Vulnerability assessment of marine economic system based on comprehensive index and catastrophe progression model

Gao, Sheng; Sun, Hai; Ma, Miaosen; Lu, Yao; Yao, Yuan; Liu, Wei

doi:10.1080/20964129.2020.1834459

Cited by 9 publications

(6 citation statements)

References 24 publications

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“…Vulnerability has recently been widely applied in many research fields, such as disaster management, ecology, public health, climate change, land use, sustainability science, economics, and engineering. There is an increasing number of studies on climate change vulnerability [17][18][19][20], road network vulnerability [21], economic system vulnerability [22][23][24][25], social system vulnerability [26], urban vulnerability [27][28][29], and food security vulnerability [30][31][32][33][34]. Due to different research objects and disciplinary perspectives in different application fields, scholars hold great differences in the concepts of "vulnerability" vulnerability and vulnerability assessment [35,36].…”

Section: Vulnerability Researchmentioning

confidence: 99%

Trade vulnerability assessment in the grain-importing countries: A case study of China

2021

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Since the 2008 global food crisis, food security vulnerability has been a prominent topic in the food policy debate. However, vulnerability is inherently difficult to conceptualize and is more challenging to operationalize and measure. This study constructs a mathematical model and takes China as a case study to measure the vulnerability and sensitivity of China with its partners in the international grain trade. The results show that 1) the degree of interdependence between China and its grain trading partners is asymmetric, which generates trade vulnerability or economic power; 2) the vulnerability of China’s food trade shows a high spatiotemporal heterogeneity among countries: the higher vulnerability zones are concentrated in North America and Northeast Asia, and the scope of the higher vulnerability zones tends to expand; 3) Our results also reveal that China also has different sensitivities to fluctuations in grain markets from different countries, and the higher sensitive zones of the grain trade in China are mainly distributed in America, Europe, and Oceania. The main contribution of this paper is the development of a methodology for food trade vulnerability assessment and examines the influence of international food trade on food security in importing countries, measured using the vulnerability index and sensitivity index. Nevertheless, the conclusions of this study can be considered preliminary, and there remains great potential for future studies to deepen and broaden our analyses further.

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Section: Vulnerability Researchmentioning

confidence: 99%

Trade vulnerability assessment in the grain-importing countries: A case study of China

2021

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“…TOPSIS is a method for evaluating the relative merits of existing solutions [11]. The data of each indicator in the past years is used as a solution, and each solution in the past years is compared and analysed with the best value of each indicator in the past years, which makes the research more relevant to the real situation of the research subject.…”

Section: Topsis Methods For Calculating Vulnerability Indicesmentioning

confidence: 99%

“…A ij (11) where: A ij denotes the barrier of a single indicator at the indicator level; w ij denotes the contribution of the indicator to the overall target, here using the indicator weight value determined by the CRITIC method; d ij is the degree of deviation of the indicator, denoting the gap between the single indicator and the maximum target, set as the gap between the standardised value of the indicator and 1; x ij denotes the standardised value of the j th indicator; and U denotes the barrier at the guideline level.…”

Section: The Barrier Model Calculates the Barrier Level For Each Indi...mentioning

confidence: 99%

Study on the Vulnerability of Port Logistics System of Guangzhou Port Under the New Development Pattern

Liu,

Qu,

Yan

2023

Atlantis Highlights in Intelligent Systems

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Under the new development pattern, it is necessary for the logistics industry to play its leading and linking role better. Port is an important window for domestic and foreign trade, and the sustainable and healthy development of its logistics system is particularly important. Vulnerability is an important indicator to evaluate the healthy development of the logistics system, and also an important guide to achieve sustainable development. With the new development pattern as the background, this paper constructs the evaluation index system of port logistics system combined with the theory of vulnerability, adopts the CRITIC-TOPSIS method to measure the overall development of port logistics system, identifies the main constraints combined with the obstacle degree model and puts forward specific suggestions. The results show that the vulnerability of Guangzhou port logistics system shows a fluctuating trend. From 2011 to 2020, the vulnerability index increases from 0.4870 to 0.5487, in which the sensitivity index increases and the resilience index decreases. The main obstacle factors gradually turn from port logistics operation and urban economic subsystem to logistics infrastructure, collection and distribution and port logistics support subsystem.

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“…For TOPSIS analysis, after normalization, entropy weight is calculated. Entropy weight method (EWM) is one of the popular methods in the decision-making process 68 since it relies on the information gained from each index value and uses inherent law to calculate weight for each attribute and weightage according to variation of index 69 . First attributes were normalized using vector normalization as of their cardinality 70 , 71 .…”

Section: Vulnerability Assessmentmentioning

confidence: 99%

Enhancing co-seismic landslide susceptibility, building exposure, and risk analysis through machine learning

Pyakurel,

K.C.,

Dahal

2024

Sci Rep

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Landslides are devastating natural disasters that generally occur on fragile slopes. Landslides are influenced by many factors, such as geology, topography, natural drainage, land cover, rainfall and earthquakes, although the underlying mechanism is too complex and very difficult to explain in detail. In this study, the susceptibility mapping of co-seismic landslides is carried out using a machine learning approach, considering six districts covering an area of 12,887 km2 in Nepal. Landslide inventory map is prepared by taking 23,164 post seismic landslide data points that occurred after the 7.8 MW 2015 Gorkha earthquake. Twelve causative factors, including distance from the rupture plane, peak ground acceleration and distance from the fault, are considered input parameters. The overall accuracy of the model is 87.2%, the area under the ROC curve is 0.94, the Kappa coefficient is 0.744 and the RMSE value is 0.358, which indicates that the performance of the model is excellent with the causative factors considered. The susceptibility thus developed shows that Sindhupalchowk district has the largest percentage of area under high and very high susceptibility classes, and the most susceptible local unit in Sindhupalchowk is the Barhabise municipality, with 19.98% and 20.34% of its area under high and very high susceptibility classes, respectively. For the analysis of building exposure to co-seismic landslide susceptibility, a building footprint map is developed and overlaid on the co-seismic landslide susceptibility map. The results show that the Sindhupalchowk and Dhading districts have the largest and smallest number of houses exposed to co-seismic landslide susceptibility. Additionally, when conducting a risk analysis based on susceptibility mapping, as well as considering socio-economic and structural vulnerability in Barhabise municipality, revealed that only 106 (1.1%) of the total 9591 households, were found to be at high risk. As this is the first study of co-seismic landslide risk study carried out in Nepal and covers a regional to the municipal level, this can be a reference for future studies in Nepal and other parts of the world and can be helpful in planning development activities for government bodies.

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Vulnerability assessment of marine economic system based on comprehensive index and catastrophe progression model

Cited by 9 publications

References 24 publications

Trade vulnerability assessment in the grain-importing countries: A case study of China

Trade vulnerability assessment in the grain-importing countries: A case study of China

Study on the Vulnerability of Port Logistics System of Guangzhou Port Under the New Development Pattern

Enhancing co-seismic landslide susceptibility, building exposure, and risk analysis through machine learning

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