The strong impact of weather on crops in the world led to the development of locally adapted agro climatic indices. One of these indices is the well known Penman-FAO index [6][7] which is strongly related to crop yields in many arid and semi-arid regions of the world. (FAO is the Food and Agriculture Organization of the United Nations.) Recent developments in satellite imagery have allowed the derivation of new agro climatic indices from vegetation reflectance measures, which are better related to crops in many cases, particularly in arid and semi-arid regions. The Normalized Difference Vegetation Index (NDVI), as registered since 1980 by the AVHRR (Advanced Very High Resolution Radio meter) sensor, is one of these satellite indices. The AVHRR sensor is a broadband, 4- or 5-channel scanning radio meter, sensing in the visible, near-infrared and thermal infrared portions of the electromagnetic spectrum. The NDVI has been extensively used in vegetation monitoring, crop yield assessment and forecasting [8][9][10][11]. Most statistical procedures rely on relatively simple frequency analysis of time series at decadal, monthly and annual levels as well asspatial interpolation. However, statistical analysis of climate remains an expert knowledge art that is very specific to local conditions.