Tracking Cyclonic Impact and Recovery Rate of Mangrove Forest using Remote Sensing: A Case Study of the Sundarbans, Bangladesh

Keywords: Mangrove Forests, Remote Sensing, Cyclones, Ecosystem Disturbance, Pixel-based Approach
Session Type: Virtual Paper
Day: Thursday
Session Start / End Time: 4/8/2021 03:05 PM (Pacific Time (US & Canada)) - 4/8/2021 04:20 PM (Pacific Time (US & Canada))
Room: Virtual 13

Abstract

The Sundarbans mangrove forest, one of the world’s largest of its kind situated at the southwest of Bangladesh (approximately 60%), plays a vital role in safeguarding the country from the wrath of tropical cyclones and other disaster events. It is known to act as a buffer to protect cyclonic wind's initial threat during any tropical cyclone towards Bangladesh. During SIDR (November 15, 2007), the second-largest cyclone in Bangladesh since 1877, it is estimated the Sundarbans lost 30% of its plant habitat while upwards of 15% of the forest sustained severe damage. To manage the natural resources of Sundarbans after disturbance, proper study regarding the impact and post-disturbance recovery of the forests is an immediate requirement. Most of the literature has focused on change in land cover types, which can help investigate the overall impact. However, the question of how long it takes these forests to recover is still relatively unexplored. We propose to use a pixel-based approach to address the following questions: (i) what was the extent and severity of the cyclone damage on the mangrove forest, and (ii) how long did it take the forest to return to its pre-disturbance condition. We plan to use a dense time series of vegetation indices from several remotely sensed platforms to estimate post-disturbance vegetation condition relative to its pre-disturbance condition. We will describe our proposed framework and plan to address the challenges of using remotely sensed data in this environment