Rapid assessment of a flood‐affected population through a spatial data model

Raza, Sharique; Ahsan, Moien; Ahmad, Sajid Rashid

doi:10.1111/jfr3.12134

Cited by 7 publications

(3 citation statements)

References 9 publications

(12 reference statements)

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“…However, these estimates can still provide valuable information by pinpointing areas of interest for more focused investigation. Several recent studies note that rapid assessments of economic losses can aid in the allocation of potentially scarce resources during the recovery and reconstruction phases of a flood event [54,55]. The case study application presented here illustrates how the damages could be assessed using historical imagery, but the same process could also be applied to flood forecast maps, further increasing its value for future risk planning.…”

Section: Damage Estimate Validationmentioning

confidence: 94%

Socioeconomic Impact Evaluation for Near Real-Time Flood Detection in the Lower Mekong River Basin

Oddo¹,

Ahamed²,

Bolten³

2018

Hydrology

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Flood events pose a severe threat to communities in the Lower Mekong River Basin. The combination of population growth, urbanization, and economic development exacerbate the impacts of these events. Flood damage assessments, critical for understanding the effects of flooding on the local population and informing decision-makers about future risks, are frequently used to quantify the economic losses due to storms. Remote sensing systems provide a valuable tool for monitoring flood conditions and assessing their severity more rapidly than traditional post-event evaluations. The frequency and severity of extreme flood events are projected to increase, further highlighting the need for improved flood monitoring and impact analysis. In this study we integrate a socioeconomic damage assessment model with a near real-time flood remote sensing and decision support tool (NASA's Project Mekong). Direct damages to populations, infrastructure, and land cover are assessed using the 2011 Southeast Asian flood as a case study. Improved land use/land cover and flood depth assessments result in rapid loss estimates throughout the Mekong River Basin. Results suggest that rapid initial estimates of flood impacts can provide valuable information to governments, international agencies, and disaster responders in the wake of extreme flood events.

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Section: Damage Estimate Validationmentioning

confidence: 94%

Socioeconomic Impact Evaluation for Near Real-Time Flood Detection in the Lower Mekong River Basin

Oddo¹,

Ahamed²,

Bolten³

2018

Hydrology

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“…Bhatt et al [26] used multitemporal satellite images, hydrological observations, and gridded population data to estimate the population affected by a flood. Raza et al [27] superimposed the flood extent and gridded population data to count the number of people in the affected population in the flooded area. Ozcelik et al [28] proposed a GIS-based methodology to model the population affected by storm surges.…”

Section: Traditional Approaches To Assessing Affected Populationmentioning

confidence: 99%

Assessing the Intensity of the Population Affected by a Complex Natural Disaster Using Social Media Data

Cheng

Zhang

et al. 2019

IJGI

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Complex natural disasters often cause people to suffer hardships, and they can cause a large number of casualties. A population that has been affected by a natural disaster is at high risk and desperately in need of help. Even with the timely assessment and knowledge of the degree that natural disasters affect populations, challenges arise during emergency response in the aftermath of a natural disaster. This paper proposes an approach to assessing the near-real-time intensity of the affected population using social media data. Because of its fatal impact on the Philippines, Typhoon Haiyan was selected as a case study. The results show that the normalized affected population index (NAPI) has a significant ability to indicate the affected population intensity. With the geographic information of disasters, more accurate and relevant disaster relief information can be extracted from social media data. The method proposed in this paper will benefit disaster relief operations and decision-making, which can be executed in a timely manner.

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“…Scientific and accurate flood hazard assessment is the theoretical basis and premise of flood prevention and disaster reduction measures, and it is also one of the current research hotspots [3][4][5]. Previous research mainly focused on static assessment, assessing the loss of a certain period of time after the flood [6][7][8]. Few studies have focused on how losses change during flood development.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Assessment of Flood Hazard Based on Points-of-Interest Data

Shao

Liu

2021

Advances in Transdisciplinary Engineering

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In order to better formulate flood prevention and disaster mitigation measures and reduce the impact of urban flood on social development, it is necessary to conduct a scientific and accurate flood hazard assessment. The development of big data technology has brought new opportunities for flood hazard assessment. This study used a coupling model to simulate urban flood, and used the HR method to classify flood hazard. The dynamic change process of two types of Points-of-Interest(POIs) for catering services and living services under different flood hazard degrees were counted. The results showed that (1) In the northern part of the basin, mountainous, impervious ground and the lack of effective drainage channels have combined to cause more serious floods; (2) The flood hazard were mainly low-degree in the study area. Moderate flood hazard mainly occurred in farmland and built-up land. High-degree and extreme-degree flood hazard mainly occurred on both sides of rivers in the northwest of the basin; (3) Affected by the rainfall pattern, the number of POI affected by flood presented the characteristics of “three stages” under four flood hazard degrees; (4) The POIs of the two services was most seriously affected by the flood when the rainfall just stopped; (5) In terms of the proportion of POIs affected by floods, the impact of floods on the two industries is basically the same, but from the perspective of the number of POIs affected by floods, catering services will be more affected; (6) The spatial location of the POIs led to a slight difference in the trend of the number of POIs under high-degree and extreme-degree flood hazard. This study provided a new method for urban flood hazard dynamic assessment, which could help decision makers formulate more targeted flood prevention and disaster mitigation measures

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Rapid assessment of a flood‐affected population through a spatial data model

Cited by 7 publications

References 9 publications

Socioeconomic Impact Evaluation for Near Real-Time Flood Detection in the Lower Mekong River Basin

Socioeconomic Impact Evaluation for Near Real-Time Flood Detection in the Lower Mekong River Basin

Assessing the Intensity of the Population Affected by a Complex Natural Disaster Using Social Media Data

Dynamic Assessment of Flood Hazard Based on Points-of-Interest Data

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