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In the last decades, Mediterranean rural landscapes have undergone significant changes, with relevant considerable environmental and socio-economic impacts. These phenomena are often triggered by agricultural abandonment, especially in environmentally-sensitive areas, which are usually located in marginal and less profitable regions, and which could indeed irremediably compromise the identity and role of these Mediterranean landscapes. On the other hand, the progressive increase of available multi-source geodata allows to reconstruct the landscape original structure, providing new tools able to prevent negative impacts on environment. Hence, thanks to the development of increasingly advanced and open-source GIS tools, it is possible to implement several geodata typologies that can be mutually integrated in an increasingly efficient approach. In this paper the process of landscape reshaping pattern is analyzed in a study area of Basilicata region (Southern Italy) using remote sensing. In particular, the vegetation component of a landscape has been assessed by means of SAR images by using an artificial intelligence approach, that is machine learning to understand landscape dynamics in two different time periods. In this way, it has been possible to integrate data of different source and composition into landscape analysis methodologies, hence developing a suitable tool for planning and managing the rural landscape.