Atmospheric pollution feature recognition method and device

Abstract

The invention provides an atmospheric pollution feature recognition method and device, and belongs to the field of environmental science. The method comprises the following steps: acquiring spatial distribution data of atmospheric pollution indexes of a set area based on two-dimensional grid storage; a two-dimensional spatial data grid of the set area is constructed, and each first geographic grid in the two-dimensional spatial data grid has a first corresponding relation with a two-dimensional grid of the spatial distribution data; a spatial topological relation data grid is constructed according to the two-dimensional spatial data grid, each second geographic grid in the spatial topological relation data grid has a second corresponding relation with the geographic position identifier of the geographic position, and the second geographic grids are in one-to-one correspondence with the first geographic grids; and according to the spatial distribution data, the two-dimensional spatial data grid and the spatial topological relation data grid, identifying spatial distribution characteristics of the atmospheric pollution indexes of the at least one target area. According to the invention, the identification efficiency can be improved.

Description

technical field [0001] The invention relates to the field of environmental science, in particular to a method and device for identifying air pollution characteristics. Background technique [0002] Generally speaking, the analysis of the air pollution situation is mainly carried out by some professionals (such as forecasters of environmental protection bureaus at all levels) by previewing a large amount of meteorological condition data and pollutant data (such as various meteorological body distribution maps, pollutant distribution maps, etc.) ), through their professional knowledge and experience, artificially analyze the changes in the air pollution situation, draw corresponding conclusions, and finally release relevant information through various media channels (such as real-time air quality broadcasts, future air quality forecasts, etc.). [0003] Therefore, it is a very necessary job for air quality forecasters to understand the pollutant distribution map, identify the ...

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Problems solved by technology

[0004] 1. Judging the air pollution situation through the pollutant distribution map requires professional knowledge and relevant experience, and ordinary people cannot complete it

[0005] 2. Since there are many types of pollutants, and each time corresponds to a map, when manually analyzing the characteristics of each pollutant distribution map, the task is heavy and takes a lot of time

[0006] 3. Affected by human factors, different people will identify the pollution distribution map differently, increasing the inconsistency of the identification conclusion of the pollution distribution map

[0007] 4. Manually identify the distribution map of pollutants, some requirements cannot be realized, and some identification processes will also have errors

For example, human recognition such as figure 1 In the air quality (AQI, Air Quality Index) forecast distribution map shown, since only provincial areas are shown in the picture, limited by the map shown, it may not be possible to manually identify the AQI average pollution level to achieve light pollution Municipal area

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