基于环境小卫星的凌河叶绿素a浓度定量反演

Quantitative Retrieval of Chlorophyll?A by Remote Sensing in Linghe River Based on HJ?1BData

利用遥感技术对河流水质环境进行监测评价,实现河流水质的实时同步监测。以辽宁省大凌河朝阳市区段为研究对象,在获取实地监测数据和HJ-1B遥感影像的基础上,建立比值线性回归模型和模糊控制RBF神经网络模型,对水质参数叶绿素a浓度进行定量反演。试验表明,模糊控制RBF神经网络模型的叶绿素a浓度反演结果和精度明显好于线性模型,为凌河水质监测提供了一种较好的方法。

In this study, the river water quality ＆ environmental is monitored and assessed by using remote sensing technology to a chieve the real-time river water quality monitoring. Taking the Chaoyang City reach of Linghe River in Liaoning Province as studying object, based on the field monitoring data and HJ-1B remote sensing data, this study sets up a linear regression model and fuzzy con trol RBF neural network model to quantitatively reverse the concentration of Chlorophyll A. The experiment result shows that the application of fuzzy control RBF neural network for inversing water quality parameters is effective, its retrieving results is much better than the linear regression model. It provides a good method for water monitoring in Linghe River.