Integrating Satellite-Derived Vegetation Indices and Field Observations for Monitoring Seasonal Wetland Changes

The wetlands in monsoon environments experience rapid changes in water cover, aquatic plants, and bare substrate, although systematic monitoring programs fail to record such events on a management scale. In this study, the combination of vegetation and water indices derived from Sentinel-2 images was linked with repeated field observations in order to analyze the intra- and
inter-annual variability of the Vedanthangal tank wetland in a monsoon-driven environment in India. The monthly timeseries of the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil-Adjusted Vegetation Index (SAVI), and Modified Normalized Difference Water Index (MNDWI) were constructed using 76 satellite images without clouds, together with field sampling conducted 12 times throughout the year and involving 24 fixed plots that collected data on vegetation cover, height of macrophytes, leaf chlorophyll, and water depth. Wetland condition showed a clear annual pattern that was regulated by the northeast monsoon: maximum water cover occurred in December and January, while the development of floating and emergent vegetation took place in the post-monsoon drawdown period. The MNDWI index captured field water depths well, while NDVI, SAVI, and EVI largely accounted for variability in vegetation cover. The NDVI index alone was affected by the presence of water under the plant canopy cover as well as saturation in thick floating vegetation cover; the combination of NDVI with MNDWI gave more accurate vegetation maps. The dry 2022-23 hydrological year caused delayed filling and shortened the inundation period by one month, resulting in a delay in the vegetation peak. The combination of multiple indices from time series of satellite images and a limited number of field measurements provides a reliable framework for monitoring changes in wetlands.