Geologic Disaster Prediction Method Based on Remote Sensing Images and Artificial Intelligence

Landslides, avalanches and mudslides have become the three most common and typical geologic hazards, and they are also the geologic hazards with the widest influence and the greatest losses. In this paper, we take the geological remote sensing image as the research object, and construct a high-precision neural network model for automatic identification of geological disasters. By comparing and analyzing the convolutional neural network model proposed in this paper and the other two SVM machine learning algorithms, the experimental results show that the convolutional neural network proposed in this paper achieves high recognition accuracy for different categories of feature objects, is better than the other methods in scene recognition, and is more suitable for the recognition of the mudslide accumulation fan scene.