Computer Science – Performance
Scientific paper
Dec 2003
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003georl..30wasc2h&link_type=abstract
Geophysical Research Letters, Volume 30, Issue 23, pp. ASC 2-1, CiteID 2187, DOI 10.1029/2003GL018446
Computer Science
Performance
5
Atmospheric Composition And Structure: Aerosols And Particles (0345, 4801), Global Change: Remote Sensing, Global Change: Instruments And Techniques, Meteorology And Atmospheric Dynamics: Radiative Processes, Meteorology And Atmospheric Dynamics: Remote Sensing
Scientific paper
A method is proposed to enhance the performance of automated cloud detection algorithms in the vicinity of desert regions. The approach uses data in MODIS Channel 8, which has a bandpass of 405-420 nanometers (nm) where a strong contrast exists between the more highly reflective clouds and lower reflective cloud-free desert regions. Special processing is required to exploit cloud signatures since the MODIS high (880) signal-to-noise-ratio (SNR) requirement in this band causes saturation. The value of 412 nm data is demonstrated in the analysis of a scene that contains clouds over the western part of the Sahara Desert and has airborne sand and dust extending over the eastern Atlantic Ocean.
Hutchison Keith D.
Jackson John M.
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