Analysing flood fatalities in Vietnam using national disaster database and tree-based methods

Luu, Chinh; Meding, Jason von; Kanjanabootra, Sittimont

doi:10.5194/nhess-2017-155

Cited by 14 publications

(11 citation statements)

References 44 publications

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“…Storms and hurricanes from the South China Sea annually land on the mainland and cause serious damage to the RRD from May to October [3], especially during the summer-autumn rice crop. We have addressed and solved the two main remaining problems in previous studies.…”

Section: Discussionmentioning

confidence: 99%

“…The Red River Delta (RRD) is one of the four plains with the largest rice-growing area in Vietnam (see Table 1). On average, the RRD suffers about 4 storms a year from the South China Sea, which cause heavy rainfall in high mountainous and delta areas from May to October [3]. As a result, large floods occur frequently.…”

Section: Rice and Flood In The Red River Deltamentioning

confidence: 99%

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Rapid Assessment of Flood Inundation and Damaged Rice Area in Red River Delta from Sentinel 1A Imagery

Anh

Man

et al. 2019

Remote Sensing

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The Red River Delta (RRD), including 11 provinces, is one of the four largest rice-growing areas in Vietnam. Tropical storms often occur and cause serious flooding from May to October annually in the RRD, which strongly affects the productivity of the summer–autumn rice, one of two main rice crops. Therefore, the rapid assessment of damaged rice area by flooding inundation is critical for farmers and the government. In this study, we proposed a methodology for quick estimation of rice areas damaged by flooding using Sentinel 1A (S1A) imagery. Firstly, the latest rice map was produced. Then, a Near Real-Time (NRT) flood map, which is estimated from S1A images at the closest time to a flooding event, was generated by excluding the yearly permanent map from the temporal water map. Our experiment was conducted for the assessment of damaged rice area by flooding from the tropical storm named Son-Tinh, which happened on 19–21 July 2018. A Support Vector Machine (SVM) classifier was applied on time-series of S1A VV with VH data (VVVH) to obtain a rice map for the winter-spring season of 2018 with 90.5% Overall Accuracy (OA) and 2.37% difference (12,544 ha) from the General Statistics Office (GSO) of Vietnam’s reports for the whole region. Then, the Otsu thresholding method was applied for permanent water surface extraction and NRT flood mapping. The estimated damaged area was compared to available provincial and communal statistics for validation and further analysis. Right after the Son-Tinh storm, the estimation of inundated rice was approximately 50% of the total rice area in the RRD (271,092 ha). As a result, rice damage level strongly corresponds to the inundation period. In addition, the rice-flooding frequency map over the RRD was estimated to show rice fields suffering a high risk of flooding during the rainy season in the RRD. Our experiment’s results highlight the potential of using Synthetic-Aperture Radar (SAR) imagery for fast monitoring and assessment of paddy rice areas affected by flooding at a large scale in the RRD region.

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Section: Discussionmentioning

confidence: 99%

Section: Rice and Flood In The Red River Deltamentioning

confidence: 99%

Rapid Assessment of Flood Inundation and Damaged Rice Area in Red River Delta from Sentinel 1A Imagery

Anh

Man

et al. 2019

Remote Sensing

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“…The standard of living in most Asian and African countries in terms of mitigation, control, and human settlement characteristics are much lower than those in most European countries, where preparedness, warning systems, and rescue procedures are more advanced. The strength one's house, for example, has 152 been demonstrated to have the greatest influence on FFs in countries such as Vietnam (1989-2015) (Luu et al, 2017). According to some authors, flood outcomes in terms of the number of fatalities, can be only be compared between countries characterized by similar population densities and gross domestic product per capita (Brazdova and Riha, 2014).…”

Section: Location Of the Accidentmentioning

confidence: 99%

Review article. Factors leading to the occurrence of flood fatalities: a systematic review of research papers published between 2010 and 2020

Petrucci

2021

Preprint

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Abstract. Floods kill several people every year in both developed and developing countries. The transfer of research findings from the academic community to practitioners, policy-makers and citizens may reduce the impact of floods on mortality. This systematic review analyzes 44 scientific articles extracted from WOS and SCOPUS databases written in English, published between 2010 and 2020, and focuses on flood fatalities. The first main finding of this review is the classification of drivers of flood mortality into two groups: the first group relates to the environment and the second group relates to the victims. The second main finding is the identification of strategies to practically cope with the identified drivers of flood fatalities. The main lacks of the review concern: a) the unavailability of papers based on flood fatality occurrence in developing countries and b) the absence of data focusing on people who have survived floods. This review amplifies useful findings, best practices, and lessons learned that can be useful for administrators, risk managers, and teachers of primary and secondary schools to mitigate the impact of future floods on human life.

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“…Decision tree analysis is a data mining method based on machine learning and is used to determine the independent variables that influence the classification of a set of independent variables and their order. This method is sometimes used to predict damage in the event of disaster (Haimes (2012), Kim (2018), Luu (2017)). The boundary values of those independent variables that can be divided into two groups that form the greatest dependent variable differential are located and established as independent variables.…”

Section: Analytical Approachmentioning

confidence: 99%

An Examination of the Self-Evaluations Over Time of the 3.11 Tsunami Survivors Regarding Their Post-Disaster Recovery

LEE¹,

Hanada²

2020

IDRiM Journal

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In this study, the factors that affected the sense of recovery of the victims of the Great East Japan Earthquake were analyzed from both short-term and long-term perspectives. We used the results of questionnaire surveys conducted in 2013 and 2017 amongst residents of Noda Village, Iwate Prefecture, to determine the factors that affected the sense of recovery of their personal lives as well as their sense of the recovery of the village itself. We also examined how differences in the choice of temporary housing affected their sense of recovery. Utilizing decision tree analysis, we clarified differences in the key factors that impacted their short-term and long-term perspectives as well as the sense of their own recovery and their sense of the village's recovery. Because the introduction of publicly-funded rental housing deviated from the temporary housing networks available in previous disasters, there remains the possibility that although the short-term sense of recovery of those in publicly-funded temporary housing was relatively low, it seemed to increase over the long-term.

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Analysing flood fatalities in Vietnam using national disaster database and tree-based methods

Cited by 14 publications

References 44 publications

Rapid Assessment of Flood Inundation and Damaged Rice Area in Red River Delta from Sentinel 1A Imagery

Rapid Assessment of Flood Inundation and Damaged Rice Area in Red River Delta from Sentinel 1A Imagery

Review article. Factors leading to the occurrence of flood fatalities: a systematic review of research papers published between 2010 and 2020

An Examination of the Self-Evaluations Over Time of the 3.11 Tsunami Survivors Regarding Their Post-Disaster Recovery

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