April 8, 2012, the east region of Inner Mongolia out broke a strong sandstorm. Based on the analysis of the spectral characteristics of dust, cloud and surface, this paper propose a duststorm mask algorithm for the identification of dust coverage region by using three infrared channels of FY-3B. By utilizing diurnal variation of brightness temperature of dust aerosol, the bi-temporal thermal dust index was established to represent the intensity of duststorm. Through the analysis we found that BTDI has a high negative correlation with aerosol optical depth which can be used as an effective means to monitor the duststorm.
NASA’s Moderate Resolution Imaging Spectro-radiometer (MODIS) sensors have been observing the Earth from polar
orbit, from Terra since early 2000 and from Aqua since mid 2002. MODIS is uniquely suited for characterization of
aerosols, combining broad swath size, multi-band spectral coverage and moderately high spatial resolution imaging. By
using MODIS data, many algorithms have showed excellent competence at the aerosol distribution and properties
retrieval. However, in China, many regions are not satisfied with the dark density pixel condition. In this paper, aerosol
optical depth (AOD) datasets (China Collection 1.1) at 1 km resolutions have been derived from the MODIS data using
the Synergetic Retrieval of Aerosol Properties (SRAP) method over mainland China for the period from August 2002 to
now, comprising AODs at 470, 550, and 660 nm. We compared the China Collection 1.1 AOD datasets for 2010 with
AERONET data. From those 2460 collocations, representing mutually cloud-free conditions, we find that 62% of China
Collection 1.1 AOD values comparing with AERONET-observed values within an expected error envelop of 20% and
55% within an expected error envelop of 15%. Compared with MODIS Level 2 aerosol products, China Collection 1.1
AOD datasets have a more complete coverage with fewer data gaps over the study region.