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



Wang, Y; Xue, Y; Li, YJ; Guang, J; Mei, LL; Xu, H; Ai, JW (2012). Prior knowledge-supported aerosol optical depth retrieval over land surfaces at 500 m spatial resolution with MODIS data. INTERNATIONAL JOURNAL OF REMOTE SENSING, 33(3), 674-691.

Aerosol optical depth (AOD) values at a spatial resolution of 500 m were retrieved over terrain areas by applying a time series of Moderate resolution Imaging Spectroradiometer (MODIS) 500 m resolution data in the Heihe region (36-42 degrees N, 97-104 degrees E) of Gansu Province, China; in the Pearl River Delta (18-30 degrees N, 108-122 degrees E), China; and in Beijing (39-41 degrees N, 115-118 degrees E), China. A novel prior knowledge scheme was used in the algorithm that performs cloud screening, simultaneous AOD and surface reflectance retrieval from the MODIS 500 m Level 1B data. This prior knowledge scheme produced a new angstrom ngstrom exponent alpha, utilizing a Terra pass time alpha and an Aqua pass time alpha to better satisfy the invariant alpha assumption. The retrieved AOD data were compared with AOD data observed with the ground-based, automatic Sun-tracking photometer CE318 at corresponding bands in the Heihe region and with Aerosol Robotic Network (AERONET) data in the Pearl River Delta and in Beijing. Validation experiments demonstrated the potential of applying the algorithm to MODIS 500 m AOD retrieval on land; validation showed the uncertainty of Delta tau = +/- 0.1 +/- 0.2 tau over various types of underlying land surface, including cities, where tau is the aerosol optical depth. The root mean square errors (RMSEs) were around 0.1 for inland regions and up to 0.24 for cities by the sea, such as Hong Kong and Zhongshan, China.



NASA Home Page Goddard Space Flight Center Home Page