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Integrating multiple information sources for landslide hazard assessment: the case of Italy

Landslides are the most frequent and diffuse natural hazards in Italy causing the greatest number of fatalities and damage to urban areas. The integration of natural hazard information and social media data could improve warning systems to enhance the awareness of disaster managers and citizens abou...

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Autores principales: Franceschini, Rachele, Rosi, Ascanio, del Soldato, Matteo, Catani, Filippo, Casagli, Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9715727/
https://www.ncbi.nlm.nih.gov/pubmed/36456578
http://dx.doi.org/10.1038/s41598-022-23577-z
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author Franceschini, Rachele
Rosi, Ascanio
del Soldato, Matteo
Catani, Filippo
Casagli, Nicola
author_facet Franceschini, Rachele
Rosi, Ascanio
del Soldato, Matteo
Catani, Filippo
Casagli, Nicola
author_sort Franceschini, Rachele
collection PubMed
description Landslides are the most frequent and diffuse natural hazards in Italy causing the greatest number of fatalities and damage to urban areas. The integration of natural hazard information and social media data could improve warning systems to enhance the awareness of disaster managers and citizens about emergency events. The news about landslide events in newspapers or crowdsourcing platforms allows fast observation, surveying and classification. Currently, few studies have been produced on the combination of social media data and traditional sensors. This gap indicates that it is unclear how their integration can effectively provide emergency managers with appropriate knowledge. In this work, rainfall, human lives, and earmarked fund data sources were correlated to “landslide news”. Analysis was applied to obtain information about temporal (2010–2019) and spatial (regional and warning hydrological zone scale) distribution. The temporal distribution of the data shows a continuous increase from 2015 until 2019 for both landslide and rainfall events. The number of people involved and the amount of earmarked funds do not exhibit any clear trend. The spatial distribution displays good correlation between “landslide news”, traditional sensors (e.g., pluviometers) and possible effects in term of fatalities. In addition, the cost of soil protection, in monetary terms, indicates the effects of events.
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spelling pubmed-97157272022-12-03 Integrating multiple information sources for landslide hazard assessment: the case of Italy Franceschini, Rachele Rosi, Ascanio del Soldato, Matteo Catani, Filippo Casagli, Nicola Sci Rep Article Landslides are the most frequent and diffuse natural hazards in Italy causing the greatest number of fatalities and damage to urban areas. The integration of natural hazard information and social media data could improve warning systems to enhance the awareness of disaster managers and citizens about emergency events. The news about landslide events in newspapers or crowdsourcing platforms allows fast observation, surveying and classification. Currently, few studies have been produced on the combination of social media data and traditional sensors. This gap indicates that it is unclear how their integration can effectively provide emergency managers with appropriate knowledge. In this work, rainfall, human lives, and earmarked fund data sources were correlated to “landslide news”. Analysis was applied to obtain information about temporal (2010–2019) and spatial (regional and warning hydrological zone scale) distribution. The temporal distribution of the data shows a continuous increase from 2015 until 2019 for both landslide and rainfall events. The number of people involved and the amount of earmarked funds do not exhibit any clear trend. The spatial distribution displays good correlation between “landslide news”, traditional sensors (e.g., pluviometers) and possible effects in term of fatalities. In addition, the cost of soil protection, in monetary terms, indicates the effects of events. Nature Publishing Group UK 2022-12-01 /pmc/articles/PMC9715727/ /pubmed/36456578 http://dx.doi.org/10.1038/s41598-022-23577-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Franceschini, Rachele
Rosi, Ascanio
del Soldato, Matteo
Catani, Filippo
Casagli, Nicola
Integrating multiple information sources for landslide hazard assessment: the case of Italy
title Integrating multiple information sources for landslide hazard assessment: the case of Italy
title_full Integrating multiple information sources for landslide hazard assessment: the case of Italy
title_fullStr Integrating multiple information sources for landslide hazard assessment: the case of Italy
title_full_unstemmed Integrating multiple information sources for landslide hazard assessment: the case of Italy
title_short Integrating multiple information sources for landslide hazard assessment: the case of Italy
title_sort integrating multiple information sources for landslide hazard assessment: the case of italy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9715727/
https://www.ncbi.nlm.nih.gov/pubmed/36456578
http://dx.doi.org/10.1038/s41598-022-23577-z
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