IEEE Geoscience and Remote Sensing Letters · 2006 · 159 citations · 10 references
Natural SciencesEarth SciencesAtmospheric ScienceClimatologyRemote SensingAerosol Remote SensingCloud Optical PropertiesCloud PropertiesSatellite Image InterpretationSatellite SensorsAerosol IndexAerosol Optical ThicknessDust Aerosol Remote SensingDust MonitoringDust Storm DetectionOptical Thickness MeasurementReflectanceSatellite Remote Sensing Data
Sand and dust storms (SDSs), which present environmental risks and affect the regional climate, have been worsened in the East Asian regions over the last decade. Monitoring SDS from space using satellite remote sensing (RS) has become one of the most important issues in this field. At present, satellite RS of SDS is limited to using true-color images or aerosol optical thickness (AOT), or a new algorithm called "Deep Blue". Using current existing approaches makes it difficult to identify SDS from clouds. The authors have detected SDS by combining Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) solar reflectance band (SRB) measurements. Based on the dust spectral characteristic, this letter proposes a normalized difference dust index (NDDI) using MODIS reflectance measurements and applies it to the Asian SDS cases. The simple NDDI index is found to be able to identify SDS and clouds easily. The results suggest that NDDI could be used to detect SDS over bright surfaces where the MODIS AOT product is not available
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The MODIS Aerosol Algorithm, Products, and Validation
L. A. Remer, Yoram J. Kaufman, D. Tanré et al. · Journal of the Atmospheric Sciences · 2005 · 3.4K citations · Full text