Large-scale dynamic evolution dust type aerosol retrieval method

Abstract

The invention discloses a large-scale dynamic evolution dust type aerosol retrieval method. The large-scale dynamic evolution dust type aerosol retrieval method comprises step 1 training a classifier; acquiring a source field sample and a cloud layer sample of a dust type aerosol layer and a target field sample of the dust type aerosol layer according to passive type satellite sensor remote sensing data; acquiring characteristic vectors of the samples according to active type satellite sensor laser radar profile data; training a support vector machine classifier according to the characteristic vectors of the source field sample and the cloud layer sample; optimizing the classifier according to the characteristic vector of the target field sample and the transfer learning theory; step 2 performing retrieval on the dust type aerosol through an optimized classifier. The large-scale dynamic evolution dust type aerosol retrieval method can improve the cloud-sand classification accuracy after the dust is subjected to long-distance transmission, effectively reverse the situation that only low-accuracy data provided by NASA (National Aeronautic And Space Administration) can be used currently passively, solve the bottleneck problems that, in China, large-area dust vertical profile data is lost and the data usability is poor and the like and satisfy the observation requirement of dust aerosol source regions and diffusion transmission regions in China and even the globe.

Description

technical field [0001] The invention belongs to the technical field of satellite remote sensing data processing, and in particular relates to a large-scale dynamic evolution dust type aerosol inversion method. 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 have suffered 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...

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 algorithm prevents it from being applied to the research and forecast of dust in my country.

For example, NASA's Version2 algorithm has a high dust classification error rate, and the Version3 algorithm is complex, has many parameters, and has poor adaptability to aerosol model areas, etc.

Images