About this Earth and Planetary Sciences article

Mapping crop yield spatial variability using Sentinel-2 vegetation indices in Ethiopia by Gizachew Ayalew Tiruneh; Derege Tsegaye Meshesha; Enyew Adgo; Atsushi Tsunekawa; Nigussie Haregeweyn; Ayele Almaw Fenta; Tiringo Yilak Alemayehu; Temesgen Mulualem; Genetu Fekadu; Simeneh Demissie; José Miguel Reichert is a Earth and Planetary Sciences article available to read on EtoBox.

## Abstract Crop yield prediction before harvest is a key issue in managing agricultural policies and making the best decisions for the future. Using remote sensing techniques in yield estimation studies is one of the important steps for many countries to reach their agricultural targets. However, crop yield estimates rely on labor-intensive surveys in Ethiopia. To solve this, we used Sentinel-2, crop canopy analyzer, and ground-truthing data to estimate grain yield (GY) and aboveground biomass (AGB) of two major crops, teff and finger millet, in 2020 and 2021 in Ethiopia’s Aba Gerima catchment. We performed a supervised classification of October Sentinel-2 images at the tillering stage. Among vegetation indices and leaf area index (LAI) used to predict teff and finger millet GY and AGB, the enhanced vegetation index (EVI) and normalized-difference VI (NDVI) provided the best fit to the data. NDVI and EVI most influenced teff AGB (__R__^2^ = 0.87; RMSE = 0.50 ton/ha) and GY (__R__^2^ = 0.84; RMSE = 0.14 ton/ha), and NDVI most influenced finger millet AGB (__R__^2^ = 0.87; RMSE = 0.98 ton/ha) and GY (__R__^2^ = 0.87; RMSE = 0.22 ton/ha). We found a close association between GY and A

Author

Gizachew Ayalew Tiruneh; Derege Tsegaye Meshesha; Enyew Adgo; Atsushi Tsunekawa; Nigussie Haregeweyn; Ayele Almaw Fenta; Tiringo Yilak Alemayehu; Temesgen Mulualem; Genetu Fekadu; Simeneh Demissie; José Miguel Reichert

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Earth and Planetary Sciences (Physical Sciences)