i Detection of Smoke and Dust Aerosols Using Multi-sensor Satellite ...

spatial characterization, the biggest mis-registration is observed between the warm FPA
and the cold FPA. The existence of spatial shift between these two bands, up to 320 m
along-track and 265 m along scan, will produce undesired effects, and consequently, lead
to less accurate NDDI value and dust aerosol detection product.
If the NDDI is calculated with 500 m resolution measurements, the mis-registration
between two bands is up to 0.64 pixels in track direction and 0.53 pixels in scan direction.
The tentative correction is performed by shifting one pixel in track direction while keep
unchanged in scan direction since the mis-registration is more serious along-track. A dust
storm is displayed in Fig. 7.9 (only part of dust storm) by MODIS true color image. The
dust storm is prevalent in the left and right sides of the image, divided by the cloud in the
middle. Fig. 7.10 and Fig. 7.11 present the difference of NDDI values and dust aerosol
detection. The three subplots in Figs. 7.10 and 7.11, from left to right, are the results with
and without correction and their comparison difference.
In Fig. 7.11, the total number of dust aerosol pixels detected is 15,622 in the
sampled area, listed in Table 7.3. After correction, the number of detected dust aerosol
pixels decrease to 15,455. There are 15,270 pixels are labeled as dust aerosol in two
results, equaling 97.747%. About 185 non-dust aerosol pixels (cloud and other pixels) are
labeled as dust aerosol pixels after correction, and correspondingly 352 dust aerosol
pixels are identified as non-dust pixels in the corrected results. The difference is up to 3%.
The correlation coefficients, r 2 , of all three surface scenes increase after spatial correction.
This increase demonstrates that the quality of science data products can be improved by
spatial correction.
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