基于透射频带比的遥感水深反演方法

Zhenxing Zhang, H. Teng
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引用次数: 4

摘要

浅礁水深反演在海洋安全、海洋工程和海洋军事等方面具有重要作用。本文对IKONOS卫星遥感影像和海图水深数据进行了分析和处理,并根据传输频带比建立了一种新的神经网络模型。利用IKONOS的蓝、绿、红、近红外波段的比值计算水深。利用神经网络模型,在不考虑其他环境因素(如海洋沉积物、海洋生物等)的情况下,直接利用遥感影像数据反演水深。该模型可以建立IKONOS多光谱数据与实测深度数据之间的非线性关系,与传统回归模型相比,反演精度更高。
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An Inversion Method of Remote Sensing Water Depth Based on Transmission Bands Ratio
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.
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