摘要
悬浮泥沙作为重要水质参数,其分布和动态变化对河口及近岸的生态、环境、物质循环等都具有深远的影响。我国静止轨道高分四号(GF-4)卫星数据具有高时间和高空间分辨率的观测优势,在水色遥感上具有重大应用潜力。为探究GF-4卫星对悬浮泥沙浓度的监测能力,本文以杭州湾为研究区,构建反演模型,利用静止海洋水色成像仪进行交叉验证。结果表明,以GF-4卫星第5和第4波段遥感反射率的比值作为遥感因子建立的反演模型精度较高,决定系数为0.92,均方根误差为223.2 mg/L,平均相对误差为17.2%。交叉验证结果显示,GF-4卫星作为一种新的遥感数据源,在低浓度区与静止海洋水色成像仪反演悬浮泥沙浓度分布相似,但在高浓度区的差异随浓度增高而增大,总体可满足中国大部分海区的监测需求。
As an important water quality parameter,the distribution and dynamic change of suspended sediment have a profound impact on the ecology,environment and material circulation of the estuary and the near shore.GF-4 satellite has the ability to observe at any time,can quickly provide a large number of observation data,and has the application potential in water color remote sensing.In order to explore the monitoring effect of GF-4 satellite on suspended sediment in water,takes the Hangzhou Bay as the research area in this paper,constructs suspended sediment concentration inversion model,and uses GOCI satellite to cross verify.The results show that the index model established by using the ratio of remote sensing reflectance of the 5th and 4th band of GF-4 as the remote sensing factor has a high inversion accuracy,with a determination coefficient of 0.92,a root mean square error of 273.6 mg/L and an mean relative error of 17.2%.The cross-validation results show that GF-4 satellite data,as a new remote sensing data source,is similar to the distribution of GOCI satellite inversion suspended sediment concentration in the low concentration region,but the difference increases with the increase of concentration in the high concentration region.The research shows that GF-4 satellite is suitable for high precision inversion in the waters with low suspended sediment concentration and can be applied in most marine areas of China.
作者
邵宇杰
胡越凯
周斌
陈芳
何贤强
王国军
袁小红
周亚丽
于之锋
Shao Yujie;Hu Yuekai;Zhou Bin;Chen Fang;He Xianqiang;Wang Guojun;Yuan Xiaohong;Zhou Yali;Yu Zhifeng(Institute of Remote Sensing and Earth Sciences,Hangzhou Normal University,Hangzhou 311121,China;State Key Laboratory of Estuarine and Coastal Research,East China Normal University,Shanghai 200241,China;State Key Laboratory of Surveying,Mapping and Remote Sensing Information Engineering,Wuhan University,Wuhan 430079,China;Fisheries Big Data Center of South China Sea,Zhanjiang 524006,China;Laboratory of Target Microwave Properties,Deqing Academy of Satellite Applications,Deqing 313200,China;Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change,Hangzhou 311121,China)
出处
《海洋学报》
CAS
CSCD
北大核心
2020年第9期134-142,共9页
基金
南方海洋科学与工程广东省实验室(湛江)(湛江湾实验室)项目(ZJW-2019-08)
国家重点研发计划(2016YFC1400906,2016YFC1401008)
国家自然科学基金(41206169)
浙江省微波目标特性测量与遥感重点实验室开放基金(2018KF03)。