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<p>Lake Urmia, once one of Iran’s largest inland water bodies, has severely dried up, creating major sources of salt and dust storms that threaten environmental stability, public health, and regional demographics. This study utilizes a cloud-based Google Earth Engine (GEE) platform to analyze remote sensing big data, defined here as the long-term, multi-sensor processing of thousands of satellite observations at pixel scale using a cloud-based environment, to investigate spatiotemporal environmental degradation associated with hydrological changes in the Lake Urmia basin from 2000 to 2024. Demographic trends in population change were examined to provide contextual insight into regional pressures rather than to imply direct causation. We processed 6500 MODIS and Landsat (TM/ETM+/OLI) images to extract Aerosol Optical Depth (AOD), the Normalized Difference Vegetation Index (NDVI), and the Normalized Difference Water Index (NDWI). Pixel-wise Linear Fit Regression (LFR) was then applied to MODIS- and Landsat-derived indices to quantify long-term trends, with validation using observations from seven regional meteorological stations. Monthly GRACE satellite data (2002–2024) were also used to assess changes in total terrestrial water storage (TWS) using Equivalent Water Height (EWH) anomalies. Results revealed five persistent hotspots of salt and dust emissions concentrated along the eastern and northeastern lake margins. AOD exhibited an overall increase of approximately 55%, lake surface area declined by more than 2700&#xa0;km², and vegetation cover decreased by nearly 50%, with associated uncertainty reflected in validation metrics (<i>r</i> &gt; 0.71 for AOD-dust events, R² ≈ 0.66 for NDVI comparisons, and 87% accuracy for NDWI-based shoreline detection). Population trends showed spatially heterogeneous patterns, including declines in cities such as Tabriz and relative growth in Urmia and Osku, concurrent with observed environmental degradation. While these patterns suggest a strong association between hydrological-environmental stressors and demographic redistribution, they should be interpreted as correlational rather than evidence of direct causality. Overall, this integrated hydrological, atmospheric, and demographic assessment highlights the need for sustainable water management and ecosystem restoration strategies to mitigate further environmental degradation and potential human displacement, in line with global Disaster Risk Reduction frameworks.</p>

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Spatiotemporal analysis of hydrological and environmental changes in lake Urmia (2000–2024) using google earth engine

  • 期刊论文

  • 发表日期：

    2026年3月17日

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  • Huxiong Li,
  • Vahid Isazade,
  • Saied Pirasteh,
  • Ahmed Serwa,
  • Zeinab Zaheri Abdehvand,
  • Davoud Rezaei,
  • Esmail Isazade,
  • Zhaoxi Fang,
  • Mahdieh Shirmohammadi

摘要

Lake Urmia, once one of Iran’s largest inland water bodies, has severely dried up, creating major sources of salt and dust storms that threaten environmental stability, public health, and regional demographics. This study utilizes a cloud-based Google Earth Engine (GEE) platform to analyze remote sensing big data, defined here as the long-term, multi-sensor processing of thousands of satellite observations at pixel scale using a cloud-based environment, to investigate spatiotemporal environmental degradation associated with hydrological changes in the Lake Urmia basin from 2000 to 2024. Demographic trends in population change were examined to provide contextual insight into regional pressures rather than to imply direct causation. We processed 6500 MODIS and Landsat (TM/ETM+/OLI) images to extract Aerosol Optical Depth (AOD), the Normalized Difference Vegetation Index (NDVI), and the Normalized Difference Water Index (NDWI). Pixel-wise Linear Fit Regression (LFR) was then applied to MODIS- and Landsat-derived indices to quantify long-term trends, with validation using observations from seven regional meteorological stations. Monthly GRACE satellite data (2002–2024) were also used to assess changes in total terrestrial water storage (TWS) using Equivalent Water Height (EWH) anomalies. Results revealed five persistent hotspots of salt and dust emissions concentrated along the eastern and northeastern lake margins. AOD exhibited an overall increase of approximately 55%, lake surface area declined by more than 2700 km², and vegetation cover decreased by nearly 50%, with associated uncertainty reflected in validation metrics (r > 0.71 for AOD-dust events, R² ≈ 0.66 for NDVI comparisons, and 87% accuracy for NDWI-based shoreline detection). Population trends showed spatially heterogeneous patterns, including declines in cities such as Tabriz and relative growth in Urmia and Osku, concurrent with observed environmental degradation. While these patterns suggest a strong association between hydrological-environmental stressors and demographic redistribution, they should be interpreted as correlational rather than evidence of direct causality. Overall, this integrated hydrological, atmospheric, and demographic assessment highlights the need for sustainable water management and ecosystem restoration strategies to mitigate further environmental degradation and potential human displacement, in line with global Disaster Risk Reduction frameworks.