The main goal of Precision agriculture concepts is enabling the field management practices considering its spatial-temporal variability. Management zones can be defined based on the variables that impact directly or indirectly the performance of a specific field, as soil attributes, topography and crop yield. For yield analysis, due the high cost and low accessibility of on-board technology in several countries and for different crops, the analysis of satellite images, once the sensors are developed based on the spectral response of vegetation, soil, water and its interactions, has been widely used as an alternative data input for analysis of the performance zones inside of the field. Particularly for the corn seed production, once the fields must be harvested in ear buck with pickers mainly to preserve the genetic potential factors, the yield monitoring by harvesting is under developing and the remote sensing can be a powerful product to support this development and an important auxiliary data input to the management zones creation. In this context, the main objective of this project was to validate the use of the variabilities’ zones obtained from EVI (Enhanced Vegetation Index) time-series analysis as one of the data inputs for a methodology to reach the management zones map for Corn Seed Production fields. The EVI was processed from Landsat 8 images of 3 different seasons, resulting in a consolidated temporal image with sub-field variability. Besides temporal EVI, topography and electrical conductivity were processed and the field was distinguished on 3 different zones, High, Medium and Low Potential of Performance on yield. During the harvested period, 90 plot samples (6 lines in 10m) of ear was manually collected from the field for each zone to obtain the yield and the Zonal Spatial Analysis tool was applied. The descriptive statistics showed that the High, Medium and Low zones presented, 7.6, 7.4 and 7.3 kg of corn seeds/plot sample of Shell Weight (13% of moisture) and 39.8, 39.2 and 38.6 SSU (Saleable Seed Unit). A satellite image was collected one month before harvesting and presented respectively, 0.36, 0.35 and 0.32 of vegetation index (EVI normalized on -1 to 1). The results for this specific field showed the promissory value of the vegetation index obtained by remote sensors as a parameter part of management zones variability analysis, mainly for variable rate management for inputs.