Olives have been cultivated in the Mediterranean for millennia and traditional methods of cultivation have created a stable, sustainable ecosystem. In Crete, traditionally managed olive groves are internationally recognised as being of key significance in the island's landscape ecology. The trees provide a shaded under-story supporting limited cultivation and rich assemblages of perennial plants of considerable ecological/conservation significance.Unfortunately, recent changes (abandonment; replanting; mechanised cultivation; fertilizers/herbicide and irrigation) threaten these communities. Cumulatively these changes threaten the quality, diversity and sustainability of the ecosystem.Hitherto, remote sensing has enabled accurate delineation of olive extent but has offered no possibility of evaluating age, species, under-storey properties and diversity. Although sensors suitable for wide area mapping exhibit distinct variability in olive signatures the properties they represent have proved too complex to map.This study will exploit the potential of high resolution Airborne LiDAR and CASI to characterise distinct olive typologies (young/old, replanted/wild, (un)irrigated, (un)terraced. It will examine the unique potential of LiDAR for describing canopy vertical structure/properties and use ATM/CASI for classification of cover and productivity. The results will be scaled up using existing (E)TM, DEM and classification data to map the status of this important landscape system.