In order to accurately invert the concentration of chlorophyll a in water,taking the eastern branch of Huangbai River as a case,the STNLFFM space-time fusion algorithm was used to fuse the reflectance data of GF-4 and Sentinel-2 in 2017 to reconstruct the time series data of Sentinel-2 image.A multiple linear regression model was established for the response relation-ship between water quality parameters and spectral characteristics obtained before and after the application of the algorithm,and the prediction effect of the model on chlorophyll a was compared to verify the feasibility of the space-time fusion algorithm.The artificial neural network model was established by using the response relationship between the reconstructed image spectral charac-teristics and water quality parameters to invert the chlorophyll a concentration of each reservoir in the eastern branch of Huangbai River in 2017.The results show that the image generated by the spatio-temporal fusion algorithm is close to the real image,which improves the effect of multiple linear regression model to predict chlorophyll a.The R2 is increased from 0.659 before fu-sion to 0.844 after fusion,and the artificial neural network model based on the water quality parameters-spectral relationship ob-tained by the spatio-temporal fusion algorithm has better simulation accuracy.The R2 and MRE reach 0.925 and 9.461％,and the spatial difference of retrieved chlorophyll a concentration is obvious.It is proved that the spatio-temporal fusion algorithm has a good application prospect in the process of water quality parameter inversion.
关键词
STNLFFM时空融合算法/黄柏河/人工神经网络/水质反演/叶绿素a
Key words
STNLFFM spatio-temporal fusion algorithm/Huangbai River/artificial neural network/water quality inversion/chlorophyll a
维普
万方数据