increased from 4.16% to 18.33%. At the same time, the desertification center shifted westward, and the desertification distribution showed a clustering trend. It is known that different factors affect the formation and distribution of desertification in the Mu Us Sandy Land in the following order: soil, meteorology, and topography. Over the past 30 years, the mean annual temperature and annual precipitation increased at rates of 0.01871 °C/a and 1.0374 mm/a, respectively, while the mean annual wind speed decreased at a rate of 0.00945 m/s·a. These changes provided more favorable natural conditions for vegetation growth and sand fixation. Human factors, such as economic development, agriculture and animal husbandry practices, and the policy of returning farmland to forest (grassland) also had a significant impact on the desertification process, leading to a year-by-year improvement in the ecological environment of the Mu Us Sandy Land.
Suggested Citation
Xinyang Ji & Jinzhong Yang & Jianyu Liu & Xiaomin Du & Wenkai Zhang & Jiafeng Liu & Guangwei Li & Jingkai Guo, 2023.
"Analysis of Spatial-Temporal Changes and Driving Forces of Desertification in the Mu Us Sandy Land from 1991 to 2021,"
Sustainability, MDPI, vol. 15(13), pages 1-17, July.
Handle:
RePEc:gam:jsusta:v:15:y:2023:i:13:p:10399-:d:1184775
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Citations
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Cited by:
- Weiyi Lu & Geer Teni & Huishi Du, 2024.
"Vegetation–Lake–Sand Landscape of Northeast China Sandy Land between 1980 and 2022: Pattern, Evolution, and Driving Forces,"
Sustainability, MDPI, vol. 16(8), pages 1-18, April.
- Changfu Tong & Hongfei Hou & Hexiang Zheng & Ying Wang & Jin Liu, 2024.
"A Coupled Model for Forecasting Spatiotemporal Variability of Regional Drought in the Mu Us Sandy Land Using a Meta-Heuristic Algorithm,"
Land, MDPI, vol. 13(11), pages 1-22, October.
- Jiaying Li & Yu Li & Xuhui Wang & Zhongxu Ma, 2024.
"Exploring the Spatial-Temporal Patterns, Drivers, and Response Strategies of Desertification in the Mu Us Desert from Multiple Regional Perspectives,"
Sustainability, MDPI, vol. 16(21), pages 1-28, October.
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