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城市湿地微塑料的增强时空地图:使用卫星图像和有限样本的可解释的CNN-GRU方法

Jiongji Xu¹, Jie Jiang¹, Zhaoli Wang²

¹School of Civil Engineering and Transportation, State Key Laboratory of Subtropical Building and Urban Science, South China University of Technology, Guangzhou 510641, China.

Ecotoxicology and environmental safety

|September 12, 2025

概括

这项研究使用卫星遥感和CNN-GRU模型来绘制城市湿地中的微塑料 (MP) 污染. 结果显示,湿地中的MP积累率高于水库,藻类生物量作为潜在指标.

科学领域:

环境科学环境科学
遥感遥感遥感遥感
数据科学数据科学数据科学

背景情况:

微塑料 (MP) 是城市地表水中的新兴污染物,对生态系统和人类健康构成风险.
了解国会议员的时空分布对于有效管理至关重要.
有限的现场数据对全面的PM污染评估构成了挑战.

研究的目的:

利用卫星遥感 (SRS) 数据开发一种可解释的模型,用于分析城市湿地中的微塑料污染.
调查在广州的北排水盆地的MPs的时空分布特征.
以有限的现场样本评估基于SRS的MP映射的可行性.

主要方法:

构建一个可解释的卷积神经网络通道循环单元 (CNN-GRU) 模型.
将卫星遥感 (SRS) 数据与有限的现场样本集成.
应用夏普利添加式解释 (SHAP) 模型解释性和远程传感指数 (RSI) 分析.

主要成果:

在预测MP度方面,CNN-GRU模型实现了高精度 (R2 = 0.9526).
近红外光谱带被确定为关键预测因素,与藻类含量相关.
城市湿地显示了比水库更高的MP积累,夏季峰值.

结论:

在城市湿地中基于SRS的MP的时空映射是可行的,即使样本有限.
可解释的深度学习模型,如CNN-GRU,通过SHAP进行增强,提高了MP污染评估的可信度.
藻类生物量可以作为城市湿地中MP积累的代理,尽管这种关系在各个生态系统之间可能有所不同.

关键词:

美国有线电视新闻网-GRU 可以解释的可解释.微塑料是一种微塑料.卫星遥感卫星遥感卫星遥感时间空间绘制地图.

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