The most likely scenario for the next decades presents strong modifications in the global environment, including increase of the atmospheric concentration of CO2 and other trace gases, climate change and intensification of the impacts caused by the man's action. These changes may cause important modifications in the composition, structure and distribution of the ecosystems on the planet, therefore a precise monitoring of the changes in the terrestrial biosphere is extremely important. The detection of the interannual variability and long-term trends in the ecosystems structure and dynamics will allow obtaining indications of change that would otherwise be unnoticed until the beginning of the transformation of the biome. Among the planetary ecosystems, one of the more threatened is the South America tropical forest, with the Atlantic Forest nearly devastated and the Amazonian Tropical Forest deforestation continuing at a rate that varies between 14,000 and 28,000 km2 a year. In this scenario of deforestation and climate change, the monitoring of the tropical forest is important to identify in advance changes in this unique ecosystem. Not just the deforested area should be monitored, but the composition, structure and dynamics of the forest should be monitored. The composition and structure of an ecosystem depend basically on its dynamics, i.e., on the rate of fixation of carbon and on its mortality rate. The carbon fixation rate of an ecosystem, or net primary production (NPP), is the net flux of carbon from the atmosphere to the plants, and is the difference between the gross primary production (GPP) and the autotrophic respiration of the ecosystems (RA), integrated through time. NPP can be estimated by several methodologies, like field measurements, remote sensing and modeling. In the field measurements, increments of the biomass (leaves, stems, trunks and roots) are monitored through time. This methodology is the most traditional, expensive and difficult, being usually used at experimental plots of reduced dimensions. Their estimates are of limited application for regional estimates. This work develops a regional algorithm, named RATE, for the automatic monitoring of the rate of fixation of carbon (NPP) by the Tropical Forests of South America. The algorithm is based on remote sensing data from the MODIS sensor (products MOD12Q1 and MOD15A2), meteorological data from the NCEP/NCAR reanalysis, and modeling. The assimilation of the MOD15A2 Leaf area index (LAI) and the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) used in the RATE algorithm presented satisfactory results for the values of LAI and FAPAR, compared against observed values, generating a database for the Amazonian Forest superior than the original product MOD15A2. In the Amazonian Forest sites, the algorithm RATE presented values of NPP closer to the observed, when compared to the estimates of the MODIS NPP product (MOD17A3), while it presented values of NPP similar to the MOD17A3 for the Atlantic Forest site estimate. RATE demonstrated to be reliable for the estimate of the rate of fixation of carbon by Tropical Forests for the specific conditions of South America with an average error of 2.41%.