Extraction method for coverage rate of sub-pixel accumulated snow based on resampling regression analysis

Abstract

The invention relates to an extraction method for coverage rate of sub-pixel accumulated snow based on resampling regression analysis. The method does not depend on ground actual measured data or synchronous high resolution ratio, the resolution ratio of an image is reduced, and the image is resampled, the data after being subjected to resampling and the resolution ratio reduction are used as thesample data; and a multivariate linear model between the coverage rate of the sub-pixel accumulated snow and reflectivity is established. The technical scheme of the extraction method is small in calculated amount and is suitable for remote-sensing images with larger area range, larger data amount, different areas and different time.

Description

technical field [0001] The invention belongs to the application field of remote sensing images, in particular to a new sub-pixel snow coverage extraction method. Background technique [0002] The binary snow cover map only divides pixels into snow and non-snow. Therefore, the binary snow cover products produced by low- and medium-resolution images are difficult to meet the accuracy requirements of snow research in a small area. Therefore, the snow cover information extraction method based on sub-pixel was conceived. At present, there are mainly two research methods for subpixel-based snow cover inversion: one is mixed pixel decomposition method, and the other is statistical regression analysis method (Xu Lina, 2006). [0003] The ground reflection or emission spectral signal obtained by the remote sensor is recorded in units of pixels, which is the synthesis of the spectral signals of the surface material corresponding to the pixel. If the pixel contains only one type, it i...

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Problems solved by technology

[0002] The binary snow cover map only divides pixels into snow and non-snow. Therefore, the binary snow cover products produced by low- and medium-resolution images are difficult to meet the accuracy requirements of snow research in a small area.

On the basis of this, Zhou Qiang et al. tried to classify the snow cover rate according to NDSI, and then modeled the different categories separately, and verified the estimation results of the data model with ETM+ data. The inversion of snow cover rate in the value area has been improved to some extent, however, the segmented model can still give accurate estimates in the transition zone of snow cover (Zhou Qiang et al., 2008)

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