The Officine Galileo (OG) Hyperspectral Camera (HYC) (currently under development in the frame of the Hypseo ASI program) consists of an high spatial resolution (20 m) imaging spectrometer working in the visible and SWIR bands, to be embarked on future low earth orbit operational satellites. The mission requirements include monitoring of vegetation, coastal/internal waters and geology/hydrology. The instrument works with a swath of 20 Km and steering capability within 500-Km across-track. It operates in about 210 spectral bands of 10 nm of resolution. The objective of the present work is the evaluation of application performances of the HYC camera compared to those of multi- spectral sensors (e.g. ETM+/Landsat 7), carried out by means of images and products simulations. For this scope some airborne campaigns have been performed with hyper- spectral sensors (VIRS, MIVIS) in a test area of Tuscany region (1), with contemporaneous collection of ground/sea truth data. HYC and ETM+ radiance images have been simulated by means of surface reflectance maps obtained from the airborne sensors, applying the MODTRAN atmospheric code and the HYC (and ETM+) instrumental models (spatial, spectral and noise degradation). The retrieval of surface reflectance has been performed by means of an atmospheric correction algorithm based on the dark pixel method. Next, two test products (forest classification and river plumes analysis) have been simulated; the first based on a maximum likelihood classification method and the second based on multivariate regression analysis. The results have been validated with ground truth data for different atmospheric conditions. Classification error decreases from 22% (ETM+) to 13% (HYC), whereas suspended sediments accuracy error decreases from 24% (ETM+) to 15% (HYC) in the tested conditions. The implemented methodology has allowed studying the better trade-off between product accuracy and instrumental requirements.