Estimation of corn yield thro ugh image treatments obtained by Sentinel 2: case of Las Arenas, Acambay

Authors

  • Mónica Ivonne García-Martínez Facultad de Geografía-Universidad Autónoma del Estado de México. Ciudad Universitaria s/n. Toluca, Estado de México. CP. 50110
  • Xanat Antonio-Némiga Facultad de Geografía-Universidad Autónoma del Estado de México. Ciudad Universitaria s/n. Toluca, Estado de México. CP. 50110
  • José Francisco Ramírez-Dávila Facultad de Agronomía-Universidad Autónoma del Estado de México. Carretera Toluca-Ixtlahuaca km 15.5, El Cerrillo Piedras Blancas, Toluca, México. CP. 50200. https://orcid.org/0000-0002-8625-4655
  • Adán Salazar-Garibay Agencia Espacial Mexicana. Insurgentes sur 1685, Álvaro Obregón, Ciudad de México, México. CP. 01020 https://orcid.org/0000-0002-3764-6273

DOI:

https://doi.org/10.29312/remexca.v16i3.3636

Keywords:

biophysical indicators, corn production, vegetation indices

Abstract

Corn (Zea mays L.) is the basis of food and culture in the state of Mexico, so estimating its production to sustain a growing population is a current need. Therefore, images obtained by ESA Copernicus’ Sentinel 2 were used to estimate corn yield in plots in the localities of Las Arenas, Acambay, state of Mexico. The efficiency of various indices and biophysical indicators calculated with information from these images was tested to establish their correlation against the harvest measured in the field. The indices calculated in Sentinel 2 were: NDVI and EVI and the LAI and FAPAR indicators. In this region and under conditions of intense drought, the NDVI calculated in Sentinel 2 had the best predictive ability for corn yield (model fit r2= 0.79). Based on the correlation, the production of 10 randomly selected plots was estimated, demonstrating that, in the range of values between 0.4 and 0.5, NDVI is an excellent predictor of corn harvest under drought conditions, whereas higher NDVI values tend to overestimate yield by up to 1 t ha-1. This information is useful for estimating the harvest and insurance of agricultural production.

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References

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Published

2025-05-12

How to Cite

García-Martínez, Mónica Ivonne, Xanat Antonio-Némiga, José Francisco Ramírez-Dávila, and Adán Salazar-Garibay. 2025. “Estimation of Corn Yield Thro Ugh Image Treatments Obtained by Sentinel 2: Case of Las Arenas, Acambay”. Revista Mexicana De Ciencias Agrícolas 16 (3). México, ME:e3636. https://doi.org/10.29312/remexca.v16i3.3636.

Issue

Vol. 16 No. 3 (2025)

Section

Articles

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