Articles | Volume 23, issue 7
https://doi.org/10.5194/nhess-23-2505-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-23-2505-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Criteria-based visualization design for hazard maps
Max Schneider
CORRESPONDING AUTHOR
Section 2.6: Seismic Hazard and Risk Dynamics, German Research Centre for Geosciences, Potsdam, Germany
Fabrice Cotton
Section 2.6: Seismic Hazard and Risk Dynamics, German Research Centre for Geosciences, Potsdam, Germany
University of Potsdam, Potsdam, Germany
Pia-Johanna Schweizer
Research Institute for Sustainability, Helmholtz Centre Potsdam, Potsdam, Germany
Related authors
No articles found.
Kai Schröter, Pia-Johanna Schweizer, Benedikt Gräler, Lydia Cumiskey, Sukaina Bharwani, Janne Parviainen, Chahan M. Kropf, Viktor Wattin Håkansson, Martin Drews, Tracy Irvine, Clarissa Dondi, Heiko Apel, Jana Löhrlein, Stefan Hochrainer-Stigler, Stefano Bagli, Levente Huszti, Christopher Genillard, Silvia Unguendoli, Fred Hattermann, and Max Steinhausen
Nat. Hazards Earth Syst. Sci., 25, 3055–3073, https://doi.org/10.5194/nhess-25-3055-2025, https://doi.org/10.5194/nhess-25-3055-2025, 2025
Short summary
Short summary
With the increasing negative impacts of extreme weather events globally, it is crucial to align efforts to manage disasters with measures to adapt to climate change. We identify challenges in systems and organizations working together. We suggest that collaboration across various fields is essential and propose an approach to improve collaboration, including a framework for better stakeholder engagement and an open-source data system that helps gather and connect important information.
Timothy Tiggeloven, Colin Raymond, Marleen C. de Ruiter, Jana Sillmann, Annegret H. Thieken, Sophie L. Buijs, Roxana Ciurean, Emma Cordier, Julia M. Crummy, Lydia Cumiskey, Kelley De Polt, Melanie Duncan, Davide M. Ferrario, Wiebke S. Jäger, Elco E. Koks, Nicole van Maanen, Heather J. Murdock, Jaroslav Mysiak, Sadhana Nirandjan, Benjamin Poschlod, Peter Priesmeier, Nivedita Sairam, Pia-Johanna Schweizer, Tristian R. Stolte, Marie-Luise Zenker, James E. Daniell, Alexander Fekete, Christian M. Geiß, Marc J. C. van den Homberg, Sirkku K. Juhola, Christian Kuhlicke, Karen Lebek, Robert Šakić Trogrlić, Stefan Schneiderbauer, Silvia Torresan, Cees J. van Westen, Judith N. Claassen, Bijan Khazai, Virginia Murray, Julius Schlumberger, and Philip J. Ward
EGUsphere, https://doi.org/10.5194/egusphere-2025-2771, https://doi.org/10.5194/egusphere-2025-2771, 2025
This preprint is open for discussion and under review for Geoscience Communication (GC).
Short summary
Short summary
Natural hazards like floods, earthquakes, and landslides are often interconnected which may create bigger problems than when they occur alone. We studied expert discussions from an international conference to understand how scientists and policymakers can better prepare for these multi-hazards and use new technologies to protect its communities while contributing to dialogues about future international agreements beyond the Sendai Framework and supporting global sustainability goals.
Graeme Weatherill, Fabrice Cotton, Guillaume Daniel, Irmela Zentner, Pablo Iturrieta, and Christian Bosse
Nat. Hazards Earth Syst. Sci., 24, 3755–3787, https://doi.org/10.5194/nhess-24-3755-2024, https://doi.org/10.5194/nhess-24-3755-2024, 2024
Short summary
Short summary
New generations of seismic hazard models are developed with sophisticated approaches to quantify uncertainties in our knowledge of earthquake processes. To understand why and how recent state-of-the-art seismic hazard models for France, Germany, and Europe differ despite similar underlying assumptions, we present a systematic approach to investigate model-to-model differences and to quantify and visualise them while accounting for their respective uncertainties.
Laurentiu Danciu, Domenico Giardini, Graeme Weatherill, Roberto Basili, Shyam Nandan, Andrea Rovida, Céline Beauval, Pierre-Yves Bard, Marco Pagani, Celso G. Reyes, Karin Sesetyan, Susana Vilanova, Fabrice Cotton, and Stefan Wiemer
Nat. Hazards Earth Syst. Sci., 24, 3049–3073, https://doi.org/10.5194/nhess-24-3049-2024, https://doi.org/10.5194/nhess-24-3049-2024, 2024
Short summary
Short summary
The 2020 European Seismic Hazard Model (ESHM20) is the latest seismic hazard assessment update for the Euro-Mediterranean region. This state-of-the-art model delivers a broad range of hazard results, including hazard curves, maps, and uniform hazard spectra. ESHM20 provides two hazard maps as informative references in the next update of the European Seismic Design Code (CEN EC8), and it also provides a key input to the first earthquake risk model for Europe.
Graeme Weatherill, Sreeram Reddy Kotha, Laurentiu Danciu, Susana Vilanova, and Fabrice Cotton
Nat. Hazards Earth Syst. Sci., 24, 1795–1834, https://doi.org/10.5194/nhess-24-1795-2024, https://doi.org/10.5194/nhess-24-1795-2024, 2024
Short summary
Short summary
The ground motion models (GMMs) selected for the 2020 European Seismic Hazard Model (ESHM20) and their uncertainties require adaptation to different tectonic environments. Using insights from new data, local experts and developments in the scientific literature, we further calibrate the ESHM20 GMM logic tree to capture previously unmodelled regional variation. We also propose a new scaled-backbone logic tree for application to Europe's subduction zones and the Vrancea deep seismic source.
Karina Loviknes, Fabrice Cotton, and Graeme Weatherill
Nat. Hazards Earth Syst. Sci., 24, 1223–1247, https://doi.org/10.5194/nhess-24-1223-2024, https://doi.org/10.5194/nhess-24-1223-2024, 2024
Short summary
Short summary
Earthquake ground shaking can be strongly affected by local geology and is often amplified by soft sediments. In this study, we introduce a global geomorphological model for sediment thickness as a protentional parameter for predicting this site amplification. The results show that including geology and geomorphology in site-amplification predictions adds important value and that global or regional models for sediment thickness from fields beyond engineering seismology are worth considering.
Dino Bindi, Riccardo Zaccarelli, Angelo Strollo, Domenico Di Giacomo, Andres Heinloo, Peter Evans, Fabrice Cotton, and Frederik Tilmann
Earth Syst. Sci. Data, 16, 1733–1745, https://doi.org/10.5194/essd-16-1733-2024, https://doi.org/10.5194/essd-16-1733-2024, 2024
Short summary
Short summary
The size of an earthquake is often described by a single number called the magnitude. Among the possible magnitude scales, the seismic moment (Mw) and the radiated energy (Me) scales are based on physical parameters describing the rupture process. Since these two magnitude scales provide complementary information that can be used for seismic hazard assessment and for seismic risk mitigation, we complement the Mw catalog disseminated by the GEOFON Data Centre with Me values.
Irina Dallo, Michèle Marti, Nadja Valenzuela, Helen Crowley, Jamal Dabbeek, Laurentiu Danciu, Simone Zaugg, Fabrice Cotton, Domenico Giardini, Rui Pinho, John F. Schneider, Céline Beauval, António A. Correia, Olga-Joan Ktenidou, Päivi Mäntyniemi, Marco Pagani, Vitor Silva, Graeme Weatherill, and Stefan Wiemer
Nat. Hazards Earth Syst. Sci., 24, 291–307, https://doi.org/10.5194/nhess-24-291-2024, https://doi.org/10.5194/nhess-24-291-2024, 2024
Short summary
Short summary
For the release of cross-country harmonised hazard and risk models, a communication strategy co-defined by the model developers and communication experts is needed. The strategy should consist of a communication concept, user testing, expert feedback mechanisms, and the establishment of a network with outreach specialists. Here we present our approach for the release of the European Seismic Hazard Model and European Seismic Risk Model and provide practical recommendations for similar efforts.
Juan Camilo Gómez Zapata, Massimiliano Pittore, Nils Brinckmann, Juan Lizarazo-Marriaga, Sergio Medina, Nicola Tarque, and Fabrice Cotton
Nat. Hazards Earth Syst. Sci., 23, 2203–2228, https://doi.org/10.5194/nhess-23-2203-2023, https://doi.org/10.5194/nhess-23-2203-2023, 2023
Short summary
Short summary
To investigate cumulative damage on extended building portfolios, we propose an alternative and modular method to probabilistically integrate sets of single-hazard vulnerability models that are being constantly developed by experts from various research fields to be used within a multi-risk context. We demonstrate its application by assessing the economic losses expected for the residential building stock of Lima, Peru, a megacity commonly exposed to consecutive earthquake and tsunami scenarios.
Audrey Bonnelye, Pierre Dick, Marco Bohnhoff, Fabrice Cotton, Rüdiger Giese, Jan Henninges, Damien Jougnot, Grzegorz Kwiatek, and Stefan Lüth
Adv. Geosci., 58, 177–188, https://doi.org/10.5194/adgeo-58-177-2023, https://doi.org/10.5194/adgeo-58-177-2023, 2023
Short summary
Short summary
The overall objective of the CHENILLE project is to performed an in-situ experiment in the Underground Reaserch Laboratory of Tournemire (Southern France) consisting of hydraulic and thermal stimulation of a fault zone. This experiment is monitored with extensive geophysical means (passive seismic, active seismic, distributed fiber optics for temperature measurements) in order to unravel the physical processes taking place during the stimulation for a better charactization of fault zones.
Juan Camilo Gomez-Zapata, Nils Brinckmann, Sven Harig, Raquel Zafrir, Massimiliano Pittore, Fabrice Cotton, and Andrey Babeyko
Nat. Hazards Earth Syst. Sci., 21, 3599–3628, https://doi.org/10.5194/nhess-21-3599-2021, https://doi.org/10.5194/nhess-21-3599-2021, 2021
Short summary
Short summary
We present variable-resolution boundaries based on central Voronoi tessellations (CVTs) to spatially aggregate building exposure models and physical vulnerability assessment. Their geo-cell sizes are inversely proportional to underlying distributions that account for the combination between hazard intensities and exposure proxies. We explore their efficiency and associated uncertainties in risk–loss estimations and mapping from decoupled scenario-based earthquakes and tsunamis in Lima, Peru.
Cited articles
Armstrong, M. P., Xiao, N., and Bennett, D. A.:
Using genetic algorithms to create multicriteria class intervals for choropleth maps, Annals of the Association of American Geographers, 93, 595–623, 2003. a
Baker, J., Bradley, B., and Stafford, P.: Seismic hazard and risk analysis,
Cambridge University Press, https://doi.org/10.1017/9781108425056, 2021. a
Birch, J.:
Worldwide prevalence of red-green color deficiency, JOSA A, 29, 313–320, 2012. a
Bivand, R., Ono, H., Dunlap, R., and Stigler, M.:
Package “classint”, 2020. a
Brychtovam, A. and Çöltekin, A.:
An empirical user study for measuring the influence of colour
distance and font size in map reading using eye tracking, The Carto. J., 53, 202–212,
2016. a
Cantarino, I., Carrion, M. A., Goerlich, F., and Martinez Ibañez, V.:
A ROC analysis-based classification method for landslide
susceptibility maps, Landslides, 16, 265–282, 2019. a
Chan, A. H. S., Han, S. H., and Nanthavanij, S.:
Color associations for Hong Kong Chinese, Korean, and Thai-A
comparison, in: Proceedings of IEA 14th Triennial Congress, Seoul Korea,
2003. a
Clarke, T. and Costall, A.:
The emotional connotations of color: A qualitative investigation, Color Res. Appli., 33, 406–410, 2008. a
Çöltekin, A., Brychtová, A., Griffin, A. L.,
Robinson, A. C., Imhof, M., and Pettit, C.:
Perceptual complexity of soil-landscape maps: a user evaluation of
color organization in legend designs using eye tracking, Int. J. Dig. Earth, 10, 560–581, 2017. a
Dasgupta, A., Poco, J., Rogowitz, B., Han, K., Bertini, E.,
and Silva, C. T.:
The effect of color scales on climate scientists' objective and
subjective performance in spatial data analysis tasks, IEEE T. Vis. Comput. Gr., https://doi.org/10.1109/TVCG.2018.2876539,
2018. a, b
Dobson, M. W.:
Choropleth maps without class intervals?: a comment,
Geograph. Anal., 5, 358–360,
1973. a
Doore, G. S., Eustis, A. C., Jones, D., Leep, R., Lincoln, J., MacDonald, Al. E., Mandics, P. A., Ryan, R. T., Schiavone, J. A. (chair), and Schiessl, D.:
Guidelines for using color to depict meteorological information, B. Am. Meteor. Soc., 74, 1709–1713, 1993. a
Edler, D., Keil, J., Tuller, M.-C., Bestgen, A.-K., and
Dickmann, F.:
Searching for the “right” legend: The impact of legend position
on legend decoding in a cartographic memory task, The Carto. J., 57, 6–17,
2020. a
Fisher, W. D.:
On grouping for maximum homogeneity, J. Am. Stat. Assoc., 53, 789–798, 1958. a
GFZ: Helmholtz-Zentrum Potsdam GFZ,
D-eqhaz16, https://www-app5.gfz-potsdam.de/d-eqhaz16/index.html (last access: 1 August 2022),
Plattform zur Abfrage von gefährdungskonsistenten Antwortspektren
(UHS) für beliebige Punkte in Deutschland sowie von nationalen
Erdbebengefährdungskarten nach dem Berechnungsmodell von Grünthal et al.
(2018), 2023. a
Griffith, L. J. and Leonard, S. D.:
Association of colors with warning signal words,
Int. J. Ind. Ergonom., 20, 317–325, 1997. a
Harrower, M. and Brewer, C. A.:
Colorbrewer.org: an online tool for selecting colour schemes for
maps, The Carto. J., 40, 27–37,
2003. a
Horton, S., Nowak, S., and Haegeli, P.: Enhancing the operational value of snowpack models with visualization design principles, Nat. Hazards Earth Syst. Sci., 20, 1557–1572, https://doi.org/10.5194/nhess-20-1557-2020, 2020. a
Itten, J.:
The art of color the subjective experience and objective rationale of
color, ISBN-13 978-0471289289,
1961. a
Jenks, G. F.:
The data model concept in statistical mapping, Int. Yearbook Carto., 7, 186–190,
1967. a
Jiang, B., Liu, X., and Jia, T.:
Scaling of geographic space as a universal rule for map
generalization, Ann. Assoc. Am. Geogr.,
103, 844–855, 2013. a
Kennedy, S.:
Unclassed choropleth maps revisited/some guidelines for the
construction of unclassed and classed choropleth maps, Cartographica: The Int. J. Geogr.
Info. Geovisualiz., 31, 16–25, 1994. a
Kindlmann, G., Reinhard, E., and Creem, S.:
Face-based luminance matching for perceptual colormap generation, in: IEEE Visualization, 2002, VIS 2002., 299–306, IEEE,
2002. a
Kinkeldey, C., MacEachren, A. M., Riveiro, M., and Schiewe, J.:
Evaluating the effect of visually represented geodata uncertainty on
decision-making: systematic review, lessons learned, and recommendations, Cartogr. Geogr. Inf. Sci., 44, 1–21, 2017. a
Li, Z. and Qin, Z.:
Spacing and alignment rules for effective legend design, Cartogr. Geogr. Inf. Sci., 41, 348–362, 2014. a
Light, A. and Bartlein, P. J.:
The end of the rainbow? Color schemes for improved data graphics, Eos, Transactions American Geophysical Union, 85, 385–391, 2004. a
Lin, S., Fortuna, J., Kulkarni, C., Stone, M., and Heer, J.:
Selecting semantically-resonant colors for data visualization, in: Computer Graphics Forum, Vol. 32, 401–410, Wiley
Online Library, 2013. a
MacAdam, D. L.:
Visual sensitivities to color differences in daylight, Josa, 32, 247–274, 1942. a
MacDonald, L. W.:
Using color effectively in computer graphics, IEEE Compu. Graph. Appl., 19, 20–35, 1999. a
MacPherson-Krutsky, C. C., Brand, B. D., and Lindell, M. K.:
Does updating natural hazard maps to reflect best practices increase
viewer comprehension of risk?, Int. J. Dis. Risk Reduc., 46, 101487, https://doi.org/10.1016/j.ijdrr.2020.101487, 2020. a
Maxwell, B. A.:
Visualizing geographic classifications using color, The Carto. J., 37, 93–99,
2000. a
Mehta, R. and Zhu, R. J.:
Blue or red? exploring the effect of color on cognitive task
performances, Science, 323, 1226–1229, 2009. a
Meyer, V., Kuhlicke, C., Luther, J., Fuchs, S., Priest, S., Dorner, W., Serrhini, K., Pardoe, J., McCarthy, S., Seidel, J., Palka, G., Unnerstall, H., Viavattene, C., and Scheuer, S.: Recommendations for the user-specific enhancement of flood maps, Nat. Hazards Earth Syst. Sci., 12, 1701–1716, https://doi.org/10.5194/nhess-12-1701-2012, 2012. a, b
Miller, G. A.:
The magical number seven, plus or minus two: Some limits on our
capacity for processing information,
Psychol. Rev., 63, 81, 1956. a
Muller, J.-C.:
Perception of continuously shaded maps, Ann. Assoc. Am. Geogr., 69, 240–249, 1979. a
Olson, J. M. and Brewer, C. A.:
An evaluation of color selections to accommodate map users with
color-vision impairments,
Ann. Assoc. Am. Geogr., 87, 103–134, 1997. a
Or, C. K. L. and Wang, H. H. L.:
Color–concept associations: A cross-occupational and-cultural study
and comparison, Color Res. Appl., 39, 630–635, 2014. a
OSFHome: Seismic hazard mapping, OSFHome [data set, code], https://osf.io/puerc/?view_only=2b747decfbfb4093a9e925e5fe09cd48 (last access: 1 August 2022), 2020. a
Padilla, L., Quinan, P. S., Meyer, M., and Creem-Regehr, S. H.:
Evaluating the impact of binning 2d scalar fields, IEEE T. Vis. Comput. Gr.,
23, 431–440, 2016. a
Pratt, J. W.: Remarks on zeros and ties in the Wilcoxon signed rank procedures, J. Am. Stat. Assoc., 54.287, 655–667, 1959. a
Quinan, P. S. and Meyer, M.:
Visually comparing weather features in forecasts, IEEE T. Vis. Comput. Gr.,
22, 389–398, 2015. a
Reda, K., Nalawade, P., and Ansah-Koi, K.:
Graphical perception of continuous quantitative maps: the effects of
spatial frequency and colormap design, in: Proceedings of the 2018 CHI Conference on Human Factors in
Computing Systems, https://doi.org/10.1145/3173574.3173846, 1–12, 2018. a
Rheingans, P. L.:
Task-based color scale design, in: 28th AIPR Workshop: 3D Visualization for Data Exploration
and Decision Making, Vol. 3905, 35–43, International Society for
Optics and Photonics, https://doi.org/10.1117/12.384882, 2000. a
Robertson, P. K. and O'Callaghan, J. F.:
The generation of color sequences for univariate and bivariate
mapping IEEE Comput. Gr. Appl., 6, 24–32, 1986. a
Rogowitz, B. E., Kalvin, A. D., Pelah, A., and Cohen, A.:
Which trajectories through which perceptually uniform color spaces
produce appropriate colors scales for interval data?, in: Color and Imaging Conference, Vol. 1999, 321–326,
Society for Imaging Science and Technology, https://doi.org/10.2352/CIC.1999.7.1.art00062, 1999. a
Schloss, K. B., Gramazio, C. C., Silverman, A. T., Parker, M. L., and
Wang, A. S.:
Mapping color to meaning in colormap data visualizations, IEEE T. Vis. Comput. Gr.,
25, 810–819, 2018. a
Schneider, M., McDowell, M., Guttorp, P., Steel, E. A., and Fleischhut, N.: Effective uncertainty visualization for aftershock forecast maps, Nat. Hazards Earth Syst. Sci., 22, 1499–1518, https://doi.org/10.5194/nhess-22-1499-2022, 2022. a
Sherman-Morris, K., Antonelli, K. B., and Williams, C. C.:
Measuring the effectiveness of the graphical communication of
hurricane storm surge threat,
Weather Clim. Soc., 7, 69–82, 2015. a
Spence, I., Kutlesa, N., and Rose, D. L.:
Using color to code quantity in spatial displays,
J. Ex. Psychol. Appl., 5, 393, 1999. a
Stauffer, R., Mayr, G. J., Dabernig, M., and Zeileis, A.:
Somewhere over the rainbow: How to make effective use of colors in
meteorological visualizations, B. Am. Meteorol. Soc., 96, 203–216, 2015. a
Thompson, M. A., Lindsay, J. M., and Leonard, G. S.:
More than meets the eye: Volcanic hazard map design and visual
communication, in: Observing the Volcano World, 621–640, Springer, ISBN 978-3-319-44095-8, 2017. a
Tingting, W., Siyun, S., and Lei, M.:
Blue or red? the effects of colour on the emotions of Chinese
people, Asian J. Soc. Psychol., 17, 152–158, 2014. a
Tobler, W. R.:
Choropleth maps without class intervals?, Geogr. Anal., 5, 262–265,
1973. a
Tyagunov, S., Grünthal, G., Wahlström, R., Stempniewski, L., and Zschau, J.: Seismic risk mapping for Germany, Nat. Hazards Earth Syst. Sci., 6, 573–586, https://doi.org/10.5194/nhess-6-573-2006, 2006. a
Zhou, L. and Hansen, C. D.:
A survey of colormaps in visualization, IEEE T. Vis. Comput. Gr.,
22, 2051–2069, 2015. a
Short summary
Hazard maps are fundamental to earthquake risk reduction, but research is missing on how to design them. We review the visualization literature to identify evidence-based criteria for color and classification schemes for hazard maps. We implement these for the German seismic hazard map, focusing on communicating four properties of seismic hazard. Our evaluation finds that the redesigned map successfully communicates seismic hazard in Germany, improving on the baseline map for two key properties.
Hazard maps are fundamental to earthquake risk reduction, but research is missing on how to...
Altmetrics
Final-revised paper
Preprint