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Abstract
Exploring vegetation dynamics in arid areas and their responses to different natural and anthropogenic factors is critical for understanding ecosystems. Based on the monthly MOD13Q1 (250 m) remote sensing data from 2000 to 2019, this study analyzed spatio-temporal changes in vegetation cover in the Aksu River Basin and predicted future change trends using one-dimensional linear regression, the Mann–Kendall test, and the Hurst index. Quantitative assessment of the magnitude of anthropogenic and natural drivers was performed using the Geodetector model. Eleven natural and anthropogenic factors were quantified and analyzed within five time periods. The influence of the driving factors on the changes in the normalized difference vegetation index (NDVI) in each period was calculated and analyzed. Four main results were found. (1) The overall vegetation cover in the region significantly grew from 2000 to 2019. The vegetation cover changes were dominated by expected future improvements, with a Hurst index average of 0.45. (2) Land use type, soil moisture, surface temperature, and potential vapor dispersion were the main drivers of NDVI changes, with annual average q-values above 0.2. (3) The driving effect of two-factor interactions was significantly greater than that of single factors, especially land use type interacts with other factors to a greater extent on vegetation cover. (4) The magnitude of the interaction between soil moisture and potential vapor dispersion and the magnitude of the interaction between anthropogenic factors and other factors showed an obvious increasing trend. Current soil moisture and human activities had a positive influence on the growth of vegetation in the area. The findings of this study are important for ecological monitoring and security as well as land desertification control.
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1 Hebei GEO University, School of Water Resources and Environment, Shijiazhuang, China (GRID:grid.443566.6) (ISNI:0000 0000 9730 5695); Hebei Province Key Laboratory of Sustained Utilization and Development of Water Resources, Shijiazhuang, China (GRID:grid.443566.6); Hebei Province Collaborative Innovation Center for Sustainable Utilization of Water Resources and Optimization of Industrial Structure, Shijiazhuang, China (GRID:grid.443566.6); Hebei Center for Ecological and Environmental Geology Research, Shijiazhuang, China (GRID:grid.443566.6)
2 Hebei GEO University, School of Water Resources and Environment, Shijiazhuang, China (GRID:grid.443566.6) (ISNI:0000 0000 9730 5695); Hebei Province Key Laboratory of Sustained Utilization and Development of Water Resources, Shijiazhuang, China (GRID:grid.443566.6); Hebei Province Collaborative Innovation Center for Sustainable Utilization of Water Resources and Optimization of Industrial Structure, Shijiazhuang, China (GRID:grid.443566.6); Hebei Center for Ecological and Environmental Geology Research, Shijiazhuang, China (GRID:grid.443566.6); Hebei GEO University, School of Water Resources and Environment, Shijiazhuang, People’s Republic of China (GRID:grid.443566.6) (ISNI:0000 0000 9730 5695)