Abstract
Desertification is one of the major challenges in arid and semi-arid regions of the world, which has a profound impact on ecological sustainability, agriculture, and the livelihoods of communities. This study aimed to analyze early warning signals of desertification risk in northeastern Iran. For this purpose, the MEDALUS model was used along with field data, remotely sensed indices NDVI, NDSI, TGSI, WEHI, and groundwater depth index during the period 2002 to 2021. Landsat images with geometric and atmospheric corrections, along with data from meteorological stations and water wells, were used for the calculations. Breakpoint analysis of the time series was performed using the BFAST package, and statistical indicators (lag-1 autocorrelation, skewness, and standard deviation) were evaluated in R software. The results of the MEDALUS model indicated that 36% of the region falls into the severe to very severe desertification class, and that “quality of management and policy” and “erosion” make the largest contributions to this trend. The main breaking point occurred in 2015, which was accompanied by a sharp decline in vegetation cover, a drop in groundwater levels, and an increase in soil salinity. Spatial analysis revealed that the northeastern, southeastern, and central parts of the study area represent the main desertification hotspots, characterized by significant changes in vegetation cover, soil properties, wind erosion, and groundwater depletion. The results showed that NDVI and NDSI indices, along with lag-1 autocorrelation, are most effective in the early detection of ecosystem changes. The findings demonstrate the importance of combining remote sensing indicators with statistical methods in developing early warning systems and sustainable natural resource management to control desertification.
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Boali, A., Asgari, H.R., Behbahani, A.M. et al. Analysis of early warning signals of desertification hazard using time series of remotely sensed indicators in northeastern Iran. Earth Sci Inform 19, 230 (2026). https://doi.org/10.1007/s12145-026-02284-7
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DOI: https://doi.org/10.1007/s12145-026-02284-7