Cloud screening in IRS-P4 OCM satellite data: potential of spatial coherence method in the absence of thermal channel information

Cloud screening of satellite data for the remote sensing of atmospheric aerosols, ocean sediments, chlorophyll, and phytoplankton in the marine environment is a major problem in the absence of information from thermal channel. This is particularly the case with the data from some of the highly potential satellite sensors such as the Ocean Colour Monitor (OCM—on board the Indian Remote Sensing Satellite, IRS-P4) and the SeaWiFS. Two main tests conventionally used for cloud screening of data from such satellite sensors are the threshold method applied to visible and near-IR bands and the visible to near-IR channel ratio method. These methods do not have the potential to eliminate the pixels with small cloud fractions, leading to overestimation of the aerosol optical depth (AOD) derived from satellite data, and might also identify the pixels with high values of AOD as cloudy. The purpose of this paper is to study the potential of Spatial Coherence Test (SCT) applied to the data from the near-IR bands for cloud screening of satellite data over the oceanic environment. We use here the data from IRS-P4 OCM. Though more computationally intensive, the SCT does not suffer from the serious limitations of the threshold and channel ratio methods and is found to be superior in identifying the clear sky pixels that are not affected by clouds. Although the SCT applied to near-IR channel data may be overestimating the number of cloud affected pixels, it neither leads to overestimation of AOD nor identifies the pixels with high AOD values as cloudy.