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基于知识和遥感图像的神经网络水质反演模型

DOI: 10.11834/jig.20060486

Keywords: 遥感图像,水质反演,BP神经网络,知识

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Abstract:

为进一步提高遥感图像水质反演的精度,提出了一种基于知识和遥感图像相结合的神经网络水质反演模型。该模型利用遥感图像数据以及与水质相关的知识数据作为BP神经网络的输入,经训练后,确定神经网络的结构,在训练好的BP神经网络基础之上对水质进行反演。以中国太湖为例进行实证研究,实验中,使用的知识数据包括太湖的地理信息知识和先对太湖TM图像上的水域解译进而对水质进行分类的知识。实验结果表明,本文提出的水质反演模型较常规的线性回归模型和传统的神经网络模型有更高的反演精度。

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