Research Article
Open Access
Climate-Driven Vegetation Dynamics and Future Projection over Ethiopia Using NDVI and Google Earth Engine
1
Eastern and Central Oromia Meteorological Service Centre, Ethiopian Meteorological Institute, Addis Ababa 1093, Ethiopia
* Corresponding Author:
Gezahegn Mergia Tullu,
[email protected]
Volume 1, Issue 2
2026
Received: 24 May 2026
Revised: 24 June 2026
Accepted: 29 June 2026
Published: 19 August 2026
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CC BY 4.0 License
Article Information
Published in
Journal of Geoscience and Earth Observation
Volume/Issue
Volume 1, Issue 2, 2026
Pages
85-100
Abstract
Climate change increasingly affects vegetation dynamics and ecosystem health worldwide. This study investigates historical and projected vegetation dynamics in Ethiopia using the Normalized Difference Vegetation Index (NDVI) to assess spatial and temporal patterns of vegetation change and their relationship with climate variability. Seasonal NDVI climatology, anomalies, trends, and future projections were analyzed using AVHRR and MODIS satellite datasets combined with CMIP6 climate projections. Google Earth Engine (GEE) JavaScript workflows were employed to examine vegetation dynamics during the October--January (ONDJ), February--May (FMAM), and June--September (JJAS) seasons from 1991 to 2024 and to project NDVI changes for 2015--2100 under SSP2-4.5 and SSP5-8.5 scenarios. Regression analysis evaluated climate--NDVI relationships, while the Mann--Kendall test and Sen's slope estimator determined the significance and magnitude of vegetation trends. Results reveal substantial spatial variability in vegetation dynamics. Significant NDVI increases occurred in many highland regions, whereas declines were observed in drought-prone areas, particularly in eastern Ethiopia and the Afar region. Decadal analyses (1991--2000, 2001--2010, 2011--2024) showed enhanced vegetation across northern, western, central, and southern Ethiopia, reflecting the combined influence of rainfall variability, climatic extremes, topography, and land cover. Future projections indicate moderate NDVI changes under SSP2-4.5 and greater spatial variability under SSP5-8.5, with potential greening in northern, western, central, and southwestern Ethiopia, and persistent vegetation stress in eastern and Afar areas. The study demonstrates the effectiveness of GEE for large-scale vegetation monitoring and provides valuable information for drought early-warning systems, climate-resilient agricultural planning, and ecosystem management in Ethiopia.
Graphical Abstract
Keywords
NDVI
vegetation trend
climate change
Ethiopia
google earth engine
Data Availability Statement
Data will be made available on request.
Funding
This work was supported without any funding.
Conflicts of Interest
The authors declare no conflicts of interest.
AI Use Statement
The authors declare that no generative AI was used in the preparation of this manuscript.
Ethical Approval and Consent to Participate
Not applicable.
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APA Style
Tullu, G. M. (2026). Climate-Driven Vegetation Dynamics and Future Projection over Ethiopia Using NDVI and Google Earth Engine. Journal of Geoscience and Earth Observation, 1(2), 85-100. https://doi.org/10.62762/JGEO.2026.291236
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TY - JOUR AU - Tullu, Gezahegn Mergia PY - 2026 DA - 2026/08/19 TI - Climate-Driven Vegetation Dynamics and Future Projection over Ethiopia Using NDVI and Google Earth Engine JO - Journal of Geoscience and Earth Observation T2 - Journal of Geoscience and Earth Observation JF - Journal of Geoscience and Earth Observation VL - 1 IS - 2 SP - 85 EP - 100 DO - 10.62762/JGEO.2026.291236 UR - https://www.icck.org/article/abs/JGEO.2026.291236 KW - NDVI KW - vegetation trend KW - climate change KW - Ethiopia KW - google earth engine AB - Climate change increasingly affects vegetation dynamics and ecosystem health worldwide. This study investigates historical and projected vegetation dynamics in Ethiopia using the Normalized Difference Vegetation Index (NDVI) to assess spatial and temporal patterns of vegetation change and their relationship with climate variability. Seasonal NDVI climatology, anomalies, trends, and future projections were analyzed using AVHRR and MODIS satellite datasets combined with CMIP6 climate projections. Google Earth Engine (GEE) JavaScript workflows were employed to examine vegetation dynamics during the October--January (ONDJ), February--May (FMAM), and June--September (JJAS) seasons from 1991 to 2024 and to project NDVI changes for 2015--2100 under SSP2-4.5 and SSP5-8.5 scenarios. Regression analysis evaluated climate--NDVI relationships, while the Mann--Kendall test and Sen's slope estimator determined the significance and magnitude of vegetation trends. Results reveal substantial spatial variability in vegetation dynamics. Significant NDVI increases occurred in many highland regions, whereas declines were observed in drought-prone areas, particularly in eastern Ethiopia and the Afar region. Decadal analyses (1991--2000, 2001--2010, 2011--2024) showed enhanced vegetation across northern, western, central, and southern Ethiopia, reflecting the combined influence of rainfall variability, climatic extremes, topography, and land cover. Future projections indicate moderate NDVI changes under SSP2-4.5 and greater spatial variability under SSP5-8.5, with potential greening in northern, western, central, and southwestern Ethiopia, and persistent vegetation stress in eastern and Afar areas. The study demonstrates the effectiveness of GEE for large-scale vegetation monitoring and provides valuable information for drought early-warning systems, climate-resilient agricultural planning, and ecosystem management in Ethiopia. SN - pending PB - Institute of Central Computation and Knowledge LA - English ER -
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@article{Tullu2026ClimateDri,
author = {Gezahegn Mergia Tullu},
title = {Climate-Driven Vegetation Dynamics and Future Projection over Ethiopia Using NDVI and Google Earth Engine},
journal = {Journal of Geoscience and Earth Observation},
year = {2026},
volume = {1},
number = {2},
pages = {85-100},
doi = {10.62762/JGEO.2026.291236},
url = {https://www.icck.org/article/abs/JGEO.2026.291236},
abstract = {Climate change increasingly affects vegetation dynamics and ecosystem health worldwide. This study investigates historical and projected vegetation dynamics in Ethiopia using the Normalized Difference Vegetation Index (NDVI) to assess spatial and temporal patterns of vegetation change and their relationship with climate variability. Seasonal NDVI climatology, anomalies, trends, and future projections were analyzed using AVHRR and MODIS satellite datasets combined with CMIP6 climate projections. Google Earth Engine (GEE) JavaScript workflows were employed to examine vegetation dynamics during the October--January (ONDJ), February--May (FMAM), and June--September (JJAS) seasons from 1991 to 2024 and to project NDVI changes for 2015--2100 under SSP2-4.5 and SSP5-8.5 scenarios. Regression analysis evaluated climate--NDVI relationships, while the Mann--Kendall test and Sen's slope estimator determined the significance and magnitude of vegetation trends. Results reveal substantial spatial variability in vegetation dynamics. Significant NDVI increases occurred in many highland regions, whereas declines were observed in drought-prone areas, particularly in eastern Ethiopia and the Afar region. Decadal analyses (1991--2000, 2001--2010, 2011--2024) showed enhanced vegetation across northern, western, central, and southern Ethiopia, reflecting the combined influence of rainfall variability, climatic extremes, topography, and land cover. Future projections indicate moderate NDVI changes under SSP2-4.5 and greater spatial variability under SSP5-8.5, with potential greening in northern, western, central, and southwestern Ethiopia, and persistent vegetation stress in eastern and Afar areas. The study demonstrates the effectiveness of GEE for large-scale vegetation monitoring and provides valuable information for drought early-warning systems, climate-resilient agricultural planning, and ecosystem management in Ethiopia.},
keywords = {NDVI, vegetation trend, climate change, Ethiopia, google earth engine},
issn = {pending},
publisher = {Institute of Central Computation and Knowledge}
}
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