The use of NDVI to improve cereals agriculture: A review

Abstract

In recent years, agriculture has moved to another level of evolution to cope with climate change as well as rapidly increasing population growth and food security issues, while integrating smart and advanced technologies with traditional agricultural approaches and this is called precision agriculture. Precision agriculture explores data from an Internet of Things (IoT) platform, satellites, or Unmanned Aerial System (UAS) to make the right decisions at the right time to optimize yields and reduce the environmental footprint. More recently, remote sensing has undergone a remarkable evolution, especially with the miniaturization of electronic components; this acquisition of information occurs by measuring the electromagnetic spectrum in the visible and invisible to the eye. For the analysis of remote sensing measurements, the Normalized Difference Vegetation Index (NDVI) is the most commonly used index to assess the vegetation of the observed target. It is calculated from red and near-infrared reflectance. This study presents a systematic review of works using NDVI to contribute to precision agriculture.