Applications of hyper spectral and radar remote sensing analysis : a case study of forest landscapes in Costa Rica The main objective this research was to assess two types of emerging remote sensing technology hyper spectral and SAR sensors for an exploratory data analysis of land covers in the south of Costa Rica. Hyper spectral data contain information in several narrow spectral bands in the optical domain which give information on the biochemical and structural properties of vegetation while the SAR data as an active system can penetrate the clouds making it a promising tool for ecosystem monitoring. The main hypothesis was that these two datasets would permit greater understanding of the spectral confusion between different land covers. From the hyper spectral point of view this knowledge could help to select and derive spectral signatures which serve as training data sets in supervised species classification in the optical domain. In the microwave domain fusion and derived bands increase the separability and permit greater forest non forest classification accuracy in non flat terrains. The hyper spectral information is based on two information sources. The first comes from two scenes of the space borne Earth Observing 1 mission with the Hyperion sensor and two scenes of the airborne hyper spectral sensor HyMap. The second hyper spectral data source was acquired from the field based hyper spectral clip prove system. Furthermore the microwave information corresponds to the TerraSAR X HH and VV polarized images ...