APPRENDRE DU PASSE POUR OPTIMISER LA PREVENTION ET LA GESTION DES INONDATIONS SUR LE FERROVIAIRE

International audienceArchives records dealing with historical floods constitute a remarkable heritage for railway system analysis, but they are under-exploited. This article deals with their interest. Then a methodology to build a chronological synthesis from historical records is presented. Finally, the advantages of geovisualisation, as a tool to ease the exploitation of historical information, are presented.Les archives sur les inondations historiques constituent un patrimoine riche pour l'analyse du système ferroviaire, mais actuellement sous-exploité. Nous expliquons ce qu'elles peuvent apporter, puis nous présentons une méthode de synthèse des données issues d'archives. Enfin, nous présentons les apports de la géovisualisation, comme outil pour faciliter l'utilisation de l'information historique

L'étude des inondations historiques majeures et leurs impacts: Un enjeu pour l'avenir du système ferroviaire

National audienc

Representation and Visualization of Imperfect Geohistorical Data About Natural Risks: A Qualitative Classification and Its Experimental Assessment

International audienceImperfections, often called ‘uncertainties’, exist in almost every spatio-temporal dataset, especially in historical data. They are of different types (unreliability, inaccuracy…) and concern every data dimension (space, time and theme). Based on previous work, this article proposes a synthesis qualitative classification of imperfection types. This classification has been assessed with domain experts (hydrologists, geophysicians and GIScientists working in a railway company) during an experiment, that gave positive results towards the use of this classification. Participants were also asked to evaluate the seriousness of each imperfection type in an analysis context. This evaluation has allowed to associate a quantitative index to each imperfection type and to visualize a quantity of imperfection attached to each spatial object in a map

User testing of dynamic geovisualizations: lessons learned and possible improvements for cartographic experiments

International audienc

Mapping the narratives of natural disasters and their domino effects. The case study of floods impacting railways

International audienc

Impacts des inondations historiques sur un réseau de transport : exemple des installations et des circulations ferroviaires en France

PosterFor the past two centuries, floods have led to serious damage on the railway network and its operation. Taking into consideration extreme floods in conception, maintenance, risk management for railway infrastructures is one of the current issues of the SNCF. SNCF archives about historical data related to flood events which have impacted the railway network are abundant but scattered around the country and unexploited. Gathering those data about floods and damages on railway in France caused by extreme flooding phenomenon is essential for the evaluation and better understanding of the risk. Indeed, this analysis of flood risks would enable its anticipation by setting up an appropriate surveillance, but also to manage the risk on the rail traffic, during and after the event, and finally to improve the network operation. Moreover, a space-time representation of data would present a consistent and chronological vision of events and would enable to determine socio-economic impact of those extreme events. The aim of the collaboration between SNCF and the SARDO SNCF, the BDHI team, IRSTEA, the LIG and ACHTYS Diffusion is on one hand to set up a methodology of flood data identification and assessment that can be found on the SCNF archives and, on the other hand, to develop an innovative work tool for space-time visualisation of historical events. That would enable to enlarge the floods consequences analysis from railway infrastructures damages to socio-economic impacts induced by transport network stakes. This tool will enable to optimize railway maintenance and railway traffic management costs according to the risks, in order to optimize the network operation

IDISFER, an Ontology to Model Extreme Floods-Related Processes

International audienceExtreme floods occur in large territories and may cause significant damages to the railway system. As they are relatively rare, historical information about extreme floods is often not well known and used, whereas it could provide insights about: areas where the infrastructure is the most vulnerable, the resilience of the components of the railway system, and the financial and social impacts of extreme events. This paper deals with a framework to study historical extreme floods that can be used to model the flood processes impacting the railway system: IDISFER ontology. Ontologies are a flexible and interoperable data storage format, that is computer-readable and which can effectively process data. IDISFER includes all the relationships identified in the literature between natural flood phenomena and incidents on the railway system, causality relationships between several successive incidents (known as the 'domino effect') and chronological relationships between actions on the infrastructure and operations that are necessary to return the system to normal