An Improved Liberal Cloud-Mask for Addressing Snow/Cloud Confusion with MODIS

摘要

The utility of the daily modis snow products depends on the ability of the modis cloud-masking algorithm to differentiate between snow- and cloud-cover. Although few studies have explored the issue, snow/cloud confusion is a key issue limiting the accuracy of the modis snow products. Recent studies from the Southern Hemisphere suggested that snow/cloud confusion limited the utility of the modis snow products there. In this study, modis snow/cloud confusion over Australia was investigated using an improved liberal cloud-mask in conjunction with a snow-detection algorithm. The performance of the proposed cloud-mask was assessed using high-resolution aster imagery and in situ observations. Results indicated that the improved liberal cloud-masking algorithm reduced snow/ cloud confusion, successfully identifying snow-covered pixels that were previously identified as cloudy. The analysis further suggested that scale-related differences in imagery used in the standard modis cloud-masking workflow might be the source of some snow/cloud confusion previously reported.