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 244×104 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 1200×104 cells/L and 5000×104 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.
关键词
蓝藻水华/总藻密度/Sentinel-3/神经网络/定量遥感/湘江
Key words
cyanobacterial bloom/total algal density/Sentinel-3/neutral network/quantitative remote sensing/the Xiangjiang River
维普
万方数据