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黄河源区规范差异植被指数的时空模式和预测模型

Wei Liu^1,2, Teng-Fei Cao^1,3, Fu-Xin Yu¹

¹School of Computer Technology and Application, Qinghai University, Xining 810016, China.

Ying yong sheng tai xue bao = The journal of applied ecology

|September 1, 2025

概括

黄河源区的植被呈现显著增长,从2000年到2020年增长了18.9%. 风速,降水和温度是正常化差异植被指数 (NDVI) 变化的关键驱动因素.

科学领域:

生态学
环境科学
遥感技术

背景情况:

黄河源区是黄河流域的一个重要生态障碍.
它在节水,气候调节和生物多样性保护方面发挥着至关重要的作用.

研究的目的:

分析2000年至2020年黄河源区规范差异植被指数 (NDVI) 的时空变化和驱动机制.
构建NDVI变化的预测模型.

主要方法:

集成的MODIS遥感图像,气象,水文和地形数据.
采用Sen斜率方法,部分相关性分析,方差通胀因子分析,相互作用检测,随机森林和地理加权随机森林模型.

主要成果:

在2000年至2020年期间,年NDVI显著增加18.9% (0.0028·a-1) 从0.3301增加到0.3924.
从西北到东南, NDVI 的增长趋势明显.
风速,降水和最低温度被确定为NDVI变化的主要驱动因素,具有复杂的相互作用.

结论:

地理加权的随机森林模型在预测NDVI方面显著优于随机森林模型,达到R²=0.976.
这突显了该模型在捕捉空间异质性和本地驱动机制方面的有效性.
这项研究为黄河源区的植被动态及其驱动因素提供了宝贵的见解.

关键词:

黄河源区地理加权随机森林标准化差异植被指数空间异质性

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