摘要
近年来,一些湖泊、河流频繁发生蓝藻水华问题,相关研究也日益增多。基于2021年9月26日湘江蓝藻水华监测数据和Sentinel-3影像,以总藻密度为研究对象,采用相关系数法和BP(Back Propagation)神经网络法,确定b17/b14波段组合为特征波段,构建湘江蓝藻水华定量反演模型。该模型的回归值为0.95465,均方根误差为244×10^(4)个/L,纳什效率系数为0.90,模型较为可信。验证结果表明:该模型对于总藻密度为1200×10^(4)~5000×10^(4)个/L的水华反演适用性较好,80%的验证点反演相对误差绝对值小于60%;与MCI(Maximum Chlorophyll Index)法识别的水华结果对比,湘江各江段水华识别一致率均在80%以上,长沙段、岳阳段的水华识别一致率超过90%。因此,该模型可用于湘江水华区域的水华定量反演。
In recent years,the frequent occurrence of cyanobacterial blooms in some lakes and rivers has led to an increasing amount of related research.Based on the cyanobacterial bloom monitoring data of the Xiangjiang River on September 26,2021 and Sentinel-3 satellite images,taking the total algae density as the research object,the b17/b14 ratio band combination is determined as the feature band,and a quantitative inversion model for cyanobacterial blooms in the Xiangjiang River is constructed using the correlation coefficient method and Back Propagation(BP)neural network method.The regression value(R)of the model is 0.95465,the root mean square error is 244×10^(4) cells/L,and the Nash efficiency coefficient is 0.90,indicating that the model is relatively reliable.The validation results show that the model is suitable for the inversion of cyanobacterial blooms with total algae density between 1200×10^(4) cells/L and 5000×10^(4) cells/L,with a relative error of less than 60%for 80%of the validation points.Compared with the results obtained by Maximum Chlorophyll Index(MCI),the consistency rate of cyanobacterial bloom in all sections of the Xiangjiang River is above 80%,and the consistency rate in Changsha and Yueyang sections was above 90%.It indicates that the model can be used for the quantitative inversion of cyanobacterial blooms in the Xiangjiang River.
作者
胡月红
张屹
赵芳
郭晶
谭菊
陈军
高吉权
HU Yuehong;ZHANG Yi;ZHAO Fang;GUO Jing;TAN Ju;CHEN Jun;GAO Jiquan(Technical Centre for Soil,Agriculture and Rural Ecology and Environment,Ministry of Ecology and Environment,Beijing 100012,China;Ecological and Environmental Monitoring Center of Dongting Lake of Hunan Province,Yueyang 414000,China;Changsha Ecological and Environmental Monitoring Center of Hunan Province,Changsha 410001,China)
出处
《中国环境监测》
CAS
CSCD
北大核心
2024年第6期239-248,共10页
Environmental Monitoring in China
基金
2021年湖南省环保科研课题(HBKT-2021026)。
关键词
蓝藻水华
总藻密度
Sentinel-3
神经网络
定量遥感
湘江
cyanobacterial bloom
total algal density
Sentinel-3
neutral network
quantitative remote sensing
the Xiangjiang River
