Based On Modis Data And Aerosol Retrieval Modeling And Grid Computing Middleware

Aerosol retrieval using remotely sensed dada over land remains a difficult task because the solar light reflected by the Earth-Atmospheric system mainly comes from the ground surface. Until now, the popular aerosol retrieval algorithms usually have to assume the some parameters such as aerosol types and need the prior of surface reflectance estimated by the statistical correlation formulas, which result into lower retrieval accuracy. By using MODIS data, Dark Dense Vegetation (DDV) algorithm has showed excellent competence at the aerosol distribution and properties retrieval, which is, however, restrictedly used for lower reflectance ground surface such as water body and dense vegetation, and does not work well when used for high reflective ground surface such as urban areas.The key problems addressed here is how to retrieve the aerosol information from remotely sensed data without the assumptions or the prior knowledge of surface reflectance aforementioned, and realize the simultaneously retrieval of surface reflectance as well as aerosol properties. It could overcome the difficulties of aerosol retrieval over high reflective land surface, make the operational aerosol remote sensing possible over various land surfaces, and improve the accuracy of aerosol retrieval over land.A novel aerosol remote sensing model by exploiting the synergy of TERRA and AQUA MODIS data (SYNTAM) was proposed here, which could be used to accomplish part of the task of aerosol retrieval over land, especially over higher reflective surface. With SNYTAM, surface reflectance and aerosol optical thickness can be simultaneously retrieved over various ground types including higher reflective surface such as urban areas. The preliminary aerosol retrieval using MODIS data by SYNTAM were carried out over land surface covering Beijing city and the surrounding area. Preliminary validation results comparing with AERONET data...