Evaluating geomorphological changes and coastal flood vulnerability of the Nijhum Dwip Island using remote sensing techniques

Hasan, Md Asif; Mayeesha, Anika Nawar; Razzak, Md Zayed Abdur

doi:10.1016/j.rsase.2023.101028

Cited by 6 publications

(5 citation statements)

References 67 publications

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“…They cause losses of lives and damage to infrastructure [63], as well as fragmentation and disruption in natural landscapes [64] and increased salinity due to the intrusion of oceanic water during storms. Moreover, floods affect crop agriculture [65,66] and negatively influence the sustainability of coastal ecosystems [67][68][69]. Millions of people living in southern Bangladesh and neighbouring regions of India are vulnerable to such hazards due to exposure, high susceptibility and low resilience to repetitive floods [70,71].…”

Section: Problem Formulationmentioning

confidence: 99%

Deep Learning Methods of Satellite Image Processing for Monitoring of Flood Dynamics in the Ganges Delta, Bangladesh

Lemenkova

2024

Water

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Mapping spatial data is essential for the monitoring of flooded areas, prognosis of hazards and prevention of flood risks. The Ganges River Delta, Bangladesh, is the world’s largest river delta and is prone to floods that impact social–natural systems through losses of lives and damage to infrastructure and landscapes. Millions of people living in this region are vulnerable to repetitive floods due to exposure, high susceptibility and low resilience. Cumulative effects of the monsoon climate, repetitive rainfall, tropical cyclones and the hydrogeologic setting of the Ganges River Delta increase probability of floods. While engineering methods of flood mitigation include practical solutions (technical construction of dams, bridges and hydraulic drains), regulation of traffic and land planning support systems, geoinformation methods rely on the modelling of remote sensing (RS) data to evaluate the dynamics of flood hazards. Geoinformation is indispensable for mapping catchments of flooded areas and visualization of affected regions in real-time flood monitoring, in addition to implementing and developing emergency plans and vulnerability assessment through warning systems supported by RS data. In this regard, this study used RS data to monitor the southern segment of the Ganges River Delta. Multispectral Landsat 8-9 OLI/TIRS satellite images were evaluated in flood (March) and post-flood (November) periods for analysis of flood extent and landscape changes. Deep Learning (DL) algorithms of GRASS GIS and modules of qualitative and quantitative analysis were used as advanced methods of satellite image processing. The results constitute a series of maps based on the classified images for the monitoring of floods in the Ganges River Delta.

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Section: Problem Formulationmentioning

confidence: 99%

Deep Learning Methods of Satellite Image Processing for Monitoring of Flood Dynamics in the Ganges Delta, Bangladesh

Lemenkova

2024

Water

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“…In this research, in addition to examining the annual images, the images before and after the ood of March 2019 were also evaluated in order to investigate the direct effect of the ood. The speci cations and time of taking the images used can be seen in Table (3). Extraction of the river border…”

Section: Investigation Of River Ow Changesmentioning

confidence: 99%

“…It should be mentioned that there are rocky walls in the Bazoft River so that in some areas of the river, access is only possible to one of the right or left banks. Three areas with rocky walls were identi ed in the studied area, and the error rate was obtained by comparing the extraction boundary in different years and the reference boundary, the results of which are presented in Table (3). As can be seen, the average absolute error is 1.1 meters, of course, it should be kept in mind that in the investigation of changes in morphological parameters, the river border is measured in two consecutive years relative to each other, which in this case.…”

Section: Validationmentioning

confidence: 99%

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Investigating the Effect of Flood Flows on Morphological Changes Using a Series of Satellite Images: Rapid Changes in Morphology of Bazoft River

Koohizadeh Dehkordi,

Fatahi Nafchi,

Samadi-Boroujeni

et al. 2024

SSRN Journal

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“…Understanding the social risk of flooding, particularly in coastal areas, is challenging because of the high complexity and multi-lateral interaction within physical geographic and socio-economic elements (Brondizio et al 2016, Edmonds et al 2020. Multiple research experiences have reported more significant flood risks on islands due to higher population densities, relatively more isolated geographical locations, stronger interaction with oceanic activity, and relatively simpler social constitution, etc (Farid et al 2023, Hasan et al 2023, Rivosecchi and Singh 2023, Roy et al 2023. These findings relate the flood risk in islands not only to the natural factors but also to the social aspects.…”

Section: Introductionmentioning

confidence: 99%

Assessing the social risks of flooding for coastal societies: a case study for Prince Edward Island, Canada

Pang,

Shah,

Dau

et al. 2024

Environ. Res. Commun.

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With the worldwide growing threat of flooding, assessing flood risks for human societies and the associated social vulnerability has become a necessary but challenging task. Earlier research indicates that islands usually face heightened flood risks due to higher population density, isolation, and oceanic activities, while there is an existing lack of experience in assessing the island-focused flood risk under complex interactions between geography and socioeconomics. In this context, our study employs high-resolution flood hazard data and the principal component analysis (PCA) method to comprehensively assess the social risk of flood exposure and social vulnerability in Prince Edward Island (PEI), Canada, where limited research has been delivered on flood risk assessments. The findings reveal that exposed populations are closely related to the distribution of flood areas, with increasingly severe impact from current to future climate conditions, especially on the island’s north shore. Exposed buildings exhibit a concentrated distribution at different levels of community centers, with climate change projected to significantly worsen building exposure compared to population, possibly due to the urban agglomeration effect. The most populated cities and towns show the highest social vulnerabilities in PEI, and the results reflect a relatively less complex economic structure of islands. Recommendations for research and management in the coming stage include the necessity of particular climate actions, recognizing community centers as critical sites for flood hazard responses, and incorporating flood hazards into urban planning and management to mitigate the impacts of continuous urbanization on ecosystem services for flood prevention.

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Evaluating geomorphological changes and coastal flood vulnerability of the Nijhum Dwip Island using remote sensing techniques

Cited by 6 publications

References 67 publications

Deep Learning Methods of Satellite Image Processing for Monitoring of Flood Dynamics in the Ganges Delta, Bangladesh

Deep Learning Methods of Satellite Image Processing for Monitoring of Flood Dynamics in the Ganges Delta, Bangladesh

Investigating the Effect of Flood Flows on Morphological Changes Using a Series of Satellite Images: Rapid Changes in Morphology of Bazoft River

Assessing the social risks of flooding for coastal societies: a case study for Prince Edward Island, Canada

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