Research On Key Technologies And System Design Of Quantitative Remote Sensing Monitoring Of Air Pollution

With the sustained and rapid economic development in China,energy consumption has risen sharply,and air pollution has been increasing.Therefore,it is imperative to put more effort into environmental monitoring and improvement.Satellite's remote sensing monitoring is a new type of technology developed with the advancement of aerospace technology.Satellite's remote sensing can monitor environmental pollution over the earth's surface in a periodic and omni-directional manner.It can maximize the level of real-time monitoring of environmental pollution in effectively.Aerosol refers to the general term of various liquid or solid particles floating in the atmosphere.Aerosol can damage the radiation balance of the atmospheric system by absorbing and scattering solar radiation.That is,aerosol have certain extinctive effect on electromagnetic radiation.The main components of atmospheric pollution are also aerosol solid-liquid particles,which have similar physical and chemical properties.Atmospheric aerosol optical thickness(AOD)is one of the most important parameters of aerosol.As an important physical quantity characterizing atmospheric turbidity,AOD is an extremely critical factor in determining the aerosol climatic effect.Therefore,in the use of remote sensing monitoring technology to study atmospheric pollution,the atmosphere can be considered as an aerosol,according to the characteristics of aerosol research.In this paper,the new Landsat-8 satellite data is used as an experimental data source.Compared with the more commonly used MODIS data,it has higher resolution and more stable quality.The number of Landsat-8 data bands is 9 and the number of MODIS bands is 36.MODIS data is widely used but not suitable for research requires high precision,but they are more accurate especially for AOD inversion analysis and research on Landsat-8 data.Therefore,the use of this data will lead to more accurate experimental results and more accurate air pollution predictions.Landsat-8 satellite data was used to perform AOD inversion in Beijing using the improved DT algorithm and VNIR ACM algorithm,respectively.The root mean square errors(RMSE)are 0.195 and 0.282,the standard deviations are 0.300 and 0.471,and the average absolute deviations(MAD)are 0.236 and 0.364.The improved DT method has higher accuracy than the VNIR ACM method.According to the analysis of inversion results,the AOD distribution in Beijing shows obvious regional characteristics.The areas with high AOD are mainly concentrated in the southeast of Beijing and the surrounding areas.In addition,the relatively low AOD values in the southwest and northern parts of Beijing are mainly due to the small impact of human activities and transportation.Finally,the project uses AERONET site AOD data to verify the AOD value of the two inversion algorithms and MOD04 data to evaluate the accuracy of the improved DT algorithm performance.In order to monitor air pollution more effectively,this project designed and implemented an AOD inversion system using IDL language.The main building blocks of the system are: data read/write module,6S module,inversion module,and graphics rendering module.The project designs the overall system logic flow and implementation flow according to the sequence of AOD inversion and introduces the UI interface and layout of each functional module in detail.