A space-time continuous PM2.5 inversion method based on foundation and satellite observation

A satellite observation and inversion technology, applied in measurement devices, character and pattern recognition, suspension and porous material analysis, etc., can solve the problems of increasing satellite AOD missing rate, low AOD inversion accuracy, etc., and achieve good anti-noise ability. , to ensure the effect of stability

Inactive Publication Date: 2019-04-05
天津珞雍空间信息研究院有限公司
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Problems solved by technology

In addition, the inversion of AOD is related to the albedo of the surface. When the albedo of the surface is high, the surface is highlighted. The inv

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  • A space-time continuous PM2.5 inversion method based on foundation and satellite observation
  • A space-time continuous PM2.5 inversion method based on foundation and satellite observation
  • A space-time continuous PM2.5 inversion method based on foundation and satellite observation

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Embodiment 1

[0059] like figure 1 As shown, a time-space continuous PM2.5 retrieval method based on ground-based and satellite observations provided by this application includes the following steps:

[0060] s100. dividing the monitoring area into several sub-areas;

[0061] s200. Establish a random forest regression model for each sub-region, input meteorological dynamic indicators and satellite AOD as explanatory variables into the random forest network, train the random forest regression model to obtain the optimal model, and invert each sub-region under the optimal model Satellite estimates of PM2.5 concentrations for In , the meteorological dynamic indicators may be, for example, surface temperature, surface pressure, wind speed, relative humidity, and boundary layer height.

[0062] AOD is the aerosol optical depth, which is the integral of the aerosol extinction coefficient in the vertical direction. It is a physical quantity that quantitatively describes the reduction effect of ...

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Abstract

The invention discloses a space-time continuous PM2.5 inversion method based on foundation and satellite observation. The method comprises the following steps: dividing a monitoring area into a plurality of sub-areas; Establishing a random forest regression model for each sub-region, and carrying out inversion under the optimal model to obtain a PM2.5 concentration estimation value of each sub-region; Calculating a spatial interpolation observed by each station in each sub-region by using a common Kriging interpolation algorithm; Based on the root-mean-square error of the PM2.5 concentration satellite estimation value and the spatial interpolation, calculating the PM2.5 concentration satellite estimation value and the spatial interpolation by using an inverse variance weighting method to obtain a final PM2.5 concentration inversion value; According to the method, multi-scale segmentation and a random forest regression model are comprehensively adopted, the ground observation result isinterpolated, and seamless high-precision calculation of the near-ground PM2.5 concentration is achieved.

Description

technical field [0001] The present disclosure generally relates to the technical field of environmental monitoring, in particular to the monitoring technology of particulate matter in the air, and in particular to a space-time continuous PM2.5 retrieval method based on ground-based and satellite observations. Background technique [0002] In the past few decades, due to rapid urban expansion and industrialization, a large amount of particulate matter (PM, that is, particles with a diameter between 1 nanometer and 100 million) has been emitted into the air, resulting in frequent occurrence of haze events, especially in economically developed countries. and densely populated metropolitan areas. [0003] Atmospheric particulate matter is the most important component of aerosols and affects weather and climate systems through direct or indirect effects. Specifically, on the one hand, aerosols can directly absorb and scatter solar radiation and disturb the energy budget of the e...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06F17/18G01N15/06
CPCG06F17/18G01N15/06G06F18/214
Inventor 龚威史硕毛飞跃臧琳徐宝宋沙磊
Owner 天津珞雍空间信息研究院有限公司
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