Abstract
The performance of a new algorithm for binary snow cover monitoring based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images at 250 m resolution is validated using snow cover maps (SCA) based on Landsat 7 ETM+ images and in situ snow depth measurements from ground stations in selected test sites in Central Europe. The advantages of the proposed algorithm are the improved ground resolution of 250 m and the near real-time availability with respect to the 500 m standard National Aeronautics and Space Administration (NASA) MODIS snow products (MOD10 and MYD10). It allows a more accurate snow cover monitoring at a local scale, especially in mountainous areas characterized by large landscape heterogeneity. The near real-time delivery makes the product valuable as input for hydrological models, e.g., for flood forecast. A comparison to sixteen snow cover maps derived from Landsat ETM/ETM+ showed an overall accuracy of 88.1%, which increases to 93.6% in areas outside of forests. A comparison of the SCA derived from the proposed algorithm with standard MODIS products, MYD10 and MOD10, indicates an agreement of around 85.4% with major discrepancies in forested areas. The validation of MODIS snow cover maps with 148 in situ snow depth measurements shows an accuracy ranging from 94% to around 82%, where the lowest accuracies is found in very rugged terrain restricted to in situ stations along north facing slopes, which lie in shadow in winter during the early morning acquisition.
Highlights
Optical satellite images with high temporal resolution (Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS)) are exploited for snow cover mapping thanks to their daily availability [1,2]
To improve the snow detection, especially in heterogeneous areas, some previous works focused on the estimation of the snow cover fraction in a 500 m MODIS pixel using the additional information of the two MODIS 250 m channels [16,17]
The EURAC algorithm proposed in [18] detects the snow cover by exploiting the 250 m resolution bands of MODIS in the red (B1 centered at 645 nm) and infrared (B2 centered at 858.5 nm) spectrum, as well as the Normalized Difference Vegetation Index (NDVI)
Summary
Optical satellite images with high temporal resolution (Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS)) are exploited for snow cover mapping thanks to their daily availability [1,2]. To improve the snow detection, especially in heterogeneous areas, some previous works focused on the estimation of the snow cover fraction in a 500 m MODIS pixel using the additional information of the two MODIS 250 m channels [16,17] In this context, a new algorithm based on MODIS images has been proposed in a companion paper [18]. The EURAC algorithm proposed in [18] detects the snow cover by exploiting the 250 m resolution bands of MODIS in the red (B1 centered at 645 nm) and infrared (B2 centered at 858.5 nm) spectrum, as well as the Normalized Difference Vegetation Index (NDVI).
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