Method and system for monitoring rice bacterial blight in field based on multi-source data

A system for monitoring rice bacterial blight in a field based on multi-source data, comprising:

• a multi-spectral image obtaining module, configured to obtain a multi-spectral image of a rice field at different growth stages;
• a bacterial blight severity and accumulated temperature data obtaining module, configured to obtain severities of the rice bacterial blight and accumulated temperature data in the rice field at different growth stages;
• a bacterial blight resistance of rice varieties obtaining module, configured to obtain resistance of the rice varieties planted in the rice field to the bacterial blight;
• a mean canopy spectral reflectance extraction module, configured to extract a mean canopy spectral reflectance of each plot in the rice field based on the multi-spectral images, wherein the rice field is divided into a plurality of plots;
• a depth spectrum feature output module, configured to conduct regression of the severity of the rice bacterial blight using a convolutional neural network based on the mean canopy spectral reflectance and the severity of the rice bacterial blight for each plot, and output a depth spectrum feature;
• a disease severity regression model training module, configured to train a disease severity regression model with the accumulated temperature data, the depth spectrum feature, and the resistance to the bacterial blight for each plot as an input and the corresponding severity of the rice bacterial blight as an output to obtain a well-trained disease severity regression model;
• and
• a disease severity monitoring module, configured to input accumulated temperature data, a depth spectrum feature and resistance to the bacterial blight corresponding to each plot of a to-be-monitored rice field into the well-trained disease severity regression model to output a level of severity of the rice bacterial blight in the to-be-monitored rice field.