Alpine algorithms-time series of innovative remote sensing products for Alpine areas: Snow cover leaf area index and soil moisture

The derivation of bio-physical parameter time series from remote sensing data is of high importance for the monitoring and understanding of mountain ecosystems. However, their retrieval in mountain environments represents a challenging task due to the heterogeneous landscape and the topography. Already available global products may therefore present limitations in mountain areas. In this paper, innovative approaches for the derivation of snow cover, leaf area index (LAI), and soil moisture over the Alps are described, taking into account the peculiarity of the mountain areas. In order to account for the high heterogeneity, snow and leaf area index products rely on the use of 250 m spatial resolution MODIS data, in conjunction with elevation data and, in the case of soil moisture, radar data. Further, the correction of the topography on the remote sensing signal in implemented in all algorithms. Special conditions of mountain vegetation, such as snow in forests or the biophysical conditions of mountain grasslands, are also accounted for. The time series are used in conjunction in order to better understand key processes such as water and carbon cycles or vegetation phenology.