An improved liberal cloud-mask for addressing snow/cloud confusion with MODIS

Jeffery A. Thompson, David J. Paull, Brian G. Lees

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)119-129
Number of pages11
JournalPhotogrammetric Engineering and Remote Sensing
Volume81
Issue number2
DOIs
StatePublished - Jan 1 2015
Externally publishedYes

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