Celil Kaplan

Date of Award

January 2013

Document Type


Degree Name

Master of Science (MS)


Atmospheric Sciences

First Advisor

Jianglong Zhang


Cloud and clear sky contamination due to sub-pixel clouds remains as a troubling issue for scientific applications that rely on remotely sensed data. Sub-pixel level clouds may not be detected by a standard cloud filtering process, and thus can cause uncertainties in satellite-based meteorological property retrievals. In this study, using collocated data from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Geostationary Operational Environmental Satellite (GOES) data, sub-pixel cloud and clear-sky contamination were studied over the west coast of Northern California. The hyper-spectral data from AVIRIS have a spatial resolution on the order of 11.5 m for the study case, thus can be used for carefully examining the sub pixel cloud related bias in GOES data. This study suggest that significant sub-pixel cloud and clear-sky contamination exist, and should be considered for future applications that use measurements from passive sensors such as GOES. Lastly, simulated AVIRIS radiance values from a radiative transfer model were used to explore the possibility of using AVIRIS data for future aerosol studies.