Spatiotemporal trends in cropland phenology in the Nigerian Sahel derived from MODIS NDVI

Abstract Understanding how vegetation phenology is changing across dryland agricultural systems is crucial for predicting the effects of climate change and enhancing food system resilience. Here, we analyze two decades of seasonality changes in croplands across 10 states in Nigeria’s Sahel using MODIS MOD13A2 normalized difference vegetation index (NDVI) collection (2000–2022) and four key metrics: start of season (SOS), end of season (EOS), length of season (LOS), and NDVI amplitude (GSA). We fit mixed-effects models with sample (pixel)- and state-level random effects to quantify temporal trends and spatial variation. We used MANOVA and correlations to assess the multivariate structure and metric interrelationships. Our results reveal a significant delay in SOS (+0.26 d yr −1 ), no consistent temporal trend in EOS, and widespread shortening of growing seasons (LOS: −0.25 d yr −1 ). NDVI amplitude increased slightly (+0.000 36 yr −1 ), showing modest aggregate gains in peak vegetation vigor. Cumulative state-level changes show SOS delays of up to +15 d and LOS reductions exceeding 22 d in some states between 2000 and 2022. Sample-level analyses indicate high within-state heterogeneity, with random effects accounting for approximately 40%–55% of total variance. MANOVA results confirm a significant multivariate shift in seasonality structure, while cross-metric correlations show a strong coupling between delayed SOS and shortened LOS ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mi>r</mml:mi> <mml:mstyle scriptlevel="0"/> <mml:mo>≈</mml:mo> <mml:mstyle scriptlevel="0"/> <mml:mo>−</mml:mo> <mml:mn>0.82</mml:mn> </mml:mrow> </mml:math> ). Taken together, these findings highlight a vegetation system undergoing coherent yet spatially diverse transformation likely driven by climatic change and local land-surface processes. The observed trends have direct implications for rain-fed agriculture, food security, and climate adaptation strategies in northern Nigeria and the wider West African Sahel.

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Publication Details

Journal
Environmental Research Letters
Published
2026-04-21
DOI
https://doi.org/10.1088/1748-9326/ae628c
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatiotemporal trends in cropland phenology in the Nigerian Sahel derived from MODIS NDVI

Paulina Jaramillo, Doron Cohen, Fidelis Bologo
Environmental Research Letters
Remote Sensing in Agriculture
article

Spatiotemporal trends in cropland phenology in the Nigerian Sahel derived from MODIS NDVI

Paulina Jaramillo, Doron Cohen, Fidelis Bologo
article en

Abstract

Abstract Understanding how vegetation phenology is changing across dryland agricultural systems is crucial for predicting the effects of climate change and enhancing food system resilience. Here, we analyze two decades of seasonality changes in croplands across 10 states in Nigeria’s Sahel using MODIS MOD13A2 normalized difference vegetation index (NDVI) collection (2000–2022) and four key metrics: start of season (SOS), end of season (EOS), length of season (LOS), and NDVI amplitude (GSA). We fit mixed-effects models with sample (pixel)- and state-level random effects to quantify temporal trends and spatial variation. We used MANOVA and correlations to assess the multivariate structure and metric interrelationships. Our results reveal a significant delay in SOS (+0.26 d yr −1 ), no consistent temporal trend in EOS, and widespread shortening of growing seasons (LOS: −0.25 d yr −1 ). NDVI amplitude increased slightly (+0.000 36 yr −1 ), showing modest aggregate gains in peak vegetation vigor. Cumulative state-level changes show SOS delays of up to +15 d and LOS reductions exceeding 22 d in some states between 2000 and 2022. Sample-level analyses indicate high within-state heterogeneity, with random effects accounting for approximately 40%–55% of total variance. MANOVA results confirm a significant multivariate shift in seasonality structure, while cross-metric correlations show a strong coupling between delayed SOS and shortened LOS ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mi>r</mml:mi> <mml:mstyle scriptlevel="0"/> <mml:mo>≈</mml:mo> <mml:mstyle scriptlevel="0"/> <mml:mo>−</mml:mo> <mml:mn>0.82</mml:mn> </mml:mrow> </mml:math> ). Taken together, these findings highlight a vegetation system undergoing coherent yet spatially diverse transformation likely driven by climatic change and local land-surface processes. The observed trends have direct implications for rain-fed agriculture, food security, and climate adaptation strategies in northern Nigeria and the wider West African Sahel.

Environmental Research LettersVol. 21(9)
Rockefeller Foundation
Climate action
Openalex Percentile: Top 17%
Remote Sensing in Agriculture
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