A data-driven computational spatio-temporal analysis of rainfall and vegetation indices using satellite image processing

Layla A. AL.hak

doi:10.17977/um063.v6.i4.2026.4

Authors

Layla A. AL.hak University of Diyala

DOI:

https://doi.org/10.17977/um063.v6.i4.2026.4

Keywords:

NDVI, EVI, Image processing, Remote sensing, GIS

Abstract

Vegetation coverage is significantly influenced by rainfall. The analyses of vegetation influenced by meteorological factors contribute to research on the relationships between terrestrial ecosystems and climate changes. This study employs GIS and satellite image processing techniques to examine the relationship between the Normalized Difference of Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) as well as their relationship with rainfall in Diyala, using multi-temporal Teraa MODIS and TRMM satellite from 2001 to 2019. The results of spatial and temporal distribution show that the value of three indicators varies from year to year, also change from place to another in the Diyala governorate. The rainfall shows there is a match in behavior between the curve of rainfall with the curve of NDVI and the curve of the EVI index. The southwest and northeastern areas are characterized by high values of rainfall, NDVI and EVI. Finally, the regression technique is used to obtain the correlation between rainfall with NDVI EVI. It is concluded that the correlation between rainfall, NDVI and EVI regression coefficient is a good positive correlation.

References

Abdulkadhim, M. I., Qader, R. A., Ibrahim, S., & Ismael, H. (2025). Temporal analysis of remote sensing indices with MATLAB: Comparative study of 2016 vs. 2019 vegetation cover index in Abu Ghraib's irrigation project. MATLAB, 4(2), 52–78.

Adeeb, H. Q., & Al-Timimi, Y. K. (2020). GIS techniques for mapping of wind speed over Iraq. Iraqi Journal of Agricultural Sciences, 50(6), 1–9. https://doi.org/10.36103/ijas.v50i6.852

Al-hasn, R. (2024). Studying correlation between precipitation and NDVI/MODIS for time series (2012–2022) in arid region in Syria. E3S Web of Conferences, 58, Article 16704. https://doi.org/10.3390/ecrs2023-16704

Bakr, D. I., Al-Khalidi, J., & Abed, H. N. (2025). Estimation of climatological parameters using ANN and WEKA models in Diyala Governorate, Iraq. Journal of Agrometeorology, 27(2), 210–215. https://doi.org/10.54386/jam.v27i2.2877

Giri, C., Pengra, B., Long, J., & Loveland, T. R. (2013). Next generation of global land cover characterization, mapping, and monitoring. International Journal of Applied Earth Observation and Geoinformation, 25(1), 30–37. https://doi.org/-10.1016/j.jag.2013.03.005

Govedar, Z., & Anikić, N. (2024). Vegetation indices monitoring by using Copernicus data in the old-growth forests of the Republic of Srpska/Bosnia and Herzegovina. Frontiers in Forests and Global Change, 7, 1–9. https://doi.org/10.3389/ffgc.2024.1354769

Gunnula, W., Kosittrakun, M., Righetti, T. L., Weerathaworn, P., & Prabpan, M. (2011). Normalized difference vegetation index relationships with rainfall patterns and yield in small plantings of rain-fed sugarcane. Australian Journal of Crop Science, 5(13), 1852–1857.

Heinsch, F. A., Zhao, M., Running, S. W., Kimball, J. S., Nemani, R. R., Davis, K. J., Bolstad, P. V., Cook, B. D., Desai, A. R., Ricciuto, D. M., Law, B. E., Oechel, W. C., Kwon, H., Luo, H., Wofsy, S. C., Dunn, A. L., Munger, J. W., Baldocchi, D. D., Xu, L., … Flanagan, L. B. (2006). Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE Transactions on Geoscience and Remote Sensing, 44(7), 1908–1923. https://doi.org/-10.1109/TGRS.2005.853936

Huete, A. R., Liu, H. Q., Batchily, K., & Van Leeuwen, W. (1997). A comparison of vegetation indices over a global set of TM images for EOS-MODIS. Remote Sensing of Environment, 59(3), 440–451. https://doi.org/10.1016/S0034-4257(96)00112-5

Hussein, O. I. (2019). Impact of climate on human comfort in Diyala Governorate. Diyala Journal of Humanitarian Research, 1(3), 305–331.

Jamali, S., Seaquist, J. W., Ardö, J., & Eklundh, L. (2011). Investigating temporal relationships between rainfall, soil moisture and MODIS-derived NDVI and EVI for six sites in Africa. In 34th International Symposium on Remote Sensing of Environment – The GEOSS Era: Towards Operational Environmental Monitoring.

Jawad, T. K., Al-Taai, O. T., & Al-Timimi, Y. K. (2018). Evaluation of drought in Iraq using DSI by remote sensing. Iraqi Journal of Agricultural Sciences, 49(6), 1132–1145. https://doi.org/10.36103/ijas.v49i6.152

Justice, C. O., Vermote, E., Townshend, J. R. G., Defries, R., Roy, D. P., Hall, D. K., & Salomonson, V. V. (1998). The Moderate Resolution Imaging Spectroradiometer (MODIS): Land remote sensing for global change research. IEEE Transactions on Geoscience and Remote Sensing, 36(4), 1228–1249.

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. https://doi.org/10.37077/25200860.2024.38.1.25

Klein, J. A., Harte, J., & Zhao, X. Q. (2004). Experimental warming causes large and rapid species loss, dampened by simulated grazing, on the Tibetan Plateau. Ecology Letters, 7(12), 1170–1179. https://doi.org/10.1111/j.1461-0248.2004.00677.x

Leilei, L., Jianrong, F., & Yang, C. (2014). The relationship analysis of vegetation cover, rainfall and land surface temperature based on remote sensing in Tibet, China. IOP Conference Series: Earth and Environmental Science, 17(1), Article 012034. https://doi.org/10.1088/1755-1315/17/1/012034

Li, C. (2006). Review of studies in climate change over the Tibetan Plateau. Acta Geographica Sinica, 61(3), 327–335.

Liu, H. Q., & Huete, A. (1995). Feedback based modification of the NDVI to minimize canopy background and atmospheric noise. IEEE Transactions on Geoscience and Remote Sensing, 33(2), 457–465. https://doi.org/10.1109/36.377946

Muter, S. A., Al-Jiboori, M. H., & Al-Timimi, Y. K. (2025). Assessment of the correlation between rainfall and Normalized Difference Vegetation Index (NDVI) over Iraq. Italian Journal of Agrometeorology. https://doi.org/10.36253/ijam-3069

Pashaei, M., Rashki, A., & Sepehr, A. (2017). An integrated desertification vulnerability index for Khorasan-Razavi, Iran. Natural Resources and Conservation, 5(3), 44–55. https://doi.org/10.13189/nrc.2017.050302

Ren, R., Wu, G., & Cai, M. (2000). Sensitivity to seasonal and interannual rainfall variations in Northern China. Acta Geographica Sinica, 55.

Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1973). Monitoring vegetation systems in the great plains with ERTS. In Third Earth Resources Technology Satellite (ERTS) Symposium (Vol. 1, pp. 309–317).

Udelhoven, T., Stellmes, M., & Röder, A. (2015). Assessing drivers of vegetation changes in drylands from time series of earth observation data. In Remote Sensing and Digital Image Processing (Vol. 22). https://doi.org/10.1007/978-3-319-15967-6

Wang, J., Rich, P. M., & Price, K. P. (2003). Temporal responses of NDVI to precipitation and temperature in the central Great Plains, USA. International Journal of Remote Sensing, 24(11), 2345–2364. https://doi.org/10.1080/-01431160210154812

Yao, T., Liu, X., Wang, N., & Shi, Y. (2000). Amplitude of climatic changes in Qinghai-Tibetan Plateau. Chinese Science Bulletin, 45(13), 1236–1243. https://doi.org/10.1007/BF02886087