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盐度是重要的物理海洋参数,会影响海洋许多过程。基于渤海实测的海表盐度和MERIS卫星获取的遥感反射率数据,建立并检验了一种多元线性模型和人工神经网络模型。经检验,两种模型的反演均方根误差分别为0.858psu和0.689psu(psu为实用盐度单位),对应的相关系数分别为R2=0.81和R2=0.82。将模型应用于MERIS遥感数据,获取了渤海海表盐度图,能够体现渤海海表盐度的空间分布情况。两种模型均可适用于多光谱遥感数据。
Salinity is an important physical ocean parameter that affects many processes in the oceans. Based on the sea surface salinity measured by the Bohai Sea and the remote sensing reflectance data acquired by the MERIS satellite, a multivariate linear model and an artificial neural network model were established and tested. After verification, the RMSE of the two models are 0.858psu and 0.689psu respectively (psu is the practical salinity unit), and the corresponding correlation coefficients are R2 = 0.81 and R2 = 0.82 respectively. Applying the model to MERIS remote sensing data, we obtained the sea surface salinity map of the Bohai Sea, which can reflect the spatial distribution of salinity in the Bohai Sea. Both models are suitable for multispectral remote sensing data.