Mariculture area classification method fusing multi-source high-resolution satellite remote sensing images

Abstract

The invention relates to a mariculture area classification method fusing multi-source high-resolution satellite remote sensing images. The mariculture area classification method comprises the following steps: acquiring various satellite remote sensing images covering a 30km range of a coastline in China within a set time period; performing preprocessing and data normalization on the satellite remote sensing images to obtain a standard meter-scale high-resolution image; dividing the standard image into a training set, a test set and a detection set; selecting samples from the training set to train the U2-Net and HRNet-OCR deep learning convolutional neural network models respectively, and selecting samples from the test set to test; and detecting the images in the detection set by adopting two packaged models, outputting detection results, and fusing the detection results to obtain plant type and animal type mariculture area distribution results. According to the method, the advantages of the two models are combined, the culture area extraction accuracy is effectively improved, the workload of manual screening is reduced, the working efficiency is improved, and rapid, reliable and automatic identification and classification of different types of offshore mariculture areas in a large-scale range are realized.

Description

technical field

[0001] The invention relates to the technical field of image processing, in particular to a method for classifying marine aquaculture areas by fusing multi-source high-resolution satellite remote sensing images. Background technique

[0002] In recent years, with the continuous increase of market demand, the support of national policies and the continuous improvement of aquaculture technology, my country's aquaculture industry has developed rapidly, and the marine aquaculture industry has gradually become an important part of my country's agriculture and "blue economy". , The disorderly expansion has also brought a series of negative impacts on the ecological environment and maritime traffic. Therefore, it is of great practical significance to quickly and accurately obtain the distribution and location range changes of marine aquaculture areas to prevent and control aquaculture pollution, ensure navigation safety, and optimize aquaculture space layout. At pre...

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