Construction method and system of soil nitrogen content inversion model based on convolutional neural network
A convolutional neural network and inversion model technology, applied in the field of soil nitrogen content inversion model construction based on convolutional neural network
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Embodiment 1
[0043] see image 3 , which shows the construction method of the soil nitrogen content inversion model based on the convolutional neural network in the first embodiment of the present invention, and the method includes steps S101-S103:
[0044] S101. Obtain model training data, the model training data includes remote sensing image data and field soil samples, obtain remote sensing image range and multiple land use type samples according to the remote sensing image data, and combine the land use type samples with a convolutional neural network model for model training to obtain Obtain the first target model.
[0045] In the above steps, the land use type samples are combined with the convolutional neural network model for model training; the trained convolutional neural network model is subjected to accuracy evaluation in combination with the accuracy evaluation index to obtain the first target model, and the accuracy evaluation index includes the overall classification accurac...
Embodiment 2
[0056] Please check Figure 4 , which shows a method for constructing a soil nitrogen content inversion model based on a convolutional neural network in the second embodiment of the present invention, and the method includes steps S201-S203:
[0057] S201. Obtain model training data, where the model training data includes remote sensing image data and field soil samples, obtain the remote sensing image range and multiple land use type samples according to the remote sensing image data, and combine the land use type samples with a convolutional neural network model for model training to obtain Obtain the first target model.
[0058] The data collection stage includes remote sensing image data, related map data and field soil sample collection. After being air-dried, ground and sieved in the laboratory, the soil samples were evenly divided into two parts, one part was used to determine the total nitrogen content of the soil, and the other part was used to obtain soil spectral d...
Embodiment 3
[0078] see Figure 5 , which shows the construction system of the soil nitrogen content inversion model based on the convolutional neural network in the third embodiment of the present invention, and the system includes:
[0079] The acquisition module is used to acquire model training data, the model training data includes remote sensing image data and field soil samples, obtain remote sensing image range and multiple land use type samples according to the remote sensing image data, and combine the land use type samples The convolutional neural network model performs model training to obtain the first target model;
[0080] A conversion module, configured to obtain a land use type spatial distribution map according to the first target model in combination with the remote sensing image range, obtain a land use classification result according to the land use type spatial distribution map, and analyze different land use classification results according to the land use classifica...
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