基于Sentinel-2遥感数据的上海市河道水质参数反演研究

由于上海市河湖水网密布，科学有效地监测河湖水质，有利于巩固河湖治理成果，为新形势下水资源的保护和管理服务。研究目的是实现卫星遥感技术在城市水体水质监测中的有效应用。基于Sentinel-2多光谱影像，采用机器学习技术建立了城市河流水质参数反演模型，对2019~2021年上海市103条河流的溶解氧(Dissolved Oxygen, DO)、高锰酸盐指数(Permanganate index, CODMn)、氨氮(Ammonia Nitrogen, NH3-N)和总磷(Total Phosphorus, TP) 4种水质参数进行了遥感反演。分析了上海市主要河流水质参数的时空变化特征，并对上海市水环境进行了评价。结果表明，DO、CODMn和TP三个水质指标的反演精度优于80%，NH3-N的反演精度优于70%；4种水质参数所属水体类别均优于V类；第一、第四季度水质优于第二、第三季度。

Research on Retrieval of Water Quality Parameters in Rivers of Shanghai Based on Sentinel-2 Remote Sensing Data

Due to the dense network of rivers and lakes in Shanghai, scientific and effective monitoring of river and lake water quality is conducive to consolidating the achievements of river and lake management, and serving for the protection and management of water resources in the new situation. The purpose of this paper is to make satellite remote sensing technology be applied effectively in urban water quality monitoring. The research methods are as follows: Based on Sentinel-2 multi-spectral images, an inversion model of urban river water quality parameters is established by using machine learning technology. Dissolved oxygen, permanganate index, ammonia nitrogen and total phosphorus of 103 rivers in Shanghai from 2019 to 2021 are inverted by remote sensing, and the spatio-temporal variation characteristics of water quality parameters of main rivers in Shanghai are analyzed. The water environment of Shanghai is evaluated. The results show that the inversion accuracy of DO, CODMn and TP is better than 80%, and the inversion accuracy of NH3-N is better than 70%. The four water quality parameters are better than that of class V, and the water quality in the first and fourth quarters is better than that in the second and third quarters.