Land desertification monitoring method and system based on image recognition technology

Abstract

The invention relates to the technical field of land desertification monitoring, in particular to a land desertification monitoring method and system based on an image recognition technology. The method comprises the following steps: acquiring remote sensing image data covering a target area in recent five years, reading and preprocessing the image data through ENVI software, clipping and classifying the processed image data by using a sliding window method to form a sample set, a test set and a training set, and constructing a convolutional neural network classification model to classify the sample set. According to the land desertification monitoring method disclosed by the invention, the remote sensing image is combined with the deep learning technology, and the convolutional neural network classification model comprising the multi-scale residual module and the attention mechanism module is constructed by preprocessing and cutting the remote sensing image, so that the classification accuracy and reliability are improved, and the land desertification monitoring accuracy is improved. And meanwhile, the hierarchical features in the remote sensing image can be quickly identified, the vegetation coverage is combined, the desertification area is dynamically monitored by using the image map, and the flexibility of desertification monitoring is improved.

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