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Research On Winter Aerosol Optical Thickness Retrieval In Guanzhong Area Based On DT And DB Algorithms

Posted on:2019-10-25Degree:MasterType:Thesis
Country:ChinaCandidate:Y F ZhouFull Text:PDF
GTID:2371330545955476Subject:Environmental engineering
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With the accelerating economic development and urbanization process,environmental problems have become more and more serious,and many regions have encountered frequent continuous high-intensity atmospheric pollution.To meet the continuous monitoring requirements for regional aerosols,we need to use remote sensing monitoring methods.Detailed analysis of the ground-based monitoring station constitutes a complete "Heaven and Earth" integrated monitoring system.The scientific monitoring of atmospheric aerosols can be completed more effectively,and accurate and rapid diffusion trend analysis and forecasting is practical significance to the relevant departments to solve and prevent air pollution problems in timely.the dark pixel method and the deep blue algorithm were used to invert the aerosols in Guanzhong area in winter respectively.The MODIS aerosol products and ground monitoring stations were used to verify the accuracy of the data,and the applicability of the two inversion algorithms in Guanzhong area was analyzed.The aim is to provide high-precision real-time aerosol continuous monitoring methods to provide more efficient and accurate methods for regional aerosol monitoring,pollution source disclosure,and diffusion trend prediction analysis.The key issues involved in the study mainly include the determination of dark targets in the dark pixel inversion and the construction of the surface reflectance library in the deep blue algorithm.The article obtained the following results through research:(1)Although the aerosol optical depth in winter in the Guanzhong area is in agreement with the data of aerosol products and ground stations in the Guanzhong area,the inversion accuracy of the dark image method is low,and it is not accurate in quantitative precision inversion.It is recommended,but its algorithm is simple and the required data is easy to obtain.It is recommended to use it in the summer aerosol monitoring in Guanzhong area.In the winter aerosol monitoring application,only the dark pixel method can be used to complete simple trend analysis and simulate the atmosphere.Diffusion path of pollutants.(2)The deep blue algorithm has a good applicability to aerosol inversion in winter in Guanzhong region because the algorithm has less restrictions on landmark reflectivity,so the inversion result is more continuous and can be better than the dark pixel inversion results.Responding to the distribution of aerosols in the Guanzhong region and the diffusion process of pollutants,not only the general trend is in line with the actual situation,but also the accuracy of the inversion results has been improved.The article used aerosol products and ground-based monitoring data to verify the accuracy of the inversion results at the same time,and both achieved good correlation.This indicates that the Hawthorn algorithm can be used for the continuous monitoring of aerosols in the Guanzhong area during the winter.(3)The article summarizes the results of two inversion methods for error analysis,and discusses the main factors affecting the inversion accuracy and the corresponding solutions.The deep blue algorithm was used to invert the AOD of winter continuous haze days in Guanzhong area,and analyzed its distribution in Guanzhong area and the aerosol diffusion model during continuous haze days.Contact the wind direction data in the meteorological data to analyze the influence of wind direction on the aerosol diffusion in Guanzhong area.The retrieval of aerosols by remote sensing technology has broad prospects for development.The development of remote sensing technology will monitor aerosols.The new areas that have brought regional continuous monitoring have important guiding significance for air quality monitoring,diffusion of air pollutants,and warning and prevention of hazy weather.
Keywords/Search Tags:Dark target, Deep blue algorithm, Aerosol optical thickness, radiation transmission model, AOD spatial pattern evolution
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