Improving the monitoring of corn phenology in large agricultural areas using remote sensing data series

• Sifuentes-Ibarra, Ernesto ^[1] ; Ojeda-Bustamante, Waldo ^[2] ; Ontiveros-Capurata, Ronald E. ^[3] ; Sánchez-Cohen, Ignacio ^[4]
  1. [1] INIFAP, Campo Experimental Valle del Fuerte. Carretera internacional México-Nogales km 1609, Juan José Ríos, Sinaloa 81110
  2. [2] Colegio Mexicano de Ingenieros en Irrigación, Vicente Garrido No. 106, Cuernavaca, Morelos 62000
  3. [3] Instituto Mexicano de Tecnología del Agua, Subcoordinación de Posgrado. Paseo Cuauhnáhuac 8532, Progreso, Jiutepec, Morelos 62550
  4. [4] INIFAP, Centro Nacional de Investigación Disciplinaria en Relación Agua-Suelo-Planta-Atmósfera. Km. 6.5 Margen derecha canal de Sacramento, Gómez Palacio, Durango 35150

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• Localización: Spanish journal of agricultural research, ISSN-e 2171-9292, ISSN 1695-971X, Vol. 18, Nº. 3, 2020
• Idioma: inglés
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  • Aim of study: Mexico's large irrigation areas demand non-structural actions to improve the irrigation service, such as monitoring crop phenology; however, its application has been limited by the large volumes of field information generated, diversity of crop management and climatic variability. The objective of this study was to generate and validate a methodology to monitor corn (Zea mays L.) phenology from the historical relationship of the vegetation indexes (VIs), EVI and NDVI, with the phenological development (PD) of corn grown in large irrigation zones.Area of study: Irrigation District (ID) 075 “Valle del Fuerte”, northern Sinaloa, Mexico.Material and methods: We used a database of 20 years of climate, field crop growth and crop phenology data, and Landsat satellite images. A methodology was proposed on a large scale supported with GIS and remote sensing data series.Main results: The methodology was validated in 19 plots with an acceptable correlation between observed PD and estimated PD for the two VIs, with slightly better values for EVI than for NDVI. NDVI and EVI models agreed with experimental PD observations in 92.1% of the farms used to validate the methodology, in 2.5% only the NDVI model coincided with the real, in 3.1% only the EVI model coincided, and in 2.3% both models disagreed with observation, generated a stage out of phase with respect to the real phenological stage.Research highlights: is possible to generalize the methodology applied to large irrigation zones with remote sensing data and GIS.