基于无人机多光谱影像和XGBoost模型的城市河流水质参数反演

Inversion of Urban River Water Quality Parameters Based on UAV Multi-spectral Imagery and XGBoost Model

为建立针对城市河流水质参数稳定且准确的无人机遥感反演模型,以邯郸市境内滏阳河5个河段为研究样区,基于三期无人机多光谱影像和水体氨氮浓度实测数据,构建了4种数学统计模型与XGBoost模型,并在模型验证和评价的基础上选取最优模型对研究区氨氮浓度进行时空分布反演及分析。结果表明:①XGBoost模型反演效果优于数学统计模型,决定系数、均方根误差、平均绝对百分比误差整体优于数学统计模型,表现出较强的拟合能力和较高的预测精度;②无人机遥感反演技术适用于城市河流氨氮浓度反演,多光谱数据B1波段在建模中起关键作用;③邯郸市滏阳河流域各河段的整体氨氮浓度依次为2020年12月>2020年8月>2021年5月,呈现出一定的季节性差异特征。

To establish a stable and accurate UAV remote sensing inversion model for urban river water quality parameters,the study takes five reaches of Fuyang River in Handan as the study sample area,and constructs four mathematical statistical models and XGBoost model based on the three phases UAV multispectral images and measured data of ammonia nitrogen concentration in water.And the optimal model is selected to analyze the spatial-temporal distribution of ammonia nitrogen concentration in the study area on the basis of model verification and evaluation.The results indicate that the inversion effect of XGBoost model is better than that of mathematical statistical model,and the XGBoost model accuracy evaluation indicators of R^(2),RMSE and MAPE re generally better than mathematical statistical models and the XGBoost model shows strong fitting ability and high prediction accuracy;the UAV remote sensing inversion technology is applicable to the ammonia nitrogen concentration inversion of urban rivers,and the B1 band of multispectral data plays a key role in the model.The overall ammonia nitrogen concentration of each reach of Fuyang River Basin in Handan was from high to low in December 2020,August 2020 and May 2021,and it exhibited certain seasonal differences.