Vegetation Indices derived from Earth Observation Satellite data have been broadly used for a wide range of ecological applications. One of such applications is vegetation monitoring. Properties of NDVI time series can be summarized in several metrics of the NDVI annual curve, including metrics that measure attributes related with primary production and with phenology, which can provide information about the condition and functioning of vegetation and ecosystems, related with the exchanges of matter and energy. In this study, we use a consistency analysis approach to compare the inter-annual trends in attributes of vegetation dynamics and ecosystem functioning obtained from two NDVI time series products, from two different satellite sensors (Terra/MODIS and SPOT/VGT2). We also discuss the use of outputs from analyses based on data from multiple sensors to enhance the assessment and monitoring of condition and changes in such attributes. Results show low consistency in trends of the selected metrics, between the two datasets used, including the relative proportions of significant and non-significant, and positive and negative trends detected, as well as in the magnitude of the trends detected. Thus, the use of different datasets and/or sensors for the assessment of trends in attributes of vegetation dynamics and ecosystem functioning can potentially lead to different conclusions about environmental condition and change at regional scale, which can have an impact on reporting, management policies, and decision-making. To cope with this problem, when evaluation of the accurateness of the results (i.e. validation with ground truth like, e.g., phenological observations with dedicated stations) is not available and/or possible, we suggest using a consistency analysis of outputs from two (or more) different sources (i.e. datasets/sensors), like the one employed in this study. This approach allows to identify the main areas where the main trends in attributes of vegetation dynamics and ecosystem functioning are likely to have occurred, within a target region and period of time.