Increasing the Accuracy of MODIS/Aqua Snow Product Using Quantitative Image Restoration Technique

Abstract

The National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer (MODIS)-based snow mask product critically uses 1.6 μm band 6. The snow mask algorithm for MODIS on Aqua has been adapted to use the 2.1 μm band 7, since some of Aqua's MODIS detectors are nonfunctional. We have previously introduced an algorithm for quantitative image restoration (QIR) that can restore missing pixels or scan lines, using multilinear regression with input from a spatial-spectral window in other bands. In this letter, we argue that the use of MODIS Aqua band 6 data restored with the QIR technique in the snow algorithm results in a higher accuracy snow product as compared to the current MODIS Aqua snow product based on band 7 data. We show this by comparing a QIR-restored band 6 based product to the band 7 based product, applied to MODIS Terra, where we have simulated the Aqua-like damage to band 6. We demonstrate improved performance on representative granules covering different surface land-type conditions.