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Subtropical forest loss resulting from conversion of forest to other land-cover types such as grassland, secondary forest, subsistence crop farms and small forest patches affects leaf nitrogen (N) stocks in the landscape. This study explores the utility of new remote sensing tools to model the spatial distribution of leaf N concentration in a forested landscape undergoing deforestation in KwaZulu-Natal, South Africa. Leaf N was mapped using models developed from RapidEye imagery; a relatively new space-borne multispectral sensor. RapidEye consists of five spectral bands in the visible to near infra-red (NIR) and has a spatial resolution of 5 m. MERIS terrestrial chlorophyll index derived from the RapidEye explained 50 % of the variance in leaf N across different land-cover types with a model standard error of prediction of 29 % (i.e. of the observed mean leaf N) when assessed on an independent test data …