Estimation of the time lag occurring between vegetation indices and aridity indices in a Sicilian semi-arid catchment

The evolution of drought phenomena in a Sicilian semi-arid catchment has been analyzed processing both remote sensing images and climatic data for the period 1985-2000. The remote sensing dataset includes Landsat TM and ETM+ multispectral images, while the climatic dataset includes monthly rainfall and air temperature. The results have been specifically discussed for areas where it is possible to neglect agricultural activities and vegetation growth is only influenced by natural forcing. The main outcome of this study is the quantification of the time lag between the remote sensing retrieved vegetation indices and the aridity indices (AIs) calculated from climatic data. Moreover the obtained relationships between AI and vegetation index allow the determination of aridity index maps by means of remote sensing images instead of spatially interpolated temperature and rainfall climatic data.