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An Inversion Method of Remote Sensing Water Depth Based on Transmission Bands Ratio

机译:基于传输带比的遥感水深反演方法

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The water depth inversion of shallow reefs plays an important role for marine safety, marine engineering and marine military. The IKONOS satellite remote sensing image and the chart water depth data are analyzed and processed in this paper and a new neural network model is established by transmission bands ratio. The ratio of blue, green, red and near-infrared bands of IKONOS is used to calculate the water depth. Using neural network model, the water depth are inversed directly by the remote sensing image data without regard to other environmental factors (e.g. sea sediments, marine organisms, etc.). The non-linear relationship between the multi-spectral IKONOS data and the measured depth data can be established within the proposed model and higher inversion precision can be obtained compared with traditional regression model.
机译:浅礁的水深反演对海洋安全,海洋工程和海洋军事起着重要作用。对IKONOS卫星遥感图像和海图水深数据进行了分析和处理,并通过传输带比建立了新的神经网络模型。 IKONOS的蓝色,绿色,红色和近红外波段的比率用于计算水深。使用神经网络模型,遥感图像数据直接反演水深,而无需考虑其他环境因素(例如,海洋沉积物,海洋生物等)。与传统的回归模型相比,该模型可以建立多光谱IKONOS数据与测深数据之间的非线性关系,并具有较高的反演精度。

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