Abstract
In Mexico, the cultivation of corn is part of the daily diet, it is considered the crop with the greatest presence in the country, it constitutes an input for livestock activity, in addition to being the main source for obtaining industrial products. For its part, precision agriculture is based on applying the right number of inputs, at the right time and in the exact place. NDVI is the most popular greenness index, it helps understand vegetation health and land use remotely. The study consisted of carrying out an analysis by comparing the values obtained from this index estimated by the Sentinel-2 and Sequoia indirect remote sensors against the NDVI values estimated by the GreenSeeker terrestrial sensor, which is considered a direct measurement. The results obtained show a very high correlation with an r2 of 0.926 between the Sequoia sensor vs. GreenSeeker while an r2 ratio of 0.802 was obtained between the Sentine-2 sensor vs GreenSeeker. Which can be explained with the difference that exists in terms of spatial resolution between the Sentinel-2 and Sequoia sensors, while one has 10 meters per pixel, the other has 18 centimeters.
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