Integrated Structural and Physiological Dynamics of Tropical MangrovesUsing Sentinel-2 Time Series: A Decadal Assessment in the IndianSundarbans (2016–2025)

Tropical mangrove monitoring is essential for understanding ecosystem responses to climate
change and supporting conservation. Sentinel-2 time series enable long-term observation;
however, tidal inundation and mixed spectral responses complicate the discrimination of
mangroves from mudflats and water. Additionally, evergreen canopies can mask physiological stress despite changes in chlorophyll content, limiting the comprehensive assessment of both structural and physiological mangrove conditions.

Previous research in the Sundarbans has generally assessed structural and physiological dynamics separately. Therefore, to address this research gap, this study proposes and develops an integrated geospatial framework which utilizes  Combined Mangrove Recognition Index (CMRI; combining the Normalized Difference Vegetation Index [NDVI] and Normalized Difference Water Index (NDWI_Gao)) to reduce tidal background effects and mixed spectral responses and to characterize structural dynamics, alongside the Normalized Difference Chlorophyll Index (NDCI; a red-edge chlorophyll index) to capture chlorophyll-related physiological activity masked by evergreen canopies.

A total of 786 Sentinel-2 images acquired between 2016 and 2025 were processed for consistent temporal analysis in Sundarbans National Park under monsoon-driven hydro-climatic variability and recurring tropical cyclones.
The analysis revealed distinct seasonal and interannual structural and physiological dynamics, with mangrove conditions improving during the monsoon and declining during winter. The period from 2016–2018 showed moderate seasonal variability, followed by peak structural and physiological variability during 2019–2021, which coincided with Cyclones Bulbul (2019), Amphan (2020), and Yaas (2021). From 2022 onwards, both indicators stabilised, suggesting ecosystem recovery. Percentile-based analyses confirmed that these temporal patterns represented persistent ecosystem responses rather than isolated extreme observations, supporting the robustness of the time-series framework.

This framework enables the assessment of structural and physiological dynamics, supporting the long-term assessment of climate-sensitive tropical mangroves and providing a reproducible basis for conservation, restoration planning, and climate adaptation. Future work will integrate Sentinel-1 Synthetic Aperture Radar (SAR) and Artificial Intelligence (AI)-based classification to improve transferability and operational scalability.
Keywords: Sentinel-2; CMRI; NDCI; Sundarbans; mangroves; cyclone disturbance; structural–physiological dynamics