Sand-dust type aerosol inversion method based on support vector machine identification

Abstract

The invention discloses a sand-dust type aerosol inversion method based on support vector machine identification. The method comprises the steps of selecting a sand-dust aerosol layer with obvious characteristics, a thick cloud layer with obvious characteristics and a thin cloud layer with obvious characteristics as classification samples, training classifiers through various sample numbers and characteristic vectors, then confirming an optimal classifier, classifying data of a satellite borne laser radar sand-dust source region, obtaining a sand-dust aerosol identification result with high accuracy, and inverting level height and optical thickness of an aerosol. According to the sand-dust type aerosol inversion method based on the support vector machine identification, a support vector machine is used for confirming characteristics of a hyper-plane through support vectors, the requirements for the number of the samples can be reduced, interference on classification accuracy due to sample uncertainty is reduced, and 532nm polarization detection data and level height information of a satellite borne laser radar are effectively used for distinguishing non-spherical ice crystal cloud and sand-dust type aerosol particles. The sand-dust type aerosol inversion method based on the support vector machine identification is particularly suitable for processing satellite borne laser radar detection data of a sand-dust season in northwest region of our country.

Description

technical field [0001] The invention belongs to the technical field of satellite remote sensing, and particularly designs a dust-type aerosol inversion method based on support vector machine identification. Background technique [0002] my country suffers from many sandstorms every year. Under the influence of this extreme weather, my country's industrial and agricultural production, transportation and human life safety suffer serious losses and harms. In recent years, the scope of dust influence has gradually expanded, and has even spread to southeastern regions such as Fuzhou and Taiwan. Therefore, it is of great scientific significance to carry out basic research on large-scale sand and dust observation and inversion methods, and will play an active role in major events of the national economy and people's livelihood such as sand and dust early warning and disaster reduction. [0003] Lidar is the best way to obtain the vertical distribution profile of aerosols. Currentl...

AI Technical Summary

Problems solved by technology

CALIPSO is the best way to obtain the vertical distribution profile information of large-scale sand and dust in my country. Its hardware can detect dust information, but the defect of its data processing method prevents it from being applied to the research and forecast of dust in my country.

For example, NASA's Version2 method has a high error rate in dust classification, and the Version3 method is complex, has many parameters, and has poor regional adaptability of aerosol models, etc.

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