Hyperspectral remote sensing water depth inversion method based on deep learning

Abstract

The invention relates to a hyperspectral remote sensing water depth inversion method based on deep learning, and the method comprises the following steps: carrying out geometric correction on an original hyperspectral remote sensing image of a research region, and carrying out atmospheric correction to obtain the real reflectivity of each waveband; screening an actually measured water depth rangewithin the range of 0-20 meters in the research area; clipping the remote sensing image according to the spatial range corresponding to the screened water depth data, and processing the remote sensingimage into a formatted data file; generating a formatted training data set by matching the spectral reflectivity information of the remote sensing image with the actually measured water depth data according to geographic coordinates; Using Tensorflow and Keras deep learning framework to build a fully connected neural network, 1D- CNN network, 2D-CNN network three deep learning networks to train the research area data; And respectively applying the trained network model to remote sensing image data to invert the water depth of the research area. According to the method, high-precision water depth data can be directly inverted only by taking hyperspectral remote sensing image spectral information of an optical shallow water region as input.

Description

(1) Technical field [0001] The invention relates to a hyperspectral remote sensing water depth inversion method based on deep learning, belongs to the field of optical remote sensing, and is of great significance in the research of water color remote sensing technology and deep learning technology. (2) Background technology [0002] Water depth is an important parameter of the marine environment and an important hydrological element. Coastal underwater terrain information is the basic information for coastal engineering construction, transportation, shipping, fish farming, and scientific research, and is of great significance in economic activities and natural environment protection. Coastal topography has an important impact on geological exploration, ship transportation, harbor construction, land reclamation, cable pipeline laying, coastal military engineering and other military activities, and is crucial to the economic construction and sustainable development of the coas...

AI Technical Summary

Problems solved by technology

However, due to the influence of many interference factors such as water turbidity, water bottom reflection, wave surface reflection, remote sensor band setting and band number limitation, the current conventional water depth remote sensing retrieval is facing the bottleneck problem of low accuracy, which restricts the accuracy of water depth remote sensing retrieval. Practicality and engineering application of deduction

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