2013—2023年三峡库区植被覆盖度时空变化及其驱动力————以湖北省巴东县为例
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S127,Q948.2

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水利部重大科技项目“三峡库区河流湿地‘碳汇’潜力评价研究”(SKS-2022082)


Spatiotemporal variations and driving forces of vegetation coverage in Three Gorges reservoir area during 2013—2023———A case study at Badong County, Hubei Province
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    [目的] 分析三峡库区湖北省巴东县植被覆盖度时空变化及其驱动机制,为该区植被恢复水土保持和生态保护提供科学参考。[方法] 基于MODIS NDVI数据,分析2013—2023年巴东县植被覆盖度时空变化规律,探讨基于地形、地质、气候等影响因子的植被覆盖度分异特征,并运用地理探测器和随机森林模型探究主导因子及交互效应。[结果] ①2013—2023年,巴东县植被覆盖度整体较高,以0.001 7/a的速率呈波动增长趋势;②基于不同影响因子的植被覆盖度分异特征明显,植被覆盖度与高程、坡度、年降水量分布变化呈正相关,与年均气温负相关,且受坡向、地层岩性、植被类型、土壤类型等因子影响; ③通过地理探测器探测到高程、年均气温为主要驱动因子,解释力均在40%以上,地层岩性、地貌类型、年降水量为次级因子,且多因子交互表现为协同增强效应,高程与地层岩性的联合解释力达到55%;随机森林模型进一步验证了主导因子重要性排序:高程>年均气温>地层岩性>年降水量。[结论] 地理探测器与随机森林模型共同揭示高程为2013—2023年三峡库区巴东县植被覆盖度核心驱动因子,年均气温、地层岩性、年降水量次之。

    Abstract:

    [Objective] The spatiotemporal variations of vegetation coverage and its driving mechanisms at Badong County, Hubei Province, Three Gorges reservoir area were analyzed, in order to provide scientific references for vegetation restoration, soil and water conservation, and ecological protection. [Methods] Based on MODIS NDVI data, the spatiotemporal dynamics of fractional vegetation coverage in Badong County from 2013 to 2023 was analyzed and the differentiation characteristics of vegetation coverage influenced by topography, geology, and climate factors was explored. Furthermore, the geodetector and random forest models were employed to identify dominant factors and their interaction effects. [Results] ① From 2013 to 2023, vegetation coverage at Badong County exhibited a fluctuating upward trend at a rate of 0.001 7/a, with overall high coverage levels. ② Vegetation coverage showed distinct spatial differentiation across influencing factors: it correlated positively with the spatial variation of elevation, slope, and annual precipitation, but negatively with mean annual temperature. It was also influenced by aspect, lithology, vegetation type, and soil type. ③ Geodetector analysis identified elevation and mean annual temperature as primary drivers (explanatory power >40%), while lithology, geomorphological type, and annual precipitation were secondary factors. Multi-factor interactions demonstrated synergistic enhancement, with elevation and lithology jointly explaining 55% of variation. Random forest model further validated the importance ranking of dominant predictors: elevation > mean annual temperature > lithology > annual precipitation. [Conclusion] The geodetector and random forest model jointly reveal elevation as the core driver of fractional vegetation coverage changes at Badong County in Three Gorges reservoir area during 2013—2023, followed by mean annual temperature, lithology, and precipitation.

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丁凡桠,史超,李书.2013—2023年三峡库区植被覆盖度时空变化及其驱动力————以湖北省巴东县为例[J].水土保持通报,2025,45(5):421-432

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  • 收稿日期:2025-04-28
  • 最后修改日期:2025-06-13
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  • 在线发布日期: 2025-11-07
  • 出版日期: 2025-10-18