Snow passive microwave mixed pixel decomposition method based on classified information of five types of ground features

A hybrid pixel decomposition and passive microwave technology is applied in the field of remote sensing image processing to improve the inversion accuracy.

Inactive Publication Date: 2012-07-25
JILIN UNIV
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Problems solved by technology

[0016] The technical problem to be solved by the present invention is to provide a snow passive microwave mixed pixel decomposition method based on five types of ground object classification information, which can effec

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  • Snow passive microwave mixed pixel decomposition method based on classified information of five types of ground features
  • Snow passive microwave mixed pixel decomposition method based on classified information of five types of ground features
  • Snow passive microwave mixed pixel decomposition method based on classified information of five types of ground features

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Embodiment 1

[0139] The present invention uses AMSR-E passive microwave remote sensing data and MODIS land cover classification UMD data products, combined with the proposed snow passive microwave remote sensing hybrid pixel decomposition method, to realize the snow accumulation in Xingkai Lake area, Heilongjiang Province, China on November 26, 2010 Efficient decomposition of passive microwave hybrid pixels.

[0140] Specifically include the following steps:

[0141] 1. Acquisition of ground object classification data:

[0142] The snow microwave mixed pixel decomposition method requires the classification information of the underlying surface objects in the observation area. The microwave brightness temperature of snow cover is greatly affected by the underlying surface. Through foundation experiments, it is found that the brightness temperature of snow cover on forest land is greatly affected by tree trunks, the brightness temperature of snow cover on grassland is mainly affected by the...

Embodiment 2

[0218] The present invention uses AMSR-E passive microwave remote sensing data and MODIS land cover classification LAI / FPAR data products, combined with the proposed snow passive microwave remote sensing hybrid pixel decomposition method, to realize the passive snow accumulation in Jilin Province, China on November 13, 2010. Efficient decomposition of microwave mixed pixels.

[0219] Specifically include the following steps:

[0220] 1. Acquisition of ground object classification data:

[0221] The snow microwave mixed pixel decomposition method requires the classification information of the underlying surface objects in the observation area. The microwave brightness temperature of snow cover is greatly affected by the underlying surface. Through foundation experiments, it is found that the brightness temperature of snow cover on forest land is greatly affected by tree trunks, the brightness temperature of snow cover on grassland is mainly affected by the scattering of grass,...

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Abstract

The invention belongs to the technical field of remotely sensed image processing, and provides a snow passive microwave mixed pixel decomposition method based on the classified information of five types of ground features. According to five types of typical underlying surfaces affecting the radiation characteristic of snow, the method acquires the classified data of the ground features with high special resolution in an observed region, utilizes the different characteristics of the microwave radiation of snow on the different underlying surfaces and selects a microwave antenna gain function and a sampling rate to build a snow passive microwave mixed pixel decomposition model, and adopts the least square method with constraint conditions to iteratively solve an underdetermined system of equations, thus realizing snow passive microwave mixed pixel decomposition. The method can effectively solve the problem of the mixed pixels of passive microwaves of snow, improves the precision of snowparameter inversion, and has a significant application value in fields such as climate and hydrological research and snow disaster assessment.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and in particular relates to a snow passive microwave mixed pixel decomposition method based on five kinds of ground object classification information, which can solve the problem of low inversion accuracy of snow parameters due to snow microwave mixed pixels The problem. Background technique [0002] The variability and characteristics of snow cover are important parameters in climate research, weather forecasting and water resource management (see Reference 1 listed below). The most commonly used wavebands in snow remote sensing are visible light, near-infrared and microwave. Among them, visible light and near-infrared are mainly used to extract snow coverage. Their biggest weakness is that they cannot be used to retrieve snow depth and snow water equivalent. Microwave plays an indispensable role in remote sensing of snow cover. It can not only observe snow cover all da...

Claims

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Application Information

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IPC IPC(8): G01S7/41
Inventor 顾玲嘉任瑞治张爽王昊丰孙健
Owner JILIN UNIV
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