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Assessing Ecosystem Damage and Recovery using Object-Based Image Analysis (OBIA) in a Low-lying Coastal Region of Bangladesh

Authors: Md Ashraful Islam*, School of Science, University of New South Wales (UNSW), Canberra, Australia, David James Paull, School of Science, University of New South Wales (UNSW), Canberra, Australia, Amy Louise Griffin , School of Science, RMIT University, Melbourne, Australia, Sanzida Murshed, School of Science, University of New South Wales (UNSW), Canberra, Australia
Topics: Environment, Coastal and Marine, Remote Sensing
Keywords: Coastal ecosystems, OBIA, geospatial technique, coastal planning, Tropical Cyclone Sidr, Southwestern Bangladesh
Session Type: Poster
Presentation File: No File Uploaded


Coastal ecosystems deliver a broad range of tangible and intangible benefits for human well-being that are substantial and cost‐efficient. But these low-lying ecosystems can be severely perturbed by tropical cyclones. This research aimed to examine damage and subsequent recovery due to a tropcial cyclone in the southwestern coast of Bangladesh using geospatial techniques. The Kalapara Upazila in the Patuakhali district was severely affected by Cyclone Sidr in 2007 and was chosen as a case study. We applied Object-Based Image Analysis (OBIA) on 10 m resolution multispectral optical imagery for landcover mapping at four time-points associated with the cyclone, namely pre-cyclone, immediately post-cyclone, short-term recovery and long-term recovery. Using a unique ruleset, the OBIA yielded five distinct land cover types representing cropland, mangrove forest, riparian forest, tidal flat, and sandy beach ecosystems for the study area. Change detection revealed a substantial change in ecosystems due to the widespread destruction brought by cyclonic storm surge and wind. Significant recovery (both short-term and long-term) was observed in the affected ecosystems, particularly cropland and mangrove forest, albeit at somewhat different rates. The riparian forest and sandy beach ecosystems experienced comparatively slower recovery. By quantifying ecosystem behavior against an external stressor at different temporal phases of a major disaster, this empirical analysis offers benefits to those who plan for the development of sustainable livelihoods and build effective ecosystem-based resilience within vulnerable coastal communities

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