An algorithm for the derivation of atmospheric and surface biophysical products from the MEdium Resolution Imaging Spectrometer Instrument (MERIS) on board ENVIronmental SATellite (ENVISAT/MERIS) Level 1b data over land has been developed. Georectified aerosol optical thickness (AOT), columnar water vapor (CWV), spectral surface reflectance and chlorophyll fluorescence (CF) maps are generated. Emphasis has been put on implementing a robust software able to provide those products on an operational manner, making no use of ancillary parameters apart from those attached to MERIS images. For this reason, it has been named Self-Contained Atmospheric Parameters Estimation from MERIS data (SCAPE-M). The fundamentals of the algorithm and the validation of the derived products are presented in this thesis. Errors of ±0.03, ±4% and ±8% have been estimated for AOT, CWV and surface reflectance retrievals, respectively, by means of a sensitivity analysis. More than 200 MERIS images have been processed in order to assess the method performance under a range of atmospheric and geographical conditions. A good comparison is found between SCAPE-M AOT retrievals and ground-based measurements taken during the SPectra bARrax Campaigns (SPARC) 2003 and 2004, except for a date when an episode of Saharan dust intrusion was detected. Comparison of SCAPE-M retrievals with data from AErosol RObotic NETwork (AERONET) stations showed a square Pearson's correlation coefficient R2 of about 0.7-0.8. Those values grow up to more than 0.9 in the case of CWV after comparison with the same stations. A good correlation is also found with the ESA Level 2 official CWV product, although slight different performances with varying surface elevation are detected. Retrieved surface reflectance maps have been intercompared with reflectance data derived from MERIS images by the Bremen AErosol Retrieval (BAER) method in the first place.