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<p>Coastal lagoons and shallow lake systems are among the most productive aquatic environments worldwide but are increasingly threatened by hydrological alterations, sedimentation, and vegetation-driven ecological change. Chilika Lake, the largest brackish lagoon in Asia, has experienced substantial changes in surface-water extent and vegetation distribution over recent years. This study investigates whether these spatial–temporal patterns are consistent with broader eco-hydrological interactions described for shallow coastal lagoons. Water-vegetation dynamics during 2019, 2021, 2023, and 2025 were quantified using Sentinel-2-derived NDWI and NDVI, multi-season image differencing, a five-class vegetation encroachment framework, Getis-Ord Gi* hotspot analysis, kernel density estimation, and deep-water spectral validation. Results reveal persistent contraction of classified open-water areas (NDWI ≥ 0.05), with wet-season losses exceeding 86&#xa0;km<sup>2</sup> between 2019 and 2025 and continued dry-season decline. Vegetation dynamics exhibited a pulse-like trajectory, with substantial expansion between 2019 and 2021 followed by partial contraction during 2023 and 2025, while large portions of the lagoon remained under moderate and strong vegetation encroachment. Strong inverse relationships between ΔNDWI and ΔNDVI (r = −0.93 to −0.98) indicate consistent spatial associations between surface-water contraction and vegetation dynamics. Stable NDWI responses in deep-water reference areas indicate that the detected changes are unlikely to result from sensor bias or atmospheric effects, whereas hotspot and kernel density analyses demonstrate persistent, non-random spatial organization of vegetation transitions. These patterns are broadly consistent with conceptual eco-hydrological and eco-morphodynamic frameworks described for shallow coastal lagoons, although the underlying mechanisms were not directly evaluated. Overall, this study demonstrates that multi-season satellite observations provide a robust, scalable framework for monitoring hydrological and ecological change and supporting evidence-based management of data-limited coastal lagoons while contributing to Sustainable Development Goals 6 and 14.</p>

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Multi-season satellite analysis of surface water and vegetation dynamics in Chilika Lake from 2019 to 2025

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月16日

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  • Majd Mre,
  • Bidyadhar Basa,
  • Rabindro Nath Samal

摘要

Coastal lagoons and shallow lake systems are among the most productive aquatic environments worldwide but are increasingly threatened by hydrological alterations, sedimentation, and vegetation-driven ecological change. Chilika Lake, the largest brackish lagoon in Asia, has experienced substantial changes in surface-water extent and vegetation distribution over recent years. This study investigates whether these spatial–temporal patterns are consistent with broader eco-hydrological interactions described for shallow coastal lagoons. Water-vegetation dynamics during 2019, 2021, 2023, and 2025 were quantified using Sentinel-2-derived NDWI and NDVI, multi-season image differencing, a five-class vegetation encroachment framework, Getis-Ord Gi* hotspot analysis, kernel density estimation, and deep-water spectral validation. Results reveal persistent contraction of classified open-water areas (NDWI ≥ 0.05), with wet-season losses exceeding 86 km2 between 2019 and 2025 and continued dry-season decline. Vegetation dynamics exhibited a pulse-like trajectory, with substantial expansion between 2019 and 2021 followed by partial contraction during 2023 and 2025, while large portions of the lagoon remained under moderate and strong vegetation encroachment. Strong inverse relationships between ΔNDWI and ΔNDVI (r = −0.93 to −0.98) indicate consistent spatial associations between surface-water contraction and vegetation dynamics. Stable NDWI responses in deep-water reference areas indicate that the detected changes are unlikely to result from sensor bias or atmospheric effects, whereas hotspot and kernel density analyses demonstrate persistent, non-random spatial organization of vegetation transitions. These patterns are broadly consistent with conceptual eco-hydrological and eco-morphodynamic frameworks described for shallow coastal lagoons, although the underlying mechanisms were not directly evaluated. Overall, this study demonstrates that multi-season satellite observations provide a robust, scalable framework for monitoring hydrological and ecological change and supporting evidence-based management of data-limited coastal lagoons while contributing to Sustainable Development Goals 6 and 14.