Improving snow and cloud discrimination in MODIS snow cover products

The Moderate Resolution Imaging Spectroradiometer (MODIS) fractional snow cover products may have significant errors due to cloud contamination, varying viewing geometry and complex surface properties. To improve snow and cloud discrimination with a particular interest in large sensor viewing angles...

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Bibliographic Details
Main Authors: Gongxue Wang, Lingmei Jiang, Shirui Hao, Xiaojing Liu, Huizhen Cui
Format: Conference Proceeding
Language:English
Subjects:
Artificial satellites
cloud
Clouds
Earth
Fractional snow cover
MODIS
Remote sensing
Snow
Spatial resolution
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Summary:The Moderate Resolution Imaging Spectroradiometer (MODIS) fractional snow cover products may have significant errors due to cloud contamination, varying viewing geometry and complex surface properties. To improve snow and cloud discrimination with a particular interest in large sensor viewing angles, we utilize a reinterpretation test accounting for temporal surface variability to discard false positives and recover false negatives. This method is applied to MODIS fractional snow cover products including MOD10A1 and MODSCAG, then evaluated with reference snow cover generated from Landsat-8 Operational Land Imager (OLI) data. Rather than simply implementing evaluation at the normative 500 m spatial resolution, the expansion of pixel size is considered. Preliminary results indicate that this method significantly improves the precision and F-score of these two snow cover products, especially MODSCAG.
ISSN:2153-7003
DOI:10.1109/IGARSS.2017.8127042