摘要
黄河流域是我国重要的生态安全屏障,受气候变化、地理条件以及人类活动等多重因素的影响,依然面临植被退化、水土流失等严重的生态问题。为系统评估黄河流域植被覆盖的变化趋势及其驱动机制,基于Google Earth Engine(GEE)平台,利用MODIS13 Q1数据集获取2000—2020年黄河流域归一化植被指数(NDVI);采用Theil-Sen趋势分析和Mann-Kendall突变检验方法,对流域内11个生态功能区的NDVI时空变化趋势进行分析,同时结合气象、地形和地貌因素,应用提升回归树模型,定量评估各因子对植被变化的驱动作用。结果表明:(1)2000—2020年,黄河流域NDVI整体呈上升趋势,空间分布表现为东南部较高、西北部较低的格局。NDVI波动范围为-0.12~0.61,均值为0.28。部分NDVI小于0的区域主要分布在过度放牧和干旱频发的地区,存在植被退化的风险。(2)11个生态功能区均出现1个或2个显著的突变点,且这些突变点均出现在2018年之前。全流域NDVI改善区域面积占比为85.22%,保持稳定区域面积占比为9.08%,退化区域面积占比为5.70%。(3)驱动力分析表明,气候因素对NDVI变化的影响最大,其中降水的贡献率高于气温,地形因素(如海拔、坡度、坡向)及人口密度的贡献率次之。
The Yellow River basin serves as a critical ecological security barrier in China but remains threatened by vegetation degradation and soil erosion under the combined influences of climate change,geographical conditions,and human activities.To systematically assess trends in vegetation coverage and their driving forces,this study obtained the NDVI for 200o—2020 from the MOD13Q1 product on the Google Earth Engine(GEE)platform,analyzed spatiotemporal trends across 11 ecological functional zones using Theil-Sen slope estimation and the Mann-Kendall test for abrupt changes,and quantified the contributions of meteorological,topographic,geomorphological,and demographic factors with a Boosted Regression Tree(BRT)model.Results show that:①NDVI exhibited an overall increasing trend from 2000 to 2020,with higher values in the southeast and lower values in the northwest.The annual median NDVI ranged from—0.12 to 0.61,with a basin-wide mean of 0.28.Areas with NDVI<0 were concentrated in regions experiencing overgrazing and frequent drought,indicating a risk of vegetation degradation.②Each ecological functional zone displayed one or two significant change points,all occurring before 2018.Across the basin,areas with improving NDVI accounted for 85.22%,stable areas for 9.08%,and degrading areas for 5.70%.③Climatic factors were the dominant drivers of NDVI change,with precipitation contributing more than temperature;topographic factors(elevation,slope,aspect)and population density ranked next.These findings provide essential data support and scientific evidence for ecological conservation and vegetation management in the Yellow River basin.
作者
张新
田佳
王逸飞
马乐鹏
Zhang Xin;Tian Jia;Wang Yifei;Ma Lepeng(School of Forestry and Grassland Science,Ningxia University,Yinchuan 750021,China)
出处
《农业科学研究(中英文)》
2026年第1期20-30,共11页
Journal of Agricultural Sciences
基金
宁夏自然科学基金项目(2024AAC03089)
宁夏重点研发计划项目(2023BEG02039)
大学生创新创业项目(G202310749034)。
关键词
黄河流域
归一化植被指数(NDVI)
提升回归树分析
GEE云平台
Yellow River basin
normalized difference vegetation index(NDVI)
Boosted Regression Tree(BRT)analysis
Google Earth Engine
