Research and discussion on CNN and GNN for soil erosion prevention and control

Currently soil erosion is a more serious situation, in this study the convolutional neural network (CNN) and graph neural network (GNN) technology is used. Through the combination of the two algorithms: the remote sensing image features identified by CNN and the geospatial relationship features processed by GNN are combined to analyse the changes in soil and water conditions and predict the degree of soil erosion, so as to provide a decision-making basis for precise prevention and control. In the whole process, CNN provides basic spatial feature data for GNN, while GNN further explores the complex relationship between geographic elements on the basis of CNN, and the two are complementary to each other, so as to jointly achieve more accurate monitoring, simulation, and prevention and control strategy formulation for soil erosion. The data and conclusions fully reflect the advantages of these two algorithms over other methods for soil erosion control.