The growing demands for energy crops require a great deal of foresight and planning for sustainable growth and management. The HYPERSPEC project seeks for an integrated multi-scale approach to develop a new methodology to derive spatially distributed information of the biomass potential and the related bioenergy potential (in particular the biomethane potential, BMP) on the plot and the regional scale. Nowadays airborne hyperspectral remote sensing is accepted as an extremely powerful tool for a wide variety of applications in the field of agriculture, due to the ability of producing scientific quality spectroscopic data at high spatial resolution. For environmental studies such systems provide an information level that is not assessable using classical remote sensing technologies, thanks to the combination of a high spectral (up to 500 channels within the 400 – 2500 nm wavelength range) and spatial resolution (0.4 – 5 m). Airborne remote sensing has been recognized as a valuable agronomic tool that provides information to scientists, consultants, and producers about the status of their crops. Since spectral signatures are unique to plant species and their state, this information can be used not only to detect nutrient and water deficiencies but in addition to retrieve biochemical parameters and to assess the health state of plants.The selected methodology in the HYPERPEC project will combine ground based and airborne hyperspectral measurements and a crop growth modeling approach. The method will be tested on several permanent test fields with different maize varieties that constitute the major bioenergy crop in Luxembourg and with sorghum. The planned activities within this project are in line with the efforts of Luxembourg’s Government to put an emphasis on the production of energy from renewable sources and to lookout for new technologies that will increase the efficiency of energy from alternative sources. The methodology is also of relevance in the perspective of new forthcoming hyperspectral satellite missions such as the German Environmental Mapping and Analysis Program (EnMAP, envisaged launch in 2012) that will provide high quality hyperspectral image data on a timely and frequent basis.The project goals will be achieved by an international team of experts that are well experienced in the fields of remote sensing (CRP-GL, VITO, Trier University), agriculture (ASTA, CONVIS, CIPF) and crop growth modelling (JRC, Italy). Furthermore this project will benefit from activities in ongoing FNR and EU funded projects at CGRP-GL, including LUXCYCLE, BIOGAZ and BIONIR.