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

Ernesto Sifuentes-Ibarra,Ronald E Ontiveros-Capurata,Ignacio Sánchez-Cohen,Waldo Ojeda-Bustamante

doi:10.5424/sjar/2020183-16269

Abstract

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.

Highlights

In Mexico, more than six million hectares are annually irrigated, representing almost a third of the agricultural area cultivated, and generating 50% of the total value of agricultural production (SIAP, 2019)
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), Enhanced Vegetation index (EVI) and Normalized Difference Vegetation Index (NDVI), with the phenological development (PD) of corn grown in large irrigation zones
The phenological phases determined with cumulative growing degree days (CGDD) were compared against the stages observed weekly in the fields

Summary

Introduction

In Mexico, more than six million hectares are annually irrigated, representing almost a third of the agricultural area cultivated, and generating 50% of the total value of agricultural production (SIAP, 2019). Ontiveros-Capurata and Ignacio Sánchez-Cohen and managed by Water Users Associations (WUAs), and 50735 Irrigation Units (IUs) that users operate autonomously (CONAGUA, 2019a,b). One of the main problems of these large areas is the low irrigation efficiencies (30 to 45%) at farm level, associated with poor irrigation service by WUAs and poor conduction efficiency (Sifuentes et al, 2015). To improve irrigation efficiency and service, detailed knowledge of the phenological development of crops is required to better couple irrigation to crops’ water demand that change with their phenological development (Espinosa et al, 2017). Efforts have been made to implement farm monitoring of crop phenology in Mexico’s IDs, its application has been limited due to the large quantity of irrigated areas, diversity of crops and high volumes of field information that are managed (Ojeda-Bustamante et al, 2007). In a scenario of high competition for limited resources, coupled with food security and the effects of climate change, agricultural monitoring becomes very important (Heupel et al, 2018)

Objectives

Methods

Results

Conclusion