The use of multi-temporal NDVI measurements from AVHRR data for crop yield estimation and prediction

TLDR

The study explores using AVHRR‑derived vegetation index profiles to monitor crop yield. The authors conducted retrospective and predictive analyses (1986–1988 and 1989) in Northern Greece, using AVHRR NDVI profiles and recommending integration of an agro‑meteorological model during wheat grain‑filling. The NDVI‑yield linear model produced highly accurate estimates for wheat, cotton, rice, and maize, with predictions stabilizing 50–100 days before harvest, indicating promising operational crop monitoring.

Abstract

Abstract This paper investigates the potential of using vegetation index profiles from AVHRR data to monitor crop yield. A retrospective study and predictive study is presented, for 1986-1988 and 1989 respectively, for an area in Northern Greece. Results are encouraging for operational crop monitoring. Yield for wheat, cotton, rice and maize crops has been estimated to a high degree of accuracy using a simple linear relationship between NDVI and yield. However input from an agro-meteorological model is recommended to modify the model during the grain-filling period of the wheat crop. The estimates stabilize 50-100 days prior to harvest enabling an early assessment of crop yield to be made.