Dynamic monitoring of flood disaster based on remote sensing data cube

Wang, Zhicheng; Gao, Zhiqiang

doi:10.1007/s11069-022-05508-3

Cited by 5 publications

(4 citation statements)

References 37 publications

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“…According to Wang, et al, (2023), monsoon floods of 2022 in Pakistan damaged 3,115 kilometres of roads and destroyed 439 bridges. The widespread demolition of infrastructure translates to more difficulties for students in terms of access to schools, absenteeism, and dropouts.…”

Section: Damages Caused By 2022 Flood and Its Impact On Educationmentioning

confidence: 99%

“…According to Wang et al, (2023), strategic planning around post-flood for the continuity of education should take into consideration the physical, and organisational context of the educational institutions, along with the capacity and vulnerability of the schools. They further state that if Disaster Risk Reduction was included in education sector policies, the government would be able to eradicate weak and substandard structures and buildings.…”

Section: Learning From Other Contextsmentioning

confidence: 99%

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Catastrophic Sways of Floods on the Education Sector in Pakistan

Samad,

Sheikh

2024

AESSR

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This study aimed to identify the impact of the 2022 floods on the education sector of Pakistan and to cope with the challenges faced by various stakeholders in the sector. The study employed qualitative research methodology to curate in-depth knowledge of the issue. A semi-structured interview guide was prepared to collect the data through individual interviews. The findings showed that the effects of floods ranged from damage to the school buildings to administrative and institutional infrastructure, along with a thrust on the psychosocial and economic impact on the families, educators, and children. The findings further highlighted the educational activities that had to be halted for months, leaving educators and learners stranded. It also highlighted the observations of local community leaders to deal with the education crisis on an urgent basis, giving direction in terms of preparedness to handle floods of similar magnitude in the future. The recommendations include reconstruction of the damaged schools, teacher training, coordination and cooperation among various departments, inter-sectoral cooperation to reach out to the poorest, and the provision of Temporary Learning Centres (TLCs). The study will assist in creating awareness about the grave nature of damages that occurred to the educational sector of Pakistan and the need for support.

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Section: Damages Caused By 2022 Flood and Its Impact On Educationmentioning

confidence: 99%

Section: Learning From Other Contextsmentioning

confidence: 99%

Catastrophic Sways of Floods on the Education Sector in Pakistan

Samad,

Sheikh

2024

AESSR

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“…Recurrent floods throughout the year threaten some regions. According to statistics, the average annual flood losses in China reached 19.2 billion USD in the past 30 years, accounting for 54% of the total direct economic losses caused by weather disasters in China [3] . According to the information from China National Disaster Reduction Network, from 2004 to 2019, Sichuan torrential rainfall and floods have been listed in the annual "Top Ten National Natural Disaster Events" 15 times [4] .…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment of Flood Disaster in Sichuan Province Based on GIS

2023

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In the context of global climate change, flood disaster has become one of the significant disasters endangering human life. Sichuan Province has more annual precipitation and complex landforms, which suffer from yearly floods. To reveal the spatial distribution and spatiotemporal dynamic change characteristics, we developed a risk assessment model based on geographic information systems and natural disaster risk assessment theory. Considering both natural and human factors, precipitation, terrain, climate type, population, and GDP are selected as evaluation indexes. We Used the expert score-AHP method to obtain the annual flood disaster risk regionalization from 2017 to 2021. In the end, the results were compared with the entropy weight method in the objective weighting method. The results showed that the comprehensive flood disaster risk in Sichuan Province is higher in the east and lower in the west. The flood disaster risk in the eastern hill area, Panxi area, and northeast Sichuan Basin is generally higher. In contrast, that in the west Sichuan Plateau is lower. Based on the evaluation results, it is found that the risk assessment of flood disasters based on expert scoring-AHP method is more in line with the actual situation.

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“…IGH spatiotemporal resolution remote sensing images are in high demand for numerous applications such as crop yield estimation [1], [2], wetland observation [3], [4], and disaster assessment [5], [6]. However, due to the contradiction between satellite scanning swath and pixel size, no single satellite can provide continuous high-resolution surface monitoring [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Object-Level Hybrid Spatiotemporal Fusion: Reaching a Better Tradeoff Among Spectral Accuracy, Spatial Accuracy, and Efficiency

Guo,

Shi

2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Spatiotemporal fusion (STF) is a cost-effective way to complement the spatiotemporal resolution of multi-source images, which has been employed in various applications requiring image sequences. In real-world applications, the spectral accuracy, spatial accuracy and efficiency of STF play a critical role. Despite this, most STF methods focus on improving the spectral accuracy, while the challenges of spatial information loss and low efficiency have received limited attention. Additionally, the improvements of spectral accuracy, spatial accuracy and efficiency in STF are contradictory, and existing STF methods cannot balance them well, which limits their reliability and applicability for various STF tasks. To solve above issues, this study proposes an objectlevel hybrid spatiotemporal fusion method (OL-HSTFM), which incorporates the efficiency advantage of object-level fusion strategy, spectral accuracy advantage of the three-step method (Fit-FC), and the spatial accuracy advantage of the spatial and temporal adaptive reflectance fusion model (STARFM). The performance of OL-HSTFM was compared with two classic STF methods and eight state-of-the-art STF methods at two sites. The experimental results indicate that OL-HSTFM outperforms the other 10 methods in overall performance and has excellent efficiency. Furthermore, this study proposes a new metric that can assess the accuracy of both spatial and spectral domains in STF, which provides a more comprehensively and intuitively measurement of the quality of fused images compared to commonly used metrics. The program of OL-HSTFM is openly available on https://github.com/Andy-cumt/Object-levelspatiotemporal-fusion-models.

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Dynamic monitoring of flood disaster based on remote sensing data cube

Cited by 5 publications

References 37 publications

Catastrophic Sways of Floods on the Education Sector in Pakistan

Catastrophic Sways of Floods on the Education Sector in Pakistan

Risk Assessment of Flood Disaster in Sichuan Province Based on GIS

Object-Level Hybrid Spatiotemporal Fusion: Reaching a Better Tradeoff Among Spectral Accuracy, Spatial Accuracy, and Efficiency

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