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Abstract
The mapping of the damage caused by natural disasters is a crucial step in deciding on the actions to take at the international, national, and local levels. The large variety of representations that we have observed leads to problems of transfer and variations in analysis. In this article, we propose a representation, Regular Dot map (RD), and we compare it to 4 others routinely used to visualise post-disaster damage. Our comparison is based on a user study in which a set of participants carried out various tasks on multiple datasets using the various visualisations. We then analysed the behaviour during the experiment using three approaches: (1) quantitative analysis of user answers according to the reality on the ground, (2) quantitative analysis of user preferences in terms of perceived effectiveness and appearance, and (3) qualitative analysis of the data collected using an eye tracker. The results of this study lead us to believe that RD is the best compromise in terms of effectiveness among the various representations studied.
Correction Statement
This article has been republished with minor changes. These changes do not impact the academic content of the article.
Acknowledgements
The authors thank the IUT de Montpellier-Sète for providing the eye-tracking device and software used in the experiment. The authors also thank Catherine Trottier, statistician at IMAG - Université de Montpellier and AMIS - Université Paul-Valéry Montpellier 3, for her advice on the statistical analysis of the results, and the Master 2 GCRN class of 2019–2020 at the Université Paul-Valéry Montpellier 3 for their participation in this experiment. Finally, the authors thank RisCrises for providing support and ‘guinea pigs’ for the calibration of the experiment.
Ethical approval
All procedures performed in this study involving human participants were in accordance with the ethical standards of the institution and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The research has been conducted in an ethical and responsible manner. The protocol was clearly presented to the participants as well as the scientific publication purpose. The participants were voluntary and gave their consent. The tasks performed by the participants were anonymous and no personal data were collected during the study. The research ethics committee of the university Paul-Valéry Montpellier 3 was not yet in place at the time of the experiment. It started functioning after the data collection (September 2020).
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data and codes availability statement
The data that support the findings of this study are openly available in figshare - Code_and_data at 10.6084/m9.figshare.14724879.
Notes
1 https://disasterscharter.org/web/guest/home (accessed on April 13, 2021)
2 https://www.copernicus.eu/en (accessed on April 13, 2021)
3 In the sense of the observations and rules governing the rational design of graphics. In this context, semiology integrates the natural structure and the properties of visual perception into the construction of a graphics, namely through a set of visual variables (position, colour, value, size, grain, orientation, shape).
4 https://sertit.unistra.fr/en/ (accessed on March 02, 2021)
5 https://www.dlr.de/eoc/en/ (accessed on March 02, 2021)
6 https://colorbrewer2.org/#type=sequential&scheme=OrRd&n=3 (accessed on March 02, 2021)
7 After our observation of decisionmakers in the field, we did not find any examples of the use of this type of visualisation.
8 https://sertit.unistra.fr/ (accessed on May 11,2020)
9 The accuracy distributions measured for each task and for the response time are not considered a priori to be Gaussian, and can also be exponential or gamma for the continuous case and binomial or Poisson for the discrete case. Therefore, we use statistical models based on the Generalised Linear Model (GLM) in order to identify the significant differences between the visualisation techniques (glm function in R). This model is similar to ANOVA but takes the various distributions into account. For the tasks of the T1 type, we use the Gaussian family (normal distribution) that seems to be the most suitable. We will see below that this is not the case for the tasks of the T2 type and the time.
10 Like above, we use a model of the GLM type to identify the significant differences between the visualisation techniques for the tasks of the T2 type. However, since the responses of the participants are dichotomous here (either correct or wrong), we use the binomial family.
11 We first used a GLM model with the gamma family (exponential distribution). Then, we introduced a random effect on the participants in order to take into account the information that the same individual carries out each of the tasks (glmer function in R). This allows the correlation between 2 answers from the same individual to be modelled. For each task, we observed a decrease in the AIC between the two approaches (which was not the case for the analysis of accuracy), which allowed us to select the second model. For example, for task T1.1, the AIC decreased from 1019 to 990 when adding the random effect.
12 The Web Mercator coordinate system, also known as Spherical Mercator and Pseudo-Mercator, is a standard used for web mapping (Google, Bing, etc.) and online services (Géoportail, ArcGIS Online).
13 https://worldismap.com/dommages-irma/ (accessed on April 15, 2021)
14 https://emergency.copernicus.eu/mapping/list-of-components/EMSR317 (accessed on May 14, 2020)
15 https://emergency.copernicus.eu/mapping/list-of-components/EMSR246 (accessed on May 14, 2020)
16 https://emergency.copernicus.eu/mapping/list-of-components/EMSR232 (accessed on May 14, 2020)
17 https://unitar.org/sustainable-development-goals/satellite-analysis-and-applied-research (accessed on May 14, 2020)
Additional information
Funding
Notes on contributors
Thomas Candela
Thomas Candela is a PhD at Paul-Valéry Université de Montpellier and LAGAM (Laboratory of Geography and Territorial Planning in Montpellier). He is also Research and Development Manager at RisCrises SARL, Alès, France. His research interests include the development of cartographic and geovisualisation tools for the analysis of vulnerabilities and consequences of natural hazards at the national and international levels.
Matthieu Péroche
Matthieu Péroche is an Assistant Professor at the Paul-Valéry Université de Montpellier and researcher at LAGAM (Laboratory of Geography and Territorial Planning in Montpellier). His research focuses on the use of spatial information to help in the management of natural risks and disasters.
Arnaud Sallaberry
Arnaud Sallaberry is an Assistant Professor at the Paul-Valéry Université de Montpellier. He is the head of the applied mathematics and computer science research team (AMIS). He is also a member of the data mining and visualisation research team (ADVANSE) of the Laboratory of Computer Science, Robotics and Microelectronics of Montpellier (LIRMM). His research interests include information visualisation and visual analytics.
Nancy Rodriguez
Nancy Rodriguez is an Assistant Professor at the Université de Montpellier and researcher at LIRMM (Laboratory of Computer Science, Robotics and Microelectronics of Montpellier) at the ADVANSE team. Her research interests include virtual and augmented/mixed reality, interaction, accessibility and visualisation.
Christian Lavergne
Christian Lavergne is a Professor at Paul-Valéry Université de Montpellier with the applied mathematics and computer science research team (AMIS). He is also a member of the probability and statistics research team (EPS) at the Alexander Grothendieck Institute of Montpellier (IMAG). He conducts research in statistics and data science.
Frédéric Leone
Frédéric Leone is a Professor at Paul-Valéry Université de Montpellier. He is the head of the Laboratory of Geography and Territorial Planning in Montpellier (LAGAM). His research focuses on the spatial reconstruction of natural disasters and the integrated assessment of associated risks.