Multiple Kernel Learning with Maximum Inundation Extent from MODIS Imagery for Spatial Prediction of Flood Susceptibility

Hu, Qiang; Zhu, Yuemin; Hu, He-xuan; Guan, Zhuang; Qian, Zeyu; Yang, Aiming

doi:10.1007/s11269-021-03010-2

Cited by 4 publications

(1 citation statement)

References 42 publications

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“…EA estimates the potentially qualified application of a satellite sensor by analyzing its past applications. Hu et al [17] and Ban et al [18] applied a Moderate Resolution Imaging Spectroradiometer in their flood water observation scenarios because its observation data are frequently utilized in flood submerged area extraction. Rahman and Thakur [19] produced the flood map through the analysis of time-series images taken by Synthetic Aperture Radar (SAR), having proved that SAR can observe the flood water.…”

Section: Introductionmentioning

confidence: 99%

Observation Capability Evaluation Model for Flood-Observation-Oriented Satellite Sensor Selection

Duan,

Zhang,

Liu

et al. 2023

Applied Sciences

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Satellite sensors are one of the most important means of collecting real-time geospatial information. Due to their characteristics such as large spatial coverage and strong capability for dynamic monitoring, they are widely used in the observation of real-time flood situation information for flood situational awareness and response. Selecting the optimum sensor is vital when multiple sensors exist. Presently, sensor selection predominantly hinges on human experience and various quantitative and qualitative evaluation methods. Yet, these methods lack optimization considering the flood’s spatiotemporal characteristics, such as different flood phases and geographical environmental factors. Consequently, they may inaccurately evaluate and select the inappropriate sensor. To address this issue, an innovative observation capability evaluation model (OCEM) is proposed to quantitatively pre-evaluate the performance of flood-water-observation-oriented satellite sensors. The OCEM selects and formulates various flood-water-observation-related capability factors and supports dynamic weight assignment considering the spatiotemporal characteristics of the flood event. An experiment involving three consecutive flood phase observation tasks was conducted. The results demonstrated the flexibility and effectiveness of the OCEM in pre-evaluating the observation capability of various satellite sensors across those tasks, accounting for the spatiotemporal characteristics of different flood phases. Additionally, qualitative and quantitative comparisons with related methods further affirmed the superiority of the OCEM. In general, the OCEM has provided a “measuring table” to optimize the selection and planning of sensors in flood management departments for acquiring real-time flood information.

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Section: Introductionmentioning

confidence: 99%

Observation Capability Evaluation Model for Flood-Observation-Oriented Satellite Sensor Selection

Duan,

Zhang,

Liu

et al. 2023

Applied Sciences

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Dynamic monitoring of flood disaster based on remote sensing data cube

Wang

Gao

2022

Nat Hazards

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High-frequency dynamic monitoring of flood disaster using remote sensing technology is crucial for accurate decision-making of disaster prevention and relief. However, the current trade-off between spatial and temporal resolution of remote sensing sensors limits their application in high-frequency dynamic monitoring of flood disaster. To deal with this challenge, in this study, first, to construct the cloud-free MODIS data cube, we removed the cloudy areas in MODIS original data cube by using the information provided by GPM rainfall data. Then, we fused the cloud-free MODIS data cube and Landsat-8 data by using the spatio-temporal data fusion algorithm to construct the high spatio-temporal resolution (Landsat-like) data cube. Last, the high spatio-temporal resolution (Landsat-like) data cube was used for high-frequency dynamic monitoring of flood disaster. Our study had three main results: ⑴The differences between cloud-free MODIS data cube and observations were small and the cloud-free MODIS data cube could be used for subsequent studies. ⑵ High spatio-temporal resolution (Landsatlike) data cube reflected the spatio-temporal changes of flood well and could be used for the highfrequency dynamic monitoring of flood disaster. ⑶ There were two floods occurred in the study area

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Susceptibility Assessment of Flash Floods: A Bibliometrics Analysis and Review

Liu

et al. 2022

Remote Sensing

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A flash flood disaster is one of the most destructive natural disasters. With the increase in extreme rainfall events, more and more areas will be threatened by flash floods. The flash flood susceptibility assessment is the basis of flash flood risk assessment and is also an important step in flash flood disaster management. Based on Citespace analysis tools, this study made a bibliometric and visualized analysis of 305 documents collected in the core collection of Web of Science in the past 15 years, including the analysis of the number of publications and citation frequency, influence analysis, keyword analysis, author co-citation analysis, and institutional co-operation analysis. This paper summarizes the current research status and future development trend of flash flood susceptibility assessment from five key research subfields, including assessment scale, assessment unit, assessment index, assessment model, and model assessment method, discusses the analysis of the application of remote sensing and GIS in flash flood susceptibility assessment, discusses the problems encountered in the current research of the five subfields, and provides suggestions for flash flood hazard control.

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Multiple Kernel Learning with Maximum Inundation Extent from MODIS Imagery for Spatial Prediction of Flood Susceptibility

Cited by 4 publications

References 42 publications

Observation Capability Evaluation Model for Flood-Observation-Oriented Satellite Sensor Selection

Observation Capability Evaluation Model for Flood-Observation-Oriented Satellite Sensor Selection

Dynamic monitoring of flood disaster based on remote sensing data cube

Susceptibility Assessment of Flash Floods: A Bibliometrics Analysis and Review

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