Skip all navigation and jump to content Jump to site navigation
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link



Li, SS, Chen, LF (2009). Design of Air Quality Remote Sensing Monitoring System and Parallel Dense Dark Vegetation Algorithm. PROCEEDINGS OF THE 2009 INTERNATIONAL CONFERENCE ON SIGNAL ACQUISITION AND PROCESSING, 63-67.

During Beijing Olympic Games, air quality had been extensively concerned by home and abroad. Remote Sensing satellite can provide greater monitoring scale compared to ground equipment. Based on NASA MODerate resolution Imaging Spectrometer (MODIS) data, using NET multi-layer architecture. combined with MatlabCOM, ArcEngine and other components, we establish Air Quality Remote Sensing Monitoring System and discuss the roles and design criteria of each component layer. To solve Aerosol Optical Thickness (AOT) retrieval time consuming problem, we use a Master-Worker strategy to parallelize the Dense Dark Vegetation (DDV) algorithm, it is running on a common platform of computer clusters and based on cloud mask to distribute task. Through the acceleration performance analysis, it has shown preferable speedup radio and load balance. Finally, this paper verifies some results from Beijing Olympic atmosphere monitoring project.



NASA Home Page Goddard Space Flight Center Home Page