Abstract
This paper presents an improved algorithm for the retrieval of Leaf Area Index (LAI) from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery that has been specifically customized for mountain grasslands in the Alps. The main features of the proposed algorithm, which is based on the inversion of a radiative transfer model, are: i) a higher spatial resolution (250 m) with respect to the corresponding standard MODIS product and ii) tuning the model to the spectral characteristics of mountain grasslands.
To quantify the effects of the features of the proposed algorithm, the approach is first applied to a MODIS reflectance data time series from 2007 up-scaled to a 1 km spatial resolution for better comparison with the standard MODIS LAI product. In the next step, the benefit of the higher spatial resolution is assessed by applying the algorithm to a series of MODIS satellite images with a spatial resolution of 250 m acquired over the central Alps in the period 2005–2007. LAI estimates were validated for both temporal consistency and accuracy using ground measurement time series collected at three different study sites in the investigated area. The results obtained demonstrate the capability of the proposed algorithm to follow the expected temporal and range dynamics of LAI in this challenging environment, showing an overall RMSE accuracy of 1.68 (m2/m2). This approach thus opens a promising avenue for the exploitation of moderate resolution satellite data for novel and more accurate monitoring studies at a regional scale in mountain environments