首页|基于Landsat 8 OLI的东圳水库水质参数反演研究

基于Landsat 8 OLI的东圳水库水质参数反演研究

扫码查看
遥感技术是监测内陆水体水质的有效手段,东圳水库是莆田市水源地,为了对水质进行实时监测,了解其空间分布情况,本文基于Landsat 8 OLI遥感影像,结合124个采样点实测获得的Chl-a、浊度、COD浓度分别构建统计回归模型、BP神经网络模型、XGBoost模型,并采用R2、MAE、RMSE进行精度检验.结果表明BP神经网络模型效果优于统计回归模型,R2均大于0.9,但存在过拟合现象;XGBoost模型可以有效防止过拟合,表现出较强的拟合能力和较高的预测精度.
Inversion of Water Quality Parameters in Dongzhen Reservoir Based on the Landsat 8 OLI
Remote sensing technology is an effective method for monitoring the water quality of inland water.Dongzhen Reservoir serves as the water source for Putian City.In order to achieve real-time water quality monitoring and understand its spatial distribution,this paper is based on Landsat 8 OLI remote sensing images,in combination with measurements of Chl-a,Turbidity,and COD concentrations from 124 sampling points.Statistical regression models,BP neural network models,and XGBoost models were constructed and evaluated using precision tests such as R2,MAE,and RMSE.The results indicate that the BP neural network model outperforms the statistical regression model with an R2 value exceeding 0.9,albeit with some risk of overfitting.On the other hand,the XGBoost model effectively mitigates overfitting,demonstrating robust fitting capabilities and high predictive accuracy.

Landsat 8 OLIwater quality parametersBP neural network modelXGBoost model

何欢、陈文惠、张忠婷

展开 >

福建师范大学地理科学学院,福建福州

Landsat 8 OLI 水质参数 BP神经网络模型 XGBoost模型

福建省科技计划项目福建省环保科技计划项目

2020Y00702022R001

2024

科学技术创新
黑龙江省科普事业中心

科学技术创新

影响因子:0.842
ISSN:1673-1328
年,卷(期):2024.(1)
  • 4