Journal: Ecological Environment and Protection DOI: 10.32629/eep.v9i5.3203
Abstract
以渭河流域甘陕段2001—2020年MOD13A2 NDVI数据为基础,运用经验正交函数(EOF)分解识别植被变化主导空间模态,结合GLC 30三期土地利用数据划分强、弱人类活动干扰区,构建统一归因空间框架。在该框架 下并行运行线性残差归因(RESTREND)和3D- UNet深度学习非线性归因两条路径,定量评估气候变化与人类活动的相对贡献,系统 对比两种方法的归因差异。结果表明：(1)研究时段内流域NDVI累计增幅36.26%,十 年倾向率12.57%/10a,渭北—陇东黄土丘陵区改善最为集中,关中城市带局部退化；( 2)EOF第一模态方差贡献率86.3%,正异常区与退耕还林还草工程重点区高度吻合；( 3)线性归因显示强、弱干扰区人类活动贡献率分别为86.18%和86.71%,差距不足1%； (4)非线性归因结果分别为93.77%和96.60%,较线性结果系统偏高7—10%,揭示非线性 模型能更充分捕捉气候因子与植被的复杂响应关系。
Keywords
渭河流域；NDVI；EOF分析；线性残差归因；3D-UNet；植被恢复
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