Disaster risk governance for district-level landslide risk management in Bangladesh

Alam, Edris; Ray-Bennett, Nibedita S.

doi:10.1016/j.ijdrr.2021.102220

Cited by 51 publications

(46 citation statements)

References 48 publications

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“…The GoB received international attention for its ability to reduce the number of deaths per year from frequently occurring natural hazards with the exception to sudden onset of earthquake and landslide disasters. 35 The formulation of disaster management policies, rules and acts and establishments of institutions at national and local levels implies that the country has achieved Sendai's Target for the period of 2015-2020. 35 At the same time, the weaknesses identified by the participants of this research in regard to coordinating the implementation of COVID-19 related physical distancing policies, which are a cause of concern.…”

Section: Dovepressmentioning

confidence: 99%

“…35 The formulation of disaster management policies, rules and acts and establishments of institutions at national and local levels implies that the country has achieved Sendai's Target for the period of 2015-2020. 35 At the same time, the weaknesses identified by the participants of this research in regard to coordinating the implementation of COVID-19 related physical distancing policies, which are a cause of concern. At the same time, these concerns are also true opportunities to improve governance at all levels.…”

Section: Dovepressmentioning

confidence: 99%

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Public Trust in COVID-19 Prevention and Responses Between January and May 2020 in Bangladesh

Alam¹,

Abdouli²,

Khamis³

et al. 2021

RMHP

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Section: Dovepressmentioning

confidence: 99%

Section: Dovepressmentioning

confidence: 99%

Public Trust in COVID-19 Prevention and Responses Between January and May 2020 in Bangladesh

Alam¹,

Abdouli²,

Khamis³

et al. 2021

RMHP

Self Cite

View full text Add to dashboard Cite

“…Traditionally, town planners and strategic decision-ma kers have relied on traditional statistical analyses of regional landslide databases for strategic planning and policy implementation [2], [15], [17], [35], [36]. Previous research into ML-based algorithms has also relied on regional and local datasets, where the data were manually prepared and ML models were manually created by expert data scientists, researchers, and engineers.…”

Section: Discussionmentioning

confidence: 99%

“…From this vast number of scenarios, 25 were randomly selected to demonstrate the applicability of the system using laptops or web-enabled mobile devices, with a clustering accuracy (area under the curve (AUC)) of up to 0.951) and a prediction accuracy (mean absolute percentage error (MAPE)) of up to 0.10. Based on the existing literature [7]- [15], the proposed system is the first to utilize clustering algorithms such as automated anomaly detection (AUC up to 0.951) and decomposition tree analysis (AUC up to 0.896) in the landslide domain.…”

Section: Introductionmentioning

confidence: 99%

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Knowledge Discovery of Global Landslides Using Automated Machine Learning Algorithms

Sufi¹,

Alsulami

2021

IEEE Access

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Understanding the complex dynamics of global landslides is essential for disaster planners to make timely and effective decisions that save lives and reduce the economic impacts on society. Using NASA's inventory of global landslide data, we developed a new machine learning (ML)-based system for town planners, disaster recovery strategists, and landslide researchers. Our system revealed hidden knowledge about a range of complex scenarios created from five landslide feature attributes. Users of our system can select from a list of 1.295 10 64 possible global landslide scenarios to discover valuable knowledge and predictions about the selected scenario in an interactive manner. Three ML algorithms-anomaly detection, decomposition analysis, and automated regression analysis-are used to elicit detailed knowledge about 25 scenarios selected from 14,532 global landslide records covering 12,220 injuries and 63,573 fatalities across 157 countries. Anomaly detection, logistic regression, and decomposition analysis performed well for all scenarios under study, with the area under the curve averaging 0.951, 0.911, and 0.896, respectively. Moreover, the prediction accuracy of linear regression had a mean absolute percentage error of 0.255. To the best of our knowledge, our scenario-based ML knowledge discovery system is the first of its kind to provide a comprehensive understanding of global landslide data.

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The Anthropogenic Aggravation of Landslide Disasters in Bangladesh: Key Informants’ Perspectives

Ahmed

Alam²,

Ahmed

et al. 2023

Progress in Landslide Research and Technology, Volume 1 Issue 2, 2022

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Landslide disasters in Bangladesh’s Chittagong hill districts (CHD) put lives, livelihood, and the ecosystem at risk. Therefore, understanding the causes of landslide events in CHD is crucial to preparing and implementing disaster risk reduction (DRR) strategies. The causes of landslides are generally seen through the lenses of physical science. However, to better understand the landslide disaster mechanism, it is essential to explore the human activities that trigger and aggravate the events. This article uses qualitative social science tools and techniques to investigate CHD’s anthropogenic-induced landslide disasters. Forty key informants from diverse professions, ethnicities, communities, and backgrounds were interviewed between 9 June and 3 November 2020. The recorded interviews were translated, transcribed, and thematically analysed in NVivo software. The results show that human-induced landslides in CHD evolve around three broader areas: demography, climate change, and lack of coordination and regulation. First, increased population, hill cutting, deforestation, manipulated agricultural practices, and sand and stone extraction is the leading anthropogenic activities of landslides in CHD. Second, the influx of Rohingya refugees into Bangladesh significantly increased landslide vulnerability. Third, climate change-induced erratic rainfall is leading to more rainfall-induced landslides. Finally, a lack of coordination and regulations among various institutions hinders the DRR process. The short, medium- and long-term recommendations include stopping illegal hill cutting and deforestation, regulating heavy vehicles, increasing coordination, institutionalising early warning systems, conducting massive awareness campaigns, conducting further research, addressing challenges such as lightning, climate migration and conflict, and creating a master plan exclusive for the entire region and coming up with a political consensus for better implementation of the plan.

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Disaster risk governance for district-level landslide risk management in Bangladesh

Cited by 51 publications

References 48 publications

Public Trust in COVID-19 Prevention and Responses Between January and May 2020 in Bangladesh

Public Trust in COVID-19 Prevention and Responses Between January and May 2020 in Bangladesh

Knowledge Discovery of Global Landslides Using Automated Machine Learning Algorithms

The Anthropogenic Aggravation of Landslide Disasters in Bangladesh: Key Informants’ Perspectives

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