A pm2.5 Concentration Estimation Method Based on Geostationary Orbit Satellites

Abstract

A PM2.5 concentration estimation method based on geostationary satellites, which uses aerosol optical depth data that meets the accuracy requirements and the corresponding PM2.5 concentration data to establish a data set, and completes sample learning and data testing based on the random forest machine learning method. The accuracy of the test results is verified, and the parameters of the random forest machine learning model are adjusted to meet the accuracy requirements, and the multi-temporal PM2.5 concentration estimation under different weather conditions is performed through the final calculation model. The remote sensing estimation method of PM2.5 concentration based on geostationary satellites of the present invention can effectively perform multi-temporal remote sensing estimation of PM2.5 concentration, make up for the lack of time continuity of traditional methods, and provide more accurate data for air pollution prevention and control support.

Description

technical field [0001] The invention relates to the technical field of remote sensing, in particular to a method for estimating PM2.5 concentration based on geostationary orbit satellites. Background technique [0002] With the sustained and rapid development of my country's industrialization and urbanization, people's living standards have risen sharply, and more and more environmental problems have also emerged. In recent years, large-scale continuous smog has occurred in China many times. The smog is mainly composed of PM2.5, which can enter the lungs. PM2.5 refers to particles with an aerodynamic diameter of less than 2.5 μm. Compared with PM10, PM2.5 has a smaller particle size and can be absorbed in the atmosphere Long-term stay and long-distance transmission have a greater impact on the quality of the air environment; PM2.5 is easy to attach to various toxic and harmful substances (such as persistent organic pollutants, heavy metals, various pathogenic bacteria, etc.)...

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Problems solved by technology

Among them, satellite remote sensing data mostly come from polar-orbiting satellites, that is, sun-synchronous orbiting satellites. Because their orbits pass through the Earth’s north and south poles and are synchronous with the sun, their revisit periods at the same point are generally longer. For example, the MODIS (moderate-resolution imaging spectrometer) Imaging spectroradiometer) data is acquired twice a day (10:30 and 13:30 Beijing time). The PM2.5 concentration estimation based on this remote sensing data cannot reflect the migration of pollutants well. There are still many problems in the estimation of PM2.5 concentration

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