Detection of dust over deserts using satellite data in the solar wavelengths

Dust is a dominant feature in satellite images and is suspected to extract large radiative forcing of climate. While remote sensing of dust over the dark oceans is feasible, adequate techniques for remote sensing over the land still have to be developed. Similar to remote sensing of aerosol over vegetated regions, the authors use a combination of visible and mid-IR solar channels to detect dust over the desert. Analysis of Landsat TM images over Senegal taken in 1987 show that the surface reflectance at 0.64 μm is between 0.54±0.05 of the reflectance at 2.1 μm, and reflectance at 0.47 μm is 0.26±0.03 of that at 2.1 μm, surprisingly similar to relationships in non-desert sites. They also found that dust have only a small effect on the surface+atmosphere reflectance at 2.1 μm over the desert. Therefore, in the presence of dust, they use the Landsat TM data at 2.1 μm channel to predict the surface reflectance at 0.64 and 0.47 μm. The difference between the satellite-measured reflectances of surface+atmosphere and the predicted surface reflectances is used to derive the dust-optical thickness τ at 0.64 and 0.47 μm. Results show that τ can be derived within Δτ=±0.5 for the range of 0<τ<2.5, thus enabling detection of dust sources and the estimation of three to five levels of dust opacity over the desert. The method is very sensitive to the correct knowledge of the dust absorption and is equally sensitive to dust in the entire atmospheric column. It is best applied in the red part of the spectrum (around 0.64 μm), where dust was found to be weak-absorbing or nonabsorbing. They plan to use this method as part of the dust monitoring from the Earth-observing system MODIS instrument