Multi-frequency dual-polarization woodland snow passive microwave hybrid pixel decomposition method

Abstract

The invention discloses a multi-frequency dual-polarized woodland snow passive microwave mixed pixel decomposition method, which belongs to the technical field of remote sensing image processing. Aiming at the prior art, the error is relatively small when using passive microwave data to perform snow depth inversion on forest land snow. Big question. The present invention first acquires and reclassifies the land classification data of the forest subsurface surface, and then establishes a multi-frequency dual-polarization woodland snow passive microwave mixed pixel decomposition model based on the classification results, and finally based on the underdetermination of the dynamic window data selection strategy Solve the equations to obtain the component brightness temperature data and error data corresponding to each underlying surface after decomposition. In the process, the present invention considers the spatial correlation of microwave pixels, and proposes 8 neighborhood windows for data input and 4 neighborhood windows. Data input Two kinds of data input schemes, and according to the above two input schemes and the optimization of the solution results, four solutions are proposed.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, in particular to a multi-frequency dual-polarization woodland snow passive microwave hybrid pixel decomposition method. Background technique [0002] Snow cover is one of the most active natural factors on the earth's surface. 3 / 4 of the land's fresh water resources exist in the form of ice and snow, and 1 / 3 of the surface of the earth has seasonal snow cover. Eurasia and North America have at least 80% of the land surface is covered by snow. Snow cover is an important factor determining the radiation balance. It not only has a strong climate effect, but also has an extremely important impact on energy and water cycle processes. Because passive microwave remote sensing has high temporal resolution and can quickly cover the whole world, it plays a particularly prominent role in monitoring the temporal and spatial changes of snow cover at the global and continental scales. ...

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Problems solved by technology

[0004] In order to solve the problem that the heterogeneity in the woodland pixel has a large influence, which leads to a large error when using the snow depth inversion method, the present invention combines the passive microwave antenna with the underlying surface data in the woodland passive microwave observation pixel Gain function, providing a multi-frequency dual-polarization woodland snow passive microwave hybrid pixel decomposition method

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