Brazilian dairy farming is distributed throughout the national territory, generates thousands of direct and indirect jobs and has a significant participation in the gross domestic product (GDP). The annual national milk production is estimated at more than 30 billion liters, according to the IBGE (Brazilian Institute of Geography and Statistics), being concentrated in the Southeast, South and Midwest regions. The following mesoregions concentrate more than 40% of Brazilian milk production: Noroeste Rio-Grandense (State of Rio Grande do Sul), Triângulo/Alto Paranaíba and Zona da Mata (State of Minas Gerais), Oeste Catarinense (State of Santa Catarina), Sudoeste Paranaense and Oeste Paranaense (State of Paraná), and Sul Goiano and Centro Goiano (State of Goiás). According to IBGE data, the regions under this study have 60% of the grazing areas in the national territory, whose total is 158 million hectares, 98 million hectares of which are destined to pastures in the Southeast, South and Midwest. However, a significant part of the pasture areas has its productive capacity compromised, with 5% of the area classified by IBGE as pastures in poor condition. However, pasture conditions can vary seasonally and in the long run, annually, with accumulated loss of productivity and showing aspects of degradation. Thus, it is essential to develop and apply methodologies for the extraction of territorial information by remote sensing, aiming to evaluate the productive capacity based on vegetation indexes, in view of the great extension of pastures and their socioeconomic importance, which demand greater agility of survey of their conditions. Due to the heterogeneity of milk production, pasture productivity and condition, geospatial monitoring of milk producing regions emerges as a strategy to support the planning of actions for the sector. This research project aims at evaluating the trajectories of land use changes associated with pastures through time series of remote sensing images, using the NDVI (Normalized Difference Vegetation) index base of the Terra satellite-carried MODIS sensor (Moderate Resolution Imaging Spectroradiometer), which is made available by the USGS (United States Geological Survey). The methodology consists of collecting temporal data from NDVI images of pasture areas, in addition to observing sampled field spots and associating corresponding images with levels of vegetation vigor and pasture degradation, by means of remote sensing-based estimates of phenological metrics, temporal statistics and adoption of methods of analysis in the GIS (Geographic Information Systems). Crossings among climatological data, censitary data, and technical coefficients related to dairy production and herd will be carried out in order to develop methods for refinement and generation of maps for monitoring pasture areas. A WebGIS system is being developed for the presentation and territorial analysis of the results, concurrently with the publication of the results in geographic databases in Embrapa Dairy Cattle and Embrapa Food and Territories. At present, a methodology was developed in the project for mapping the temporal vigor of pastures, using NDVI / MODIS data for the Zona da Mata mesoregion of the State of Minas Gerais, as a test for application to other regions of Brazil. In addition to the maps of the temporal vigor of pastures, other geographic information plans related to the meteorological and productive variables of the milk production chain will be gathered and superimposed to be analyzed in the WebGIS system and internet repository. The crossing of geospatial data may assist in strategic territorial decision making applied in the monitoring and evaluation of policies aimed at recovering the productive capacity of pastures, increasing productivity and competitiveness of dairy farming.