MODIS-based PM2.5 remote sensing inversion method

Abstract

The invention relates to the field of remote sensing image processing, and in particular to an MODIS-based PM2.5 remote sensing inversion method. The method comprises the following steps of: obtainingan MODIS image and PM2.5 monitoring data at the same time; interpolating the PM2.5 data into a PM2.5 interpolation image; constructing a training set and a test set; using the training set to train amachine learning algorithm, using a trained model to the test set, and calculating a performance index, on the test set, of the model; repeating the steps S3 and S4 to obtain a plurality of performance indexes so as to select an optimum model; and using the optimum model to the whole MODIS image so as to obtain a PM2.5 inversion result of the whole MODIS image. The method starts from data of remote sensing images and directly establishes a relationship between the remote sensing images and measured PM2.5 through the machine learning algorithm, so that error transfer is avoided and inversion results with higher precision are achieved. The method has the effects of avoiding error transfer and being high in inversion precision.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a PM2.5 remote sensing inversion method based on MODIS. Background technique [0002] Aerosol, also known as aerosol or smog, refers to a dispersion system formed by solid or liquid particles stably suspended in a gas medium, and its general size is between 0.01-10 microns, which can be divided into two types: natural and human-generated; Aerosols can affect the climate, including absorbing radiation or scattering radiation, and aerosols can become condensation nuclei and affect the properties of clouds, etc. Clouds, fog, and dust in the sky, smoke from unburned fuel in boilers and various engines used in industry and transportation, solid dust from mining, quarry grinding, and grain processing, Man-made masking smoke and toxic smoke are specific examples of aerosols. The elimination of aerosols mainly depends on the process of atmospheric precipitation,...

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Problems solved by technology

[0004] The current monitoring methods are the establishment of ground observation stations, such as the Global Automatic Observation Network (AERONET), the US Environmental Visual Monitoring Station (IMPROVE), and the US Environmental Protection Agency's nearly 4,000 air observation stations (SLAMS), which can monitor aerosols. Continuous observation can directly reflect the ground concentration information of pollutants, but the sparseness and discontinuity of ground environmental observation stations make it difficult to reflect the temporal and spatial distribution, pollution sources and transmission characteristics of PM2.5 aerosol particles on a large scale. Expensive, etc. restrict the effective monitoring and macro analysis of PM2.5; now more advanced monitoring uses the inversion of PM2.5 for monitoring and analysis, and the inversion of PM2.5 refers to the inversion of its mass concentration, while the existing The inversion method of PM2.5 is to invert the atmospheric aerosol optical depth AOD first, then establish the statistical relationship between the aerosol optical depth AOD and the ground measured PM2.5, and then use the statistical relationship to obtain the area without ground observation points The PM2.5 value will bring errors during the inversion process of AOD, and then use AOD to establish the process of measuring PM2.5, which will lead to the transmission of errors, thus affecting the final PM2.5 inversion accuracy

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