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.
Bibliographical noteFunding Information:
The authors wish to acknowledge the efforts of the anonymous reviewers, whose diligent comments helped significantly improve the manuscript. Special thanks are due to Julie Kesby for editorial assistance. This study was undertaken as part of a PhD that was made possible by an Australian Postgraduate Award (APA) and was undertaken at the Canberra campus of the University of New South Wales, Australia. Financial support for writing this manuscript was provided to the first author in the form of a Publication Fellowship awarded by UNSW Canberra. The author’s also appreciated the ASTER image processing (1B) that was supplied free of charge by the Land Processes Distributed Active Archive Center.
© 2014 American Society for Photogrammetry and Remote Sensing.