Elucidating the phenology of the Sundarbans mangrove forest using 18-year time series of MODIS vegetation indices

Abstract

Mangrove forests are the most carbon-rich ecosystems in the world however, baseline information on its phenology is poor. Information on seasonal changes in canopy greenness, which reflects the level of photosynthetic activity, is helpful for understanding seasonal patterns of carbon uptake by mangrove forests. To elucidate the periodicity, timing, and length of the active photosynthetic season, we examined temporal patterns in enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) derived from 18-year (2001 2018) Moderate Resolution Imaging Spectroradiometer images for four major forest types in the Sundarbans, Bangladesh. We identified a dominant cycle for the time-series of EVI and NDVI after Fourier transformation. We also estimated four phenological dates among the forest types: the start of the season (SOS), time of maximum greenness (MaxGreen), end of the season (EOS), and length of the season (LOS). Fourier analysis revealed that both the NDVI and EVI exhibited distinct cycles per year for all forest types, suggesting that there are annual cycles of canopy greenness. The SOS as estimated using the EVI and NDVI was consistently from late May to mid-June across forest types. However, the MaxGreen, EOS and LOS estimated varied between the two indices. Because EVI-based phenological dates match better with phenological information at the ground level than do NDVI-based dates, the EVI would be better than the NDVI for depicting changes in canopy greenness. The results of this study provide baseline information for future phenological changes in the Sundarbans.

Rainfall Variability and Tidal Inundation Influences on Mangrove Greenness in Karimunjawa National Park, Indonesia

“…We used three years of time-series data of Sentinel-2 images (2019-2021) to analyze the mangrove greenness phenology in KNP. The study by Songsom et al [25] and Mandal et al [28] used time-series data of vegetation index from MODIS for 10-18 years to analyze the phenology of mangrove forests. This data may determine the phenology well because of the long time-series data.…”

“…Vegetation greenness phenology depicts the annual timing cycle of vegetation growth, such as leaf emergence, greenness, and senescence, driven by environmental and climate dynamics [25,27]. By knowing the green cycle of mangroves, we can determine when mangroves optimally absorb carbon in the atmosphere because of the impact of canopy capacity on photosynthesis [28,29].…”