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ZHEN H, WANG Y, XIA T T, WANG Y, ZHANG Z C. Spatiotemporal distribution and driving force analysis of fractional vegetation cover in the Kaidu-Kongqi River Basin using the Geodetector model. Pratacultural Science, 2023, 40(5): 1140-1153. doi: 10.11829/j.issn.1001-0629.2022-0605
Citation: ZHEN H, WANG Y, XIA T T, WANG Y, ZHANG Z C. Spatiotemporal distribution and driving force analysis of fractional vegetation cover in the Kaidu-Kongqi River Basin using the Geodetector model. Pratacultural Science, 2023, 40(5): 1140-1153. doi: 10.11829/j.issn.1001-0629.2022-0605

Spatiotemporal distribution and driving force analysis of fractional vegetation cover in the Kaidu-Kongqi River Basin using the Geodetector model

  • Fractional vegetation cover is an evaluation index that reflects the quality of the ecological environment. The systematic study of changes in vegetation cover and driving mechanisms is crucial for regional ecological management. Based on MODIS data, this study uses Sen + Mann-Kendall trend analysis, a geographical detector (Geodetector) model, and other methods to analyze the evolutionary trend of vegetation coverage in the Kaidu-Kongqi River Basin in Xinjiang, China. It also explores the spatial correlation between vegetation coverage and driving factors and identifies the dominant factor. The results indicate that: 1) From 2000 to 2020, the vegetation coverage in the Kaidu-Kongqi River Basin was trending upward (0.013·10a–1). The mean coverage fluctuated slightly prior to 2011 and then continued to increase, reaching a maximum value of 29.0% in 2019. Spatially, in 2020, the distribution of extremely low vegetation coverage was the broadest, accounting for 51.93% of the study area. This represents a decrease of 5 010.31 km2 over a 21 year period, while high vegetation coverage accounted for 22.84% of the study area. 2) The conversion from extremely low to low vegetation coverage was dominant in the Kaidu-Kongqi River Basin. There was a slight improvement in the vegetation trend, with 17.82% of the study area showing an extremely significant increased trend, while 71.9% showed non-significant or no change trend. 3) The vegetation coverage is mainly affected by elevation and land use type, and its explanatory power is above 0.45. The synergistic effect between two factors was significantly higher than that of a single factor, and the explanatory power of the intersection between elevation and land use type was the highest at 0.743.
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