基于遥感大数据的区域大气污染成因及污染物二次转换条件研究

Causes of Regional Air Pollution and Secondary Conversion Conditions of Pollutants Based on Remote Sensing Big Data

现有方法研究大气污染物二次转换条件时,数据分析存在效率低和准确率低等问题。提出基于遥感大数据的区域大气污染成因及污染物二次转换条件研究方法。分析区域大气污染成因,结合双边滤波器和冲击波滤波器对遥感图像进行预处理,获取遥感数据。根据遥感数据结果,通过多元回归方程研究污染物二次转换的条件,实验结果表明,所提方法的图像边缘强度高、分析准确率高、分析效率高,可以有效提升大气污染物的二次转换能力。

Th existing study method for secondary conversion conditions of air pollutants has the problems of low efficiency and low accuracy.The research method of regional air pollution causes and pollutant secondary conversion conditions based on remote sensing big data is proposed.The causes of regional air pollution are analyzed,and the remote sensing image is preprocessed with bilateral filter and shock wave filter to obtain remote sensing data.According to the results of remote sensing data,the conditions of pollutant secondary conversion are studied through multiple regression equation.The experimental results show that the proposed method has high image edge intensity,high analysis accuracy and high analysis efficiency,and can effectively improve the secondary conversion ability of air pollutants.