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<p>Wetlands are critical ecosystems that provide essential ecological and socio-economic services; however, anthropogenic activities and climate change increasingly threaten them. This study investigates the spatio-temporal dynamics of hydrology and vegetation in Son Beel, Asia’s second-largest seasonal freshwater wetland, using remote sensing data. Sentinel-1 and 2, Landsat imagery, and the continuous change detection and classification (CCDC) algorithm were employed to monitor seasonal and inter-annual variations in water extent and vegetation dynamics. The study includes hydroperiod analysis, assessment of open water and submerged vegetation dynamics, application of CCDC, and land use/land cover (LULC) classification. Hydroperiod analysis of Son Beel using Sentinel-1 (2015–2024) showed significant variability in water presence. The perennial water areas were 0.66&#xa0;km² in 2015 and 0.33&#xa0;km² in 2024. The fluctuations in these areas are attributed to changes in hydrology and the expansion of aquaculture ponds at the wetland’s periphery. From 2015 to 2024, open water and submerged vegetation fluctuated seasonally, with open water peaking in January 2018 (15.29&#xa0;km²) before declining, while submerged vegetation decreased until 2020 and then stabilized. NDVI analysis derived from the CCDC algorithm revealed sparse vegetation in earlier years, with recovery and increased growth after 2019. The random forest algorithm was used for LULC classification, achieving 89% accuracy for the wet and 92% for the dry seasons, demonstrating its effectiveness in capturing seasonal dynamics. This study highlights the importance of continuous wetland monitoring and demonstrates the critical role of remote sensing in ensuring the sustainable management and conservation of Son Beel.</p>

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Unveiling the Spatio-Temporal Dynamics of Son Beel: A Freshwater Wetland from Indian East Sub-Himalaya

  • 期刊论文

  • 发表日期：

    2025年4月17日

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  • Ganithi Sandhya,
  • Subrata Nandy,
  • Hitendra Padalia,
  • Anisha Dey,
  • Arun Jyoti Nath,
  • Koushik Majumdar,
  • Ashesh Kumar Das

摘要

Wetlands are critical ecosystems that provide essential ecological and socio-economic services; however, anthropogenic activities and climate change increasingly threaten them. This study investigates the spatio-temporal dynamics of hydrology and vegetation in Son Beel, Asia’s second-largest seasonal freshwater wetland, using remote sensing data. Sentinel-1 and 2, Landsat imagery, and the continuous change detection and classification (CCDC) algorithm were employed to monitor seasonal and inter-annual variations in water extent and vegetation dynamics. The study includes hydroperiod analysis, assessment of open water and submerged vegetation dynamics, application of CCDC, and land use/land cover (LULC) classification. Hydroperiod analysis of Son Beel using Sentinel-1 (2015–2024) showed significant variability in water presence. The perennial water areas were 0.66 km² in 2015 and 0.33 km² in 2024. The fluctuations in these areas are attributed to changes in hydrology and the expansion of aquaculture ponds at the wetland’s periphery. From 2015 to 2024, open water and submerged vegetation fluctuated seasonally, with open water peaking in January 2018 (15.29 km²) before declining, while submerged vegetation decreased until 2020 and then stabilized. NDVI analysis derived from the CCDC algorithm revealed sparse vegetation in earlier years, with recovery and increased growth after 2019. The random forest algorithm was used for LULC classification, achieving 89% accuracy for the wet and 92% for the dry seasons, demonstrating its effectiveness in capturing seasonal dynamics. This study highlights the importance of continuous wetland monitoring and demonstrates the critical role of remote sensing in ensuring the sustainable management and conservation of Son Beel.