A Cloud Fraction versus View Angle Technique for Automatic In-Scene Evaluation of the MISR Cloud Mask

Open Access
Publisher Website
Google Scholar
Abstract
The Multiangle Imaging Spectroradiometer (MISR), on board the Earth Observing System (EOS) satellite Terra, is the first high-resolution imager to make global, near-simultaneous multispectral and multiangle radiometric measurements of the earth. A standard product of MISR is the radiometric camera-by-camera cloud mask (RCCM), which provides a cloud mask for each of the nine MISR cameras. Validation of the RCCM is ongoing, and in this paper an automatic and efficient technique is described that is being used to flag scenes for which the quality of the RCCM may be suspect, thus allowing rapid convergence toward validation. The technique, herein called the Fθ technique, makes use of the physical relationship that cloudiness increases with viewing obliquity. Where this behavior is not met for a given scene, the Fθ technique flags the scene as potentially problematic. The technique is applied to ∼4 months of MISR data to demonstrate its utility and to identify common problems that exist in version F01... Abstract The Multiangle Imaging Spectroradiometer (MISR), on board the Earth Observing System (EOS) satellite Terra, is the first high-resolution imager to make global, near-simultaneous multispectral and multiangle radiometric measurements of the earth. A standard product of MISR is the radiometric camera-by-camera cloud mask (RCCM), which provides a cloud mask for each of the nine MISR cameras. Validation of the RCCM is ongoing, and in this paper an automatic and efficient technique is described that is being used to flag scenes for which the quality of the RCCM may be suspect, thus allowing rapid convergence toward validation. The technique, herein called the Fθ technique, makes use of the physical relationship that cloudiness increases with viewing obliquity. Where this behavior is not met for a given scene, the Fθ technique flags the scene as potentially problematic. The technique is applied to ∼4 months of MISR data to demonstrate its utility and to identify common problems that exist in version F01...