Photosynthesis is a process by which carbon and energy enter ecosystems. The knowledge of where,when, and how carbon dioxide (CO2) is exchanged between terrestrial ecosystems and atmosphere is crucial to close the Earth's carbon budget and predict feedbacks in a likely warming climate. Gross photosynthesis (uptake of CO2) by vegetation is responsible for the gross primary production (GPP) of the ecosystem. Normally GPP refers to the sum of the photosynthesis by all leaves measured at the ecosystem scale. John Monteith proposed in 1972 a simple approach that has become the paradigm for understanding GPP. It considers GPP as proportional to the incident short wave radiation (PAR), the fractional absorption of that flux (fAPAR) and the radiation use conversion efficiency, also known as light-use efficiency (LUE). This simple equation involves a great deal of biological and biophysical complexity. Photosynthesis requires that the plant replace the water that inevitably escapes from its leaves when CO2 is taken up from the atmosphere. Plants also require a supply of nutrients. Physiological and developmental mechanisms operate to adjust the GPP to the availability of resources. Thus, different types of stresses can affect the efficiency. The different terms in Monteith's equation are emphasized by different scientists. Crop physiologists focus on the PAR term, which explains the seasonal growth of crops and year-to-year variation in yield. Early work within the remote sensing community focused on the fAPAR term, which is linked to canopy structure and condition (i.e. to green biomass). It has a clear seasonal evolution in deciduous species and shows limited variability in evergreen forest ecosystems. The fAPAR is a common biophysical product derived from different remote sensing missions through the inversion of radiative transfer models or from empirical relations with vegetation indices. More recently the strong influence of the LUE term on productivity --particularly in strongly seasonal and nutrient-limited and/or water stressed vegetation canopies-- has been recognized. Variation in LUE is significant over shorter time scales when water or temperature stress develop. The LUE has been shown to vary spatially between biomes, ecosystems, and plant species, and to vary temporally during the growing season, due to environmental and physiological limitations. LUE responds more rapidly than fAPAR to different environmental factors related to the energy balance, water availability and nutrient levels. For operational applications, LUE can be expressed as the product of a LUEmax (maximum light-use efficiency), which depends on cover type, and different terms accounting for the reduction in efficiency due to different types of stress. The computation of these terms frequently requires meteorological data, which are seldom available at the needed spatial and temporal scales. The Monteith's approach provides the theoretical basis for most production efficiency models (PEMs), also known as light-use-efficiency (LUE) models: the MODIS-GPP model describes the global terrestrial photosynthesis at 1 km spatial scale and various time steps; the parametric model C-Fix has been applied to estimate forest GPP in several European countries and the modified C-Fix also takes into account the short-term water stress, a typical feature of the hot and dry Mediterranean summer. These models use remotely sensed data as well as meteorological data. In most PEMs, fAPAR is the only satellite-derived variable and, as such, it provides the link between ecosystem function and structure. Validation of satellite-derived GPP products is problematic. The development of eddy covariance (EC) as a method for quantifying the carbon, water, and energy balance over so-called "flux sites" has provided observational data to test and calibrate models; but the EC towers measure net CO2 exchange. GPP is obtained from these measurements after correcting them for respiratory losses (about half). The density of sampling is never enough to get regional or continental scale GPP. This is the domain of models. The modeling approaches also have specific limitations concerning: (i) the uncertainties of vegetation indices due to the presence of soil background mainly in sparse areas, and due to cloud and aerosol contamination problems, (ii) errors in the re-analysis of meteorological data, and (iii) difficulty constraining the light-use-efficiency term. The quality assessment of GPP products is rather complicated by the fact that GPP cannot be measured directly on a geographically relevant scale. In this Thesis, a model to estimate GPP for Mediterranean ecosystems at regional scale is proposed. The three terms in Monteith's equation have been obtained following procedures optimized for the study area, Spain (excluding Canary Islands). The "optimized model" is driven by meteorological and satellite data (MODIS/TERRA and SEVIRI/MSG). Considering the peculiarities of the study area, i.e., the diversity of the vegetation type dynamics and its spatial heterogeneity, the algorithm has been developed to run at a daily time step (to capture the dynamics even in agro-ecosystems) and 1 km spatial resolution (to assure that the spatial resolution of the remote sensing estimates is comparable to the footprint of ground estimates). Thus, the inputs of the model have been retrieved at these temporal and spatial resolutions. The daily GPP product obtained as explained above is difficult to validate due to the lack of ground GPP data. Nevertheless, GPP estimations from several eddy covariance (EC) towers have been used. These towers belong to the European Fluxes Database Cluster (http://www.europe-fluxdata.eu). By chance, these EC towers are mainly located in the semi-arid areas, which are more difficult to model due to their larger soil background effects. Thus, this direct validation of the GPP product serves to establish its upper uncertainty level. Moreover, an indirect validation, by means of an inter-comparison with two other operational products (from MODIS and Copernicus), is carried out. The results have been highly satisfactory and promising. A further analysis of the percentage of variance associated with each input of the Monteith's equation clearly evidences the role of the water stress in the inter-annual variation of GPP in Mediterranean ecosystems.El IPCC (Intergovernmental Panel onClimateChange) apunta que, sin una reducción de las emisiones antropogénicas de gases de efecto invernadero, la temperatura media del planeta aumentaría y el sistema climático mundial experimentaría durante el siglo XXI cambios muy probablemente mayores a los ya observados durante el siglo XX. Los ecosistemas terrestres desarrollan un papel fundamental en el ciclo del carbono a través de la fotosíntesis, la respiración, combustión de biomasa y la descomposición. La energía es fijada mediante fotosíntesis y es directamente empleada por la vegetación para su crecimiento produciendo materia orgánica que será posteriormente consumida por microorganismos y resto de seres vivos de manera directa o indirecta. La producción primaria bruta (GPP), i.e., el carbono fijado por la vegetación a través de la fotosíntesis, se puede estimar utilizando el modelo clásico de Monteith. Según el mismo, la GPP viene dada por el producto de tres variables: la radiación incidente fotosintéticamente activa (PAR), la fracción de PAR absorbida por la cubierta vegetal (fAPAR) y la eficiencia en el uso de la radiación (LUE). En el trabajo de tesis realizado se ha tratado la problemática de la obtención de estimaciones diarias de GPP para España. Esto involucra la investigación y mejora de las variables que componen el modelo de Monteith. Para ello se han adaptado, mejorado y desarrollado nuevas metodologías para la obtención de la LUE, la PAR y la fAPAR. Para la obtención de la PAR se han aplicado dos metodologías complementarias: (i) La primera estima la radiación a partir de datos de estación de otras variables meteorológicas (como temperatura y precipitación) mediante la construcción de diversos modelos (redes neuronales, procesos regresión mediante kernels,…), y obtiene los mapas a partir de la espacialización de dichas variables puntuales. (ii) La segunda obtiene el PAR a partir de las imágenes de irradiancia del satélite MSG (Meteosat Segunda Generación), e incorpora además un remuestreo de dichas imágenes y una corrección topográfica (por elevación). Para la obtención fAPAR se han aplicado algoritmos operacionales avalados y se han post-procesado para la corrección de huecos y ruido en las series temporales para aumentar la consistencia de las mismas. Finalmente, para la obtención de la LUE se han empleado cartografías híbridas del tipo de cubierta vegetal adaptadas al área de estudio, se han aplicado estimadores a partir de variables meteorológicas (coeficientes de estrés hídrico y por bajas temperaturas) y se ha evaluado el potencial de índices espectrales a partir de datos de satélite como el índice de reflectividad fotoquímico (PRI) u otros índices espectrales sensibles al contenido en agua de la cubierta. Finalmente los resultados de las estimaciones de GPP se han validado de forma directa sobre datos de estaciones terrestres (torres Eddy covariance) y de forma indirecta por comparación con otros productos de satélite (productos de la NASA obtenidos mediante MODIS y Copernicus DMP). Adicionalmente se ha realizado un análisis del potencial explicativo de las variables de entrada para de esta forma observar patrones espaciales relacionados con la relevancia de su variabilidad temporal en las estimaciones del modelo optimizado en el trabajo de tesis.