Methodology for prediction of corn yield using remote sensing satellite data in Central Mexico

Résumé 0

"The main goal of agricultural crop management in any country is to guarantee food resources for its population.The heterogeneity of corn-growing conditions in many countries, especially in Mexico makes accurate predictions of yieldahead of harvest time difficult. Such predictions are needed by the government to estimate, ahead of time, the amount ofcorn required to be imported to meet the expected domestic shortfall. In this paper, therefore, a methodology for theestimation of corn yield ahead of harvest time is developed for the conditions of intensive production systems in centralMexico. The method is based on the multi-temporal analysis of NOAA-AVHRR satellite images, and uses normalizeddifference vegetation indices (NDVIs), Degree-Days (DDs) and Leaf Area Indices (LAIs) to predict corn occurrence andyield. Results of the application of the methodology to successfully identify sites with corn, and to predict corn yield inCentral Mexico, are presented and discussed."