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Abstract

This study assesses and analyzes the annual and seasonal changes in the Normalized Difference Vegetation Index (NDVI) in Wasit Province, Iraq, between 2020 and 2023. Vegetation cover (VC) variation serves as a key indicator of climate change impacts on ecosystems and agricultural productivity. The research employs satellite-derived NDVI and climate data to detect spatiotemporal changes across the region. Geographically, the Tigris River divides Wasit into two zones: the southern and southwestern parts exhibit higher NDVI values due to abundant water from river branches, whereas the northern and northeastern areas show lower values. A slight improvement in VC was observed in December 2020, likely due to increased Tigris River discharges. Findings indicate a gradual NDVI increase over the study period, with the highest value recorded during summer 2023 (2.94%), highlighting the role of irrigation and modern agricultural practices in enhancing VC beyond the influence of climate factors. Seasonal variations were evident, with summer NDVI values generally exceeding those in winter; the highest winter NDVI was in 2021 (2.40%). Three statistical methods were applied: correlation analysis, linear regression, and ANOVA. Results showed a weak negative correlation between NDVI and precipitation (r = -0.60), and a negligible correlation with air temperature (r = 0.06). ANOVA confirmed significant differences in NDVI values across the years (p = 0.0039), indicating real ecological changes rather than random variation. Using the ARIMA model for forecasting, NDVI is expected to continue a slight upward trend, reaching 0.442 in 2024 and 0.463 in 2025. This suggests a positive vegetation response driven more by improved agricultural and water management practices than by climatic changes.

Keywords

ARIMA model climate change GIS NDVI satellite imagery

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite
Khalbas, M. I. ., & Kadhum, J. H. . (2025). Assessing Seasonal Variations of Vegetation Cover Using NDVI in Context Climate Change in Wasit. Basrah Journal of Agricultural Sciences, 38(1), 324–335. Retrieved from https://bjas.bajas.edu.iq/index.php/bjas/article/view/2549
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References

  1. Al-Bahadli, T. H., Al-Mayah, A. A., & Salman, F. H. (2025). Relationship between vegetation cover and land surface temperature in Basra, Iraq. Journal of Agrometeorology, 27(1), 78–85. https://journal.agrimetassociation.org/index.php/jam/article/view/2799 .
  2. Albw Jbianah, M. I. K. & W. H. Hmeesh, (2021)“Estimation of Predictive Potential of Quasi-Biennial Oscillation (QBO) Cyclical Stratospheric Circulation in Tropical Zone for Long-Term Precipitation Forecast,” in Proc. 2021 Int. Conf. on Advance of Sustainable Engineering and its Application (ICASEA), Wasit, Iraq, pp. 141–146. https://doi.org10.1109/ICASEA53739.2021.9733078
  3. Al-Kindi, K. M., Al Nadhairi, R., & Al Akhzami, S. (2023). Dynamic change in normalized difference vegetation index (NDVI) from 2015 to 2021 in Dhofar, Southern Oman in response to the climate change. Agriculture, 13(3), 592. https://doi.org/10.3390/agriculture13030592
  4. Al-Kindi, K.M.; Al Nadhairi, R.; Al Akhzami, S. (2023) Dynamic Change in Normalised Vegetation Index (NDVI) from 2015, to 2021 in Dhofar, Southern Oman in Response to the Climate Change. Agriculture, 13, 592,. https://doi.org/10.3390/agriculture13030592
  5. Al-Maliki, M. H., Al-Aboodi, A. H., & Al-Khafaji, R. A. (2024). Computing and predicting the vegetation cover using NDVI under the conditions of climate changes for the period 2000–2024: A case study, Karbala City, Iraq. International Journal of Environment and Climate Change, 14(3), 112–124. https://www.researchgate.net/publication/389698294
  6. AL-Obaidey, E. S. (2019), “The study of NDVI fluctuation in southern Iraq (Hor Ibn Najim) using remote sensing data”, Al-Mustansiriyah J. Sci., vol. 30, no. 1, pp. 1–6, Aug., http://doi.org/10.23851/mjs.v30i1.556 http://doi.org/10.23851/mjs.v30i1.556
  7. Al-Saad, R. S., Al-Jubouri, S. M., & Kareem, M. A. (2023). Using the Normalized Difference Vegetation Index (NDVI) to study the change of vegetation cover in Thi-Qar Governorate, southern Iraq for the period from 1990–2022. Journal of Environmental Studies, 15(2), 45–58. https://www.researchgate.net/publication/387603998
  8. Al-Shamarti, H. K. A., Manji, O. B., & Albw Jbianah, M. I. K. (2019). Using monthly rainfall data to estimate rainfall erosivity factor of Iraq. Scientific Review – Engineering and Environmental Sciences, 28(3), 444–454. https://doi.org/10.22630/PNIKS.2019.28.3.41
  9. Cui, L., Pang, B., Zhao, G., Ban, C., Ren, M., Peng, D., Zuo, D., & Zhu, Z. (2022). Assessing the Sensitivity of Vegetation Cover to Climate Change in the Yarlung Zangbo River Basin Using Machine Learning Algorithms. Remote Sensing, 14(7), 1556., https://doi.org/10.3390/rs14071556
  10. Cui, L., Pang, B., Zhao, G., Ban, C., Ren, M., Peng, D., Zuo, D., & Zhu, Z. (2022). Assessing the sensitivity of vegetation cover to climate change in the Yarlung Zangbo River Basin using machine learning algorithms. Remote Sensing, 14(7), 1556. https://doi.org/10.3390/rs14071556
  11. Gupta, Ujjwal K., Vidit Shah, Markand P. Oza,( 2019) Forecasting and visualization of NDVI series using statistical methods through Web-GIS, Journal of Geomatics, 13 (2),237 – 241.
  12. Hassan, A.S. & Zaki, K.N. (2018), Decadal Analysis of Carbon Dioxide Emissions from Different State of Fossil Fuels in Iraq. Indian Journal of Public Health Research & Development, vol. 9(12), 865–868,. https://doi.org/10.5958/0976-5506.2018.01956.3
  13. Hersbach, H.; Bell, B.; Berrisford, P.; Hirahara, S.; Horányi, A.; Muñoz-Sabater, J.; Nicolas, J.; Peubey, C.; Radu, R.; Schepers, D.; et al. (2020) The ERA5 Global Reanalysis. Q. J. R. Meteorol. Soc., 146, 1999–2049. https://doi.org/10.1002/qj.3803
  14. Ibrahim, Ismail Ahmed, Moutaz Al-Dabbas(2021), Analysis of Climate Parameters as Indicators of Climate Changes in Central and Eastern Iraq: Khanaqin Climate Conditions as A Case Study. Iraqi Journal of Science, 62(12), 4747-4757. https://doi.org/10.24996/ijs.2021.62.12.13
  15. Khalaf, A. B. (2024). Using geospatial techniques to analysis the impact of climate change on water and agriculture resources: Case study Khanaqin District in Diyala, Iraq. Basrah Journal of Agricultural Sciences, 37(1), 55–70. https://doi.org/10.37077/25200860.2024.37.1.05
  16. Mahdi, S. A., & Jasim, S. (2023). Detection of Vegetation Cover Changes from 1988–2022 in the University of Baghdad Campus by Remote Sensing and GIS Techniques (Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI)). https://www.researchgate.net/publication/376543382
  17. Naif, S., Mahmood, D. & Al-Jiboori, M. (2020), Seasonal normalized difference vegetation index responses to air temperature and precipitation in Baghdad. Open Agriculture, 5(1), 631-637.. https://doi.org/10.1515/opag-2020-0065
  18. Piao, S., Wang, X., Park, T. (2020) Characteristics, drivers and feedbacks of global greening. Nat Rev Earth Environ 1, 14–27. https://doi.org/10.1038/s43017-019-0001-x
  19. Rukabie, J. S., Hassan, A. S., & Kadhum, J. H., September (2023). Evaluation of carbon dioxide emissions dispersion from crude oil production of Garraf oil field in Iraq.). AIP Conf. Proc. 2839, 080014. Vol. 2839(1), https://doi.org/10.1063/5.0170102
  20. Wande Gao, Ce Zheng, Xiuhua Liu, Yudong Lu, Yunfei Chen, Yan Wei, Yandong Ma, (2022) NDVI-based vegetation dynamics and their responses to climate change and human activities from 1982 to 2020: A case study in the Mu Us Sandy Land, China, Ecological Indicators, Volume 137, , 108745, https://doi.org/10.1016/j.ecolind.2022.108745 .