NDLI: Global single and multiple cloud classification with a fuzzy logic expert system

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Global single and multiple cloud classification with a fuzzy logic expert system

Content Provider	NASA Technical Reports Server (NTRS)
Author	Tovinkere, Vasanth Titlow Sr., James Welch, Ronald M. Baum, Bryan A.
Copyright Year	1996
Description	An unresolved problem in remote sensing concerns the analysis of satellite imagery containing both single and multiple cloud layers. While cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget, most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. Coakley (1983) used a spatial coherence method to determine whether a region contained more than one cloud layer. Baum et al. (1995) developed a scheme for detection and analysis of daytime multiple cloud layers using merged AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High-resolution Infrared Radiometer Sounder) data collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign. Baum et al. (1995) explored the use of a cloud classification technique based on AVHRR data. This study examines the feasibility of applying the cloud classifier to global satellite imagery.
File Size	254804
Page Count	4
File Format	PDF
Alternate Webpage(s)	http://archive.org/details/NASA_NTRS_Archive_19970026660
Archival Resource Key	ark:/13960/t45q9vk5g
Language	English
Publisher Date	1996-02-02
Access Restriction	Open
Subject Keyword	Meteorology And Climatology Satellite Imagery Climatology Cloud Cover Classifications Isccp Project Satellite Sounding Clouds Meteorology Satellite Observation Climate Models Infrared Radiometers Remote Sensing Fuzzy Systems Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science
Content Type	Text
Resource Type	Article

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