To explore precision farming profits, the variability within a plot can be evaluated using digital technology by different remote means. The objectives of this study were to determine crop coverage (CC) of soybean ( Glycine max (L.) Merril) with Normalized Difference Vegetation Index (NDVI) data obtained by digital photographs on the field and from the satellites LANDSAT (7 and 8), with an overpass each 16 days and a pixel of 30 m, and PROBA-V, which has daily frequency and 100 m of spatial resolution, in order to evaluate productivity differences between sectors of a 45 ha rainfed plot located at south of Córdoba city, Argentina. In the plot, sowed on 22/11/2014 and harvested on 10/04/2015, 16 sampling areas were established to record periodically photographs with a modified camera and, in 8 of them, supplementary crop information. A non-linear model was developed from NDVI data of digital camera (NDVI C ) to estimate the soybean CC that showed an appropriate predictive performance. Furthermore, NDVI data of LANDSAT (7 and 8) (NDVI L ) and PROBA-V (NDVI P-V ) were also applied to estimate CC, resulting in models whose structure and accuracy was similar to that obtained with the digital camera (R 2 = 0.956 and 0.939, respectively). According to the radiometric information the two instruments provide, the digital images classification procedure to determine CC requires increasing the threshold from 0.0 to 0.05 when soybean progresses towards the maturation and senescence stages and green material is mixed with the senescent one. Growing conditions were very favorable for soybean in 2014–2015, since precipitation (PP) not only showed a marked continuity with 60 rainy days during the cycle, but also 642 mm accumulated in this period far exceeded maximum evapotranspiration (ETmax) of 389 mm. The CC had a major development in all sectors, maintaining a complete coverage condition for more than 50 days during most of the reproductive stage. However, prevalent overcast sky restricted significantly solar radiation (SR) a...