Bangladesh has been dealing with one of the world's largest refugee emergencies along its border with Myanmar (especially in the rough wooded zone of Ukhiya sub-district, Cox's Bazar) due to a massive influx of Rohingya refugees, particularly since 25 August 2017. Resulting high impacts threaten the viability of local plantation as well as natural forests (societal and ecological assets). This research aims to evaluate the impact of the influx on the physical landscape in the Ukhiya sub-district as well as changes of socio-cultural landscape. The study was relied on both geo-spatial and survey data analysis. We argue that Rohingya flooding has a significant impact on changes of physical and socio-cultural landscape of the area in and around Rohingya camps. Results from the normalized difference vegetation index analysis identified that during 2015-2018 the forestry adjacent to the Kutupalong camps (Ukhiya sub-district) declined by 11.23 km 2 . Forestry cover fell from approximately 68.9% of all land to 2.72%; the decline representing about 15.2% of the entire forested area. Furthermore, the highest elevated area of Kutupalong camps (estimated to be 41 m) is likewise affected by anthropogenic activities, for instance, wholesale cutting into the slope, and street and stair construction which is gradually rising the potentiality of landslide and inland flood in several camps. Out of which 27.76% settlements, 0.35% and 9.61% settlements are at risk of landslide and flood, respectively, in the Kutupalong RC and Kutupalong extension campsite. A large proportion of Rohingyas also used wood for fuel; wood used originates from the adjacent forest and is the primary explanation for forestry consumption in Ukhiya sub-district. Its forests and elevation will never return to their original condition if the consumption of forestry assets proceeds unabated. It is argued, that these research findings may inspire locals, national, and global aid agencies to contribute to the introduction of forestry management and environmental protection.

<p>The coastal region is confronted with increasing risk due to multiple factors such as climate change, urbanization, and the concentration of infrastructure. Under climate change, coastal hazards such as hurricanes and floods are expected to increase in intensity and frequency. This project first presents a conceptual framework of assessing coastal resilience by linking hazards, social vulnerability, and risk decision making in the coastal setting. It then presents two studies conducted in two coastal cities from the United States to illustrate this framework. Houston in Texas is selected as the location for the first study. Houston has experienced a few devastating floods in recent history. It is thus imperative to assess flood risk in this city through a comprehensive approach by considering both flood susceptibility and social vulnerability. This study first assesses flood susceptibility by applying Random Forest (RF) algorithm on remotely sensed data. It then combines flood susceptibility with social vulnerability to generate a comprehensive assessment of flood risk in Houston. New Orleans in Louisiana is selected as the location for the second study. This study first proposes a framework to study urban disaster resilience by closing the gap between municipal hazard mitigation plans and residents’ risk perceptions. Through survey research and policy analysis, this study identifies a gap between the municipal approach to climate change mitigation and the concern and expectation of actions the residents hold regarding the future effects of climate change. The study ends with recommending municipal hazard mitigation plans to reconsider risks of climate change and providing small-scale incentives to coastal residents in order to maximize resilience toward coastal hazards in the future.</p>

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Floods are a frequently occurring calamity in deltaic Bangladesh. This paper aims to assess the temporal expansion of waterbodies during flooding using geospatial techniques. Several water indices were applied to classify the satellite images at various temporal scales. Among them, the Normalized Difference Water Index (NDWI) showed the highest correlation (r = 0.831; where p = 0.01) with rainfall data. Specifically, the NDWI results showed that perennial waterbodies measured 37 km 2 and 60 km 2 in Sunamganj District in 2017 and 2019, respectively. The area of waterbodies notably increased 52-fold from March to April (37 km 2 to 1958 km 2 ) during the premonsoon flash flood of 2017. During the July 2019 monsoon flood, waterbodies started to extend after May and flooded 2784 km 2 in area. NDVI analysis showed that in 2019, floodwater submerged 361.7 km 2 of vegetation cover. At the same time, the Surma River's flooding resulted in a 73.9 per cent inundation of the total area of the Sunamganj District. We hope that this study will provide better understanding of the varying nature of floods that occur in the low lying bowl shaped Haor region which will in turn assist the government with flood mitigation.