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

ABSTRACT

Studying past at-risk phenomena is useful to prepare against future risks. Thanks to maps, it is possible to locate historical events in their spatial context. Animation and interactivity support the analysis of the dynamics of events. This paper deals with a visual method to represent narratives of past natural risk events in a map. It is based on the case study of past floods, which impacted the railway network. Map visualizations were developed with experts of the railway system, to overcome two main challenges: to visualize punctual events which have occurred at the same place over time and to display causality relationships between events in order to show domino effects. Proposals were evaluated during a user study. It showed that the combination between an animated map and a synthesis map helped users to carry out different tasks. It also showed that the combination between a map and a timeline, in a geovisualization interface, increased the efficiency of the exploration of flood narratives.

RÉSUMÉ

Etudier les phénomènes risqués qui ont eu lieu dans le passé est utile pour se préparer aux risques futurs. Grâce aux cartes, il est possible de localiser les évènements historiques dans leur contexte spatial. L’animation et l’interactivité facilitent l’analyse de la dynamique de ces évènements. Ce papier propose une méthode visuelle pour représenter sur une carte des récits d’évènements de risques naturels passés. Elle est basée sur l’analyse de cas d’inondations qui ont impacté des réseaux ferroviaires. La visualisation cartographique a été conçue avec des experts de système ferroviaire pour surmonter deux principaux défis : visualiser des évènements ponctuels qui ont eu lieu au même endroit au cours du temps et montrer les relations de causalité entre évènements afin de montrer les effets dominos. Les propositions ont été évaluées auprès d’utilisateurs. Le test montre que la combinaison entre carte animée et carte synthétique aide les utilisateurs pour réaliser les différentes tâches demandées. Il montre également que la combinaison entre une carte et une ligne temporelle dans l’interface de géovisualisation augmente l’efficacité de l’exploration des récits d’inondation.

KEYWORDS:

• Natural risks
• narrative map
• historical data
• geovisualization

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Cecile Saint-Marc is a PhD student in GIScience. Her topics of research concern geovisualization, the representation of domino effects and cognitive aspects of map reading.

Marlène Villanova-Oliver is an Assistant Professor in the Université Grenoble-Alpes. She is a member of Grenoble Informatics Lab (LIG) since 1998, where she carries out research on models, methods and tools for improving acquisition, modelling, querying, reasoning and visualizing Spatial and Temporal Information.

Paule-Annick Davoine is a Full Professor in Université Grenoble-Alpes. She recently joined the Alpine Geographic Institute of Grenoble. She supervises PhD students in the fields of cartography of spatio-temporal phenomena, social network data analysis and mobility analysis. Her research often base on concrete use cases, in partnership with industrials or thematic experts, in multidisciplinary contexts.

Cicely Pams Capoccioni is an engineer in Hydrology and the manager of a team in SNCF, the French company of railways. She is involved in many innovative projects and she supervises several PhD students in cooperation with Universities.

Dorine Chenier is an engineer in Hydrology in SNCF, the French company of railways. Among other topics, she works on the damages of water-related hazards on earthworks. She takes part in research projects related to hydrology management near the railways.

ORCID

Cécile Saint-Marc http://orcid.org/0000-0002-0062-6885

Notes

1 Source: http://www.nola.com/katrina/index.ssf/2015/08/katrina_flooding_map.html.

2 Source: https://atlascineproject.wordpress.com/.

3 Demo: http://google-maps-utility-library-v3.googlecode.com/svn/tags/markerclusterer/1.0/examples/simple_example.html.

4 Demo: https://github.com/jawj/OverlappingMarkerSpiderfier-Leaflet.