Retrieval Method for Estimating Snow Depth Using Hyperspectral Data in Snowmelt Period

The snow surface reflectance spectra with different depth in snowmelt period and snow depth data were measured and its correlation was analyzed. The characteristic absorption band data of the valley with higher correlation were used to establish a single band snow depth regression model. The highest contribution rate of the band was selected as the input variable of the neural network model to retrieve snow depth. The results show that in Juntang Lake area, near 1 022, 1 241 and 1 492 nm exists characteristic absorption valley of snow, and compared to estimation accuracy of the single-band inversion of snow depth model (R-2=0. 53), ANN-BP model has a higher inversion level, and determination coefficient (R-2 = 0. 86, RMSE = 0. 67) was obtained with 4 nodes in hidden layers, indicating that ANN-BP model can greatly improve the ability of inversion of snow depth with hyperspectral data.