Applying neighbourhood classification systems to natural hazards: a case study of Mt Vesuvius   总被引：1，自引：1，他引：0  

Iain Willis  Maurizio Gibin  Joana Barros  Richard Webber 《Natural Hazards》2014,70(1):1-22

Mt Vesuvius is regarded as one of the most deadly volcanoes on earth. With over 1 million people living on its flanks and in its periphery, there is little doubt that an eruption of sub-Plinian magnitude would be catastrophic to the livelihood and well being of contemporary Neopolitans. Such a large scale eruption would have wide ranging and differential effects on the surrounding population. Whereas previous studies of social vulnerability have focused on individual demographic factors (such as age, income or ethnicity), this research proposes the application of a general neighbourhood classification system to assess natural hazard vulnerability. In this study, Experian’s Mosaic Italy is used to classify and delineate the most vulnerable neighbourhood types around the province of Naples. Among the neighbourhoods considered most at risk, those areas with high proportions of elderly and low income families are deemed particularly vulnerable. With current evacuation plans deemed outdated and poorly communicated to the locals Rolandi (2010), Barberi et al. (2008), this methodology could prove to be a useful input to both town planners and civil protection agencies. A range of statistical measures and geophysical risk boundaries are employed here to assess the different areas of human resilience.  相似文献   

A BPR approach to hydrogeological risk management     

Maurizio Bevilacqua  Filippo Emanuele Ciarapica  Claudia Paciarotti 《Natural Hazards》2014,71(3):1995-2012

Every year, landslides and floods cause deaths, missing persons, injured people, evacuees, and homeless people. Serious damages to property and pollution are also produced. Lessons learn from landslides and flood disasters recently occurred show that flood and disaster management should be widely improved. This paper deals the problem of hydrogeological risk management from a logistic and a managerial point of view. The hydrological risk management is studied as an industrial process, and it is modeled by the IDEF0 language. The IDEF0 application provides a clear overview of the system and became a structured base for the re-engineering process. For each function of the process, the inputs, outputs, and necessary controls and resources have been identified. The use of the IDEF0 provides a simple and effective tool for the decision-making process. Starting from a realistic and efficient current state model, the process of re-engineering has been implemented. The main aim of the change introduced in the process is to improve the information management that it is a crucial point of the risk management.  相似文献   

Probabilistic GIS-based method for delineation of urban flooding risk hotspots   总被引：3，自引：1，他引：2  

Fatemeh Jalayer  Raffaele De Risi  Francesco De Paola  Maurizio Giugni  Gaetano Manfredi  Paolo Gasparini  Maria Elena Topa  Nebyou Yonas  Kumelachew Yeshitela  Alemu Nebebe  Gina Cavan  Sarah Lindley  Andreas Printz  Florian Renner 《Natural Hazards》2014,73(2):975-1001

Identifying urban flooding risk hotspots is one of the first steps in an integrated methodology for urban flood risk assessment and mitigation. This work employs three GIS-based frameworks for identifying urban flooding risk hotspots for residential buildings and urban corridors. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas and urban corridors [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. A maximum likelihood method (MLE) is employed for estimating the threshold used for identifying the flood-prone areas (the TWI threshold) based on the inundation profiles calculated for various return periods within a given spatial window. Furthermore, Bayesian parameter estimation is employed in order to estimate the TWI threshold based on inundation profiles calculated for more than one spatial window. For different statistics of the TWI threshold (e.g. MLE estimate, 16th percentile, 50th percentile), the map of the potentially flood-prone areas is overlaid with the map of urban morphology units, identified as residential and urban corridors, in order to delineate the urban hotspots for both UMT. Moreover, information related to population density is integrated by overlaying geo-spatial census datasets in order to estimate the number of people affected by flooding. Differences in exposure characteristics have been assessed for a range of different residential types. As a demonstration, urban flooding risk hotspots are delineated for different percentiles of the TWI value for the city of Addis Ababa, Ethiopia.  相似文献