Spatial mapping of topsoil total nitrogen in mountainous and hilly areas of southern China using a continuous convolution neural network
CATENA(2023)
Abstract
•Deep learning models successfully transform image spectra into laboratory-measured spectra.•Models roughly estimate soil total nitrogen content using transformed spectra.•Residual correction by ordinary kriging interpolation improves the spectral inversion accuracy.•A continuous convolutional neural network model outperforms a multilayer perceptron model.
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Key words
Deep learning, Continuous convolutional neural network, Spectral transformation, Mountainous and hilly areas, Soil total nitrogen
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