Assessment of Vulnerability of Mangrove Ecosystems of Indian Sundarban Region using Remote Sensing Derived Time Series Variables and Analytical Hierarchy process

Vulnerability assessment of ecosystem bestows an idea about the ecosystem health and its ability to resist environmental stress. Indian Sundarban region situated at the south-west part of Gangga-Brahmaputra-Meghna delta has been under constant threat of frequent climate hazards and long-term climate change. Various attempts have been made for vulnerability assessment of this mangrove ecosystem focusing only on static non-temporal variables. The present work hypothesises that mangrove ecosystems are highly adaptive and respond to the changing environment by various natural resilience strategies at the ecosystem level. So, a better understanding of the dynamics of mangrove ecosystem will provide an idea about the state of vulnerability for this ecosystem.

In the present study, a novel approach for assessing vulnerability of the mangrove ecosystem of Indian Sundarban region was used. For vulnerability assessment, Remote Sensing based Enhanced Vegetation Index (EVI) for 20-year time series was used from Landsat Archive in Google Earth Engine. All the other Remote Sensing derived variables (e.g., Land-surface temperature, Precipitation, Cyclone Intensity Change, Mean Sea Level Change) were taken at a temporal scale. The anthropogenic stress on the ecosystem was interpreted from the calculated socio-economic vulnerability index, which acts as a proxy for human dependence on the ecosystem. The relative influence of each of the variables on the overall vulnerability of the ecosystem was calculated using Analytical Hierarchy Process (AHP). The results revealed that the present approach can detect vulnerability of the mangrove ecosystem and identify the key vulnerable areas in the landscape. The present approach adapted in this study can be implemented in other similar ecosystems with some modifications in the local influencing factors.