The detection of cloud-free snow-covered areas using AATSR measurements

Abstract

A new method to detect cloud-free snow-covered areas has been developed using the measurements by the Advanced Along Track Scanning Radiometer (AATSR) on board the ENVISAT satellite in order to discriminate clear snow fields for the retrieval of aerosol optical thickness or snow properties. The algorithm uses seven AATSR channels from visible (VIS) to thermal infrared (TIR) and analyses the spectral behaviour of each pixel in order to recognize the spectral signature of snow. The algorithm includes a set of relative thresholds and combines all seven channels into one flexible criterion, which allows us to filter out all the pixels with spectral behaviour similar to that of snow. The algorithm does not use any kind of morphological criteria and does not require the studied surface to have any special structure. The snow spectral shape criterion was determined by a comprehensive theoretical study, which included radiative transfer simulations for various atmospheric conditions as well as studying existing models and measurements of optical and physical properties of snow in different spectral bands. The method has been optimized to detect cloud-free snow-covered areas, and does not produce cloud/land/ocean/snow mask. However, the algorithm can be extended and able to discriminate various kinds of surfaces. The presented method has been validated against Micro Pulse Lidar data and compared to Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask over snow-covered areas, showing quite good correspondence to each other. Comparison of both MODIS cloud mask and presented snow mask to AATSR operational cloud mask showed that in some cases of snow surface the accuracy of AATSR operational cloud mask is questionable. © 2010 Author(s).