Time series analysis of vegetation index and land degradation assessment in Dhi Qar governorate (Iraq)
DOI:
https://doi.org/10.31272/jeasd.2864Keywords:
Iraq-Dhi Qar, Land degradation, Spatiotemporal analysis, Time seriesAbstract
Land degradation is a complex problem involving many factors, and it is a change in the land over time. The loss of vegetation cover or a decrease in productivity is one of the indicators of land degradation. This research analyzes vegetation health and density measures using time series analysis of the Normalized Difference Vegetation Index (NDVI) extracted from Landsat 8 satellite data. The study employs the Mann-Kendall (MK) test and Simple Linear Regression (SLR) to identify trends. Additionally, the Bayesian Estimator of Abrupt Change, Seasonality, and Trend model (BEAST) was used for its advantages in trend analysis and change point detection in the study area of Dhi Qar, Iraq. The analysis indicates a decline in the NDVI trend. However, the BEAST method showed its distinction in revealing the details of the trend analysis and change points. In 2022, NDVI declined sharply, with vegetation cover loss estimated at 47% compared to 2014. Maps showing spatial distribution between 2014 and 2023 highlighted this change, which was linked to alterations in rainfall patterns. Therefore, we conclude that meteorological drought strongly affects the vegetation cover in the study area, and repeated drought leads to the loss of vegetation cover and, consequently, to land degradation.
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Copyright (c) 2025 Mohammed H Azeez (Author); Hisham M. Jawad Al Sharaa, Abdul Razzak T. Ziboon
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