Analysis of Relationship between Grain Yield and NDVI from MODIS in the Fez-Meknes Region, Morocco

Author:

Belmahi Mohamed1ORCID,Hanchane Mohamed1ORCID,Krakauer Nir Y.23ORCID,Kessabi Ridouane1ORCID,Bouayad Hind4,Mahjoub Aziz5,Zouhri Driss1

Affiliation:

1. Department of Geography, FLDM, Sidi Mohamed Ben Abdellah University, Fez 30050, Morocco

2. Department of Civil Engineering, The City College of New York, New York, NY 10031, USA

3. Department of Earth and Environmental Sciences, City University of New York Graduate Center, New York, NY 10016, USA

4. Department of Geography, FLH, Hassan II University, Mohammedia 28810, Morocco

5. Department of Geography, FLH, Hassan II University, Ben M’Sik, Casablanca 20450, Morocco

Abstract

Exploring the relationship between cereal yield and the remotely sensed normalized difference vegetation index (NDVI) is of great importance to decision-makers and agricultural stakeholders. In this study, an approach based on the Pearson correlation coefficient and linear regression is carried out to reveal the relationship between cereal yield and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data in the Fez-Meknes region of Morocco. The results obtained show strong correlations reaching 0.70 to 0.89 between the NDVI and grain yield. The linear regression model explains 58 to 79% of the variability in yield in regional provinces marked by the importance of cereal cultivation, and 51 to 53% in the mountainous provinces with less agricultural land devoted to major cereals. The regression slopes indicate that a 0.1 increase in the NDVI results in an expected increase in grain yield of 4.9 to 8.7 quintals (q) per ha, with an average of 6.8 q/ha throughout the Fez-Meknes region. The RMSE ranges from 2.12 to 4.96 q/ha. These results are promising in terms of early yield forecasting based on MODIS-NDVI data, and consequently, in terms of grain import planning, especially since the national grain production does not cover the demand. Such remote sensing data are therefore essential for administrations that are in charge of food security decisions.

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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