Urban flooding risk assessment based on GIS- game theory combination weight: A case study of Zhengzhou City

Peng, Jiaqi; Zhang, Jianmin

doi:10.1016/j.ijdrr.2022.103080

Cited by 79 publications

(35 citation statements)

References 31 publications

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“…The conventional objective methods of weight calculation include the entropy method and the CRITIC method. [14] The CRITIC method is a more scientific and objective weighting method, compared with the entropy method, which only considers the information quantity of indicators and ignores the correlation between indicators, the CRITIC method determines the weights of indicators based on the comparison intensity and conflict between evaluation indicators. The larger the standard deviation of the value of the indicator, the greater the amount of information reflected, and the greater the weight; correlation refers to the correlation coefficient between two indicators, the smaller the correlation coefficient, the more similar the amount of information reflected, and the smaller the weight.…”

Section: Critic Methodsmentioning

confidence: 99%

An improved multi-objective gray target model for project resource allocation selection Research

2023

E3S Web Conf.

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In response to the traditional method of using a single subjective or objective assignment, AHP (hierarchical analysis) subjective weights and CRITIC (hierarchical relevance of importance criteria method) objective weights are coupled with the Lagrange multiplier method to obtain combined weights, and the multiobjective gray target decision model is used to establish event set, countermeasure set, and situation set to obtain the resource ranking that affects the project resource deployment problem, which provides a basis for the project participants to make decisions and plan for the project. Taking the municipal road project as an example, a judgment matrix is established. The results show that the model constructed in this paper is relatively consistent with the actual situation.

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Section: Critic Methodsmentioning

confidence: 99%

An improved multi-objective gray target model for project resource allocation selection Research

2023

E3S Web Conf.

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“…Flood risk assessment is an interdisciplinary problem of natural and social disciplines, which involves the evaluation of complex systems of nature, society and economy (Peng et al, 2022). According to the previous research on flood risk analysis in Huaihe River basin (Wu et al, 2015), and the characteristics of the research area, seven indicators were selected, as shown in Figure 3.…”

Section: (1) Evaluation Indicatorsmentioning

confidence: 99%

“…Sepehri et al (2019) used five indicators regarding the dangers of flood to assess flood hazard of Hamadan city, namely elevation, slope, distance to discharge channels, index of development and persistence of the drainage network and infiltration rate. Peng et al (2022) selected six evaluation indicators of flood depth, population density, land use/land cover, road network density, night-time light brightness, and, medical rescue point, to conduct urban flooding risk assessment based on GIS in Zhengzhou city. Risk assessment of flood disasters refers to the assessment and estimation of the intensity of natural disaster factors and the potential disaster degree, and the natural and social attributes of natural disasters should be taken into account in risk assessment (Koks et al, 2015;Zhou et al, 2017;Zhang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Flood risk analysis and mapping in Henan Province using remotely sensed data and GIS techniques

Zhang

et al. 2022

Remote Sensing Technologies and Applications in Urban Environments VII

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Zhengzhou City suffered the strongest rainstorm in history in July 2021, floods and other secondary disasters have greatly endangered the property and safety of local residents in Henan Province, China. In this paper, the flood risk of Henan Province was analyzed from the three perspectives of hazard, exposure and vulnerability, and seven factors of rainfall, elevation, slope, distribution density of river network, population, GDP and arable land occupation ratio were selected to create a flood disaster risk evaluation index system. Remotely sensed data and GIS were used to analyze and map the influencing factors, and then the comprehensive risk results of flood disasters in Henan Province were obtained based on analytic hierarchy process (AHP) method. Results show that the higher-risk area and high-risk area mainly locate in cities of Xinyang, Luohe, Zhumadian, Zhoukou and Xuchang, as well as the north of Zhengzhou, accounting for 43% of the total area of Henan Province. High risk area is mainly caused by high hazard of the flat terrain and abundant rainfall. The lower-risk area is mainly distributed in Sanmenxia, Jiyuan and Anyang, and the western part of Luoyang, that locate in high-elevation areas, and the vulnerability index of GDP is low in these areas. The rest of the areas are medium-risk areas. This research provides the background information for disaster prevention and mitigation management in Henan Province.

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“…According to their research, land use is significant in assessing risk as it can control average runoff. The Game Theory method were used to developed a flood risk assessment, incorporating hazard and vulnerability components [15]. They explored using night-time satellite imagery to represent an economic vulnerability in a region.…”

Section: Introductionmentioning

confidence: 99%

Combining Landsat, VIIRS Night-time Light, and Sentinel-1 SAR for Spatial Flood Risk Assessment in Coastal Area: an Earth Engine Cloud Computing Process

Siddiq,

Sejati

2023

IOP Conf. Ser.: Earth Environ. Sci.

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The intensity of development in coastal areas stimulates various potential issues such as flood disasters. This study aims to demonstrate the importance of latest methods and geospatial data as inputs for coastal spatial planning policies in efforts to reduce flood disaster risks. Leveraging spatial analysis with cloud computing through Google Earth Engine (GEE), this research assesses flood risk components—hazards, vulnerability, and capacity. The method involves processing SAR Sentinel-1 data to map flood inundation as a representation of hazards, analyzing Landsat and WorldPop data to evaluate vulnerability, and assessing capacity by utilizing VIIRS nighttime light level imagery to determine economic activities. The chosen research study location is the coastal area of Pekalongan due to frequent flood disasters throughout the year. The results demonstrate that cloud computing is capable of assessing flood risks. The flood inundation model using SAR data covers an area of 2,780 hectares with an accuracy of 96.75%. The analysis also reveals the highest vulnerability level, reaching 15.7% (946.32 hectares) of the total area. The capacity analysis indicates a medium to high level of 15% (913.6 hectares). The assessment of flood risks in the coastal area is dominated by the medium to very high-risk class, covering 43% (2,631.84 hectares) of the area. In conclusion, integrating cloud-based flood risk modeling into spatial planning is crucial, considering disaster resilience for sustainable human habitats.

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Urban flooding risk assessment based on GIS- game theory combination weight: A case study of Zhengzhou City

Cited by 79 publications

References 31 publications

An improved multi-objective gray target model for project resource allocation selection Research

An improved multi-objective gray target model for project resource allocation selection Research

Flood risk analysis and mapping in Henan Province using remotely sensed data and GIS techniques

Combining Landsat, VIIRS Night-time Light, and Sentinel-1 SAR for Spatial Flood Risk Assessment in Coastal Area: an Earth Engine Cloud Computing Process

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