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@ARTICLE{2026EScIn..19...41L,
       author = {{Li}, Huxiong and {Isazade}, Vahid and {Pirasteh}, Saied and {Serwa}, Ahmed and {Abdehvand}, Zeinab Zaheri and {Rezaei}, Davoud and {Isazade}, Esmail and {Fang}, Zhaoxi and {Shirmohammadi}, Mahdieh},
        title = "{Spatiotemporal analysis of hydrological and environmental changes in lake Urmia (2000─2024) using google earth engine}",
      journal = {Earth Science Informatics},
     keywords = {Aerosol optical depth (AOD), Remote sensing, Google earth engine (GEE), Environmental migration, Salt dust emission hotspots, Lake urmia, Environmental Sciences, Environmental Science and Management, Engineering, Environmental Engineering, Earth Sciences, Physical Geography and Environmental Geoscience},
         year = 2026,
        month = mar,
       volume = {19},
       number = {4},
          eid = {41},
        pages = {41},
     abstract = "{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
        km{\texttwosuperior}, and vegetation cover decreased by nearly
        50\%, with associated uncertainty reflected in validation
        metrics (r > 0.71 for AOD-dust events, R{\texttwosuperior} ≍
        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.}",
          doi = {10.1007/s12145-026-02089-8},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2026EScIn..19...41L},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}