Assessing and Improving Flood and Landslide Community Social Awareness and Engagement via a Web Platform: The Case of Italy

Bignami, Daniele Fabrizio; Dragoni, Alessio; Menduni, Giovanni

doi:10.1007/s13753-018-0199-0

Cited by 19 publications

(10 citation statements)

References 18 publications

(16 reference statements)

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“…Root node has the prior probability, while the child node has no prior probability but conditional probability. GIS is an appropriate tool for collecting and processing data with attributes for deriving regional indicators on flood risk (Bignami et al 2018), which is a significant procedure in effective risk estimation. Building analytic units based on grids or administrative areas, GIS is capable of integrated modelling on natural conditions including climate, topography, hydrology, and other social and economic features.…”

Section: Bn Model and Gis Descriptionmentioning

confidence: 99%

Assessing urban flood disaster risk using Bayesian network model and GIS applications

Shen

Wang

et al. 2019

Geomatics, Natural Hazards and Risk

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With global climate change, cities face the challenge of increasing flood disaster caused by heavy rainfall, and the prediction and assessment of flood disaster risk is a crucial step towards risk mitigation and adaptation planning. In this study, a method combining Bayesian network (BN) model and geographic information system (GIS), which can capture the potential relationships between factors impacting flood disaster and has capacity of quantifying uncertainty and utilizing both data and knowledgebased sources, was proposed to assess flood disaster risk. The proposed methodology was applied in a case study to assess flood disaster risk and to diagnose the reason for flood disaster in Zhengzhou City, and the results were validated by comparing with actual situation. The results show that that the relative error of very-low, low, moderate, high and very-high risk predicted by the proposed model is 12.57%, 13.21%, 2.23%, 19.63% and 21.65%, respectively, which demonstrates the discriminative power of the established model. Based on the spatial distribution of different risk levels, it can be recognized that the flood disaster risk in Zhengzhou City is decreasing from the middle to the surroundings. The results provide some basis for the field control and management of urban flood disaster.

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Section: Bn Model and Gis Descriptionmentioning

confidence: 99%

Assessing urban flood disaster risk using Bayesian network model and GIS applications

Shen

Wang

et al. 2019

Geomatics, Natural Hazards and Risk

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“…Trust in risk communication sources is inevitable for advanced disaster risks communication [130]. They do not listen to authorities [131]. In risk communication process, the role of local leaders is unimportant because the local community does not have much trust in local leaders [130].…”

Section: Social Awareness About Flood and Its Impactmentioning

confidence: 99%

“…Social media is the main bridge for enhancing communications between government agencies and people [131]. They cares most about community's interest [130].…”

Section: Social Awareness About Flood and Its Impactmentioning

confidence: 99%

Disaster risk management: Focused to flood hazard and its impact in Pakistan

2022

Global NEST: The International Journal

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<p>Recently, weather and climate related extreme occasions circumstances such as droughts, heat waves, bush fires and floods are increasing around the world. South Asian countries, that have the highest annual average number of people physically affected by natural hazards mostly by floods. Most popular flood risk areas are urban areas because there is rapid urbanization infrastructure and uncontrolled development. These are the most common factors that It results in more people being vulnerable to natural hazards floods than ever before. Pakistan is positioned within a hazard-prone region and is exposed to several kinds of natural disasters such as earthquakes, cyclones, landslides, droughts and floods but still it lacks proper disaster management policies. Floods in Pakistan bring a great destruction both in urban and rural areas. This paper focuses on some of the key benefits that may be achieved in presence of a proper disaster management framework or policies and also it proposes latest technologies to deal with hazards. This paper also demonstrates a simple concept that may be adopted and implemented immediately, that may help to minimize the impact economically, socially and environmentally.</p>

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“…Risk maps are powerful tools since they consider also the characteristics of exposed elements providing potential damage scenarios (Bignami et al 2018;Novellino et al 2021). In general terms, landslide risk is evaluated through a multi-step analysis including i) hazard identification, ii) hazard assessment, iii) inventory of elements at risk and exposure, iv) vulnerability assessment and v) risk estimation (Dai et al 2002;Glade et al 2006;van Westen et al 2008;Corominas et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Multi-temporal relative landslide risk analysis for sustainable development of rapidly growing cities

Napoli¹,

Miele²,

Guerriero³

et al. 2021

Preprint

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In the last decades, developing countries have experienced an increase in impact of natural disasters due to both the ongoing climate change and the sustained expansion of urban areas. Intrinsic vulnerability of settlements due to poverty and poor governance, as well as the lack of tools for urban occupation planning and mitigation protocols, have made such impact particularly severe. Cuenca (Ecuador) is a significant example of a city that in the last decades has experienced considerable population growth and an associated increasing of loss due to landslide occurrence. Despite such effects, updated urban planning tools are absent, a condition that suggested an evaluation of multi-temporal relative landslide risk, here presented based on updated data depicting the spatial distribution of landslides and their predisposing factors, as well as population change between 2010 and 2020. In addition, a multi-temporal analysis accounting for risk change between 2010 and 2020 has been carried out. Due to the absence of spatially distributed data about the population, electricity supply contract data have been used as a proxy of the population. Results indicate that current higher relative risk is estimated for municipalities (parroquias) located at the southern sector of the study area (i.e. Turi, Valle, Santa Ana, Tarqui and Paccha). Moreover, the multi-temporal analysis indicates that most municipalities of the city located in the hilly areas that bound the center (i.e. Sayausi, San Joaquin, Tarqui, Valle, Sidcay, Banos, Sidcay, Ricaurte, Paccha and Chiquintad), experiencing sustained population growth, will be exposed to an increased risk with a consistently growing trend. This information is consistent with landslide susceptibility data derived by a machine learning-based analysis that indicate higher susceptibility to landslides in hilly areas surrounding the city center. The obtained relative risk maps can be considered as a useful tool for guiding land-planning, occupation restriction and early warning strategy adoption. The used methodological approach, accounting for landslide susceptibility and population variation through proxy data analysis, has the potential to be applied in a similar context of growing-population cities of low to mid-income countries, where data, usually needed for a comprehensive landslide risk analysis, are only partly available.

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Assessing and Improving Flood and Landslide Community Social Awareness and Engagement via a Web Platform: The Case of Italy

Cited by 19 publications

References 18 publications

Assessing urban flood disaster risk using Bayesian network model and GIS applications

Assessing urban flood disaster risk using Bayesian network model and GIS applications

Disaster risk management: Focused to flood hazard and its impact in Pakistan

Multi-temporal relative landslide risk analysis for sustainable development of rapidly growing cities

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