Participatory Mapping and Visualization of Local Knowledge: An Example from Eberbach, Germany

Abstract

A rise in the number of flood-affected people and areas has increased the interest in new methods and concepts that account for this change. Citizens are integrated into disaster risk reduction processes through participatory approaches and can provide valuable up-to-date local knowledge. During a field study in Eberbach (Baden–Wuerttemberg, Germany) sketch maps and questionnaires were used to capture local knowledge about flooding. Based on a previous study on urban flooding in Santiago de Chile, the tools were adapted and applied to river flooding in the city of Eberbach, which is regularly flooded by the Neckar River, a major river in southwest Germany. The empirical database of the study comprises 40 participants in the study area and 40 in a control area. Half of the participants in each group are residents and half are pedestrians. Purposive sampling was used, and the questionnaires aimed to gather demographic information and explore what factors, such as property, influence the risk perception of the study participants. The results show that residents identify a larger spatial area as at risk than pedestrians, and owning property leads to higher risk awareness. The flood type influenced the choice of the base maps for the sketch maps. For river flooding, one map with an overview of the area was sufficient, while for urban flooding a second map with more details of the area also enables the marking of small streets. The information gathered can complement authoritative data such as from flood models. This participatory approach also increases the communication and trust between local governments, researchers, and citizens.

Keywords

Disaster risk reduction / Flooding / Local knowledge / Participatory approach / Sketch maps / Volunteered geographic information

References

[1] Aerts JCJH, Botzen WJ, Clarke KC, Cutter SL, Hall JW, Merz B, Michel-Kerjan E, Mysiak J Integrating human behaviour dynamics into flood disaster risk assessment. Nature Climate Change, 2018, 8(3): 193-199

[2] Assumpção TH, Popescu I, Jonoski A, Solomatine DP. Citizen observations contributing to flood modelling: Opportunities and challenges. Hydrology and Earth System Sciences, 2018, 22(2): 1473-1489

[3] Birkmann J, von Teichman K. Integrating disaster risk reduction and climate change adaptation: Key challenges—scales, knowledge, and norms. Sustainability Science, 2010, 5(2): 171-184

[4] Botzen, W.J.W., J.C.J.H. Aerts, and J.C.J.M. van den Bergh. 2009. Dependence of flood risk perceptions on socioeconomic and objective risk factors. Water Resources Research 45(10): Article W10440.

[5] Bubeck P, Botzen WJW, Kreibich H, Aerts JCJH. Long-term development and effectiveness of private flood mitigation measures: An analysis for the German part of the river Rhine. Natural Hazards and Earth System Sciences, 2012, 12(11): 3507-3518

[6] Bustillos Ardaya, A., M. Evers, and L. Ribbe. 2019. Integrated participatory methodologies for disaster risk reduction: Tools to analyze complex systems through participatory processes in Brazil. In Strategies and tools for a sustainable rural Rio de Janeiro, ed. U. Nehren, S. Schlüter, C. Raedig, D. Sattler, and H. Hissa, 361–376. Berlin: Springer.

[7] Cheung W, Houston D, Schubert JE, Basolo V, Feldman D, Matthew R, Sanders BF, Karlin B Integrating resident digital sketch maps with expert knowledge to assess spatial knowledge of flood risk: A case study of participatory mapping in Newport Beach, California. Applied Geography, 2016, 74: 56-64

[8] Craglia M, Ostermann F, Spinsanti L. Digital earth from vision to practice: making sense of citizen-generated content. International Journal of Digital Earth, 2012, 5(5): 398-416

[9] Curtis JW, Shiau E, Lowery B, Sloane D, Hennigan K, Curtis A. The prospects and problems of integrating sketch maps with Geographic Information Systems to understand environmental perception: A case study of mapping youth fear in Los Angeles gang neighborhoods. Environment and Planning B: Planning and Design, 2014, 41(2): 251-271

[10] Dorn H, Vetter M, Höfle B. GIS-based roughness derivation for flood simulations: A comparison of orthophotos. LiDAR and crowdsourced geodata. Remote Sensing, 2014, 6(2): 1739-1759

[11] Eberbach. 2018a. Hochwasser/Wetter. http://www.eberbach.de/pb/,Lde/260581.html. Accessed 4 Apr 2018.

[12] Eberbach. 2018b. Zahlen/Daten/Fakten. http://www.eberbach.de/pb/,Lde/265205.html. Accessed 4 Apr 2018.

[13] Elwood S, Goodchild MF, Sui DZ. Researching volunteered geographic information: Spatial data, geographic research, and new social practice. Annals of the Association of American Geographers, 2012, 102(3): 571-590

[14] Ferster CJ, Coops NC. Assessing the quality of forest fuel loading data collected using public participation methods and smartphones. International Journal of Wildland Fire, 2014, 23(4): 585-590

[15] Gaillard JC, Mercer J. From knowledge to action: Bridging gaps in disaster risk reduction. Progress in Human Geography, 2013, 37(1): 93-114

[16] Goodchild MF. Citizens as sensors: The world of volunteered geography. GeoJournal, 2007, 69(4): 211-221

[17] Haworth, B.T., E. Bruce, J. Whittaker, and R. Read. 2018. The good, the bad, and the uncertain: Contributions of volunteered geographic information to community disaster resilience. Frontiers in Earth Science 6: Article 183.

[18] Haworth B, Whittaker J, Bruce E. Assessing the application and value of participatory mapping for community bushfire preparation. Applied Geography, 2016, 76: 115-127

[19] Hirsch Hadorn G, Hoffmann-Riem H, Biber-Klemm S, Grossenbacher-Mansuy W, Joye D, Pohl C, Wiesmann U, Zemp E. Handbook of transdisciplinary research, 2008, Bern: Springer

[20] Horita, F.E.A., L.C. Degrossi, L.F.F.G. Assis, A. Zipf, and J. Porto de Albuquerque. 2013. The use of volunteered geographic information and crowdsourcing in disaster management: A systematic literature review. In Proceedings of the Nineteenth Americas Conference on Information Systems, 15–17 August 2013, Chicago, Illinois, USA, 1–10.

[21] Klonner, C., and L. Blessing. 2019. Gathering local knowledge for disaster risk reduction: The use of sketch maps in group discussions. In Proceedings of the 16th International Conference on Information Systems for Crisis Response and Management, 19–22 May 2019, Valencia, Spain, 1397–1398.

[22] Klonner, C., S. Marx, T. Usón, and B. Höfle. 2016a. Risk awareness maps of urban flooding via OSM field papers—Case study Santiago de Chile. In Proceedings of the13th International Conference on Information Systems for Crisis Response and Management, 22–25 May 2016, Rio de Janeiro, Brasil, 1–14.

[23] Klonner, C., S. Marx, T. Usón, J. Porto de Albuquerque, and B. Höfle. 2016b. Volunteered geographic information in natural hazard analysis: A systematic literature review of current approaches with a focus on preparedness and mitigation. ISPRS International Journal of Geo-Information 5(7): Article 103.

[24] Klonner, C., T. Usón, S. Marx, F.-B. Mocnik, and B. Höfle. 2018. Capturing flood risk perception via sketch maps. ISPRS International Journal of Geo-Information 7(9): Article 359.

[25] Malterud K, Siersma VD, Guassora AD. Sample size in qualitative interview studies: Guided by information power. Qualitative Health Research, 2016, 26(13): 1753-1760

[26] Marana, P., L. Labaka, and J.M. Sarriegi. 2018. A framework for public-private-people partnerships in the city resilience-building process. Safety Science 110(Part C): 39–50.

[27] O’Neill E, Brennan M, Brereton F, Shahumyan H. Exploring a spatial statistical approach to quantify flood risk perception using cognitive maps. Natural Hazards, 2015, 76(3): 1573-1601

[28] Polanyi M. The tacit dimension, 1966, Chicago and London: University of Chicago Press

[29] Punch KF. Introduction to social research: Quantitative and qualitative approaches, 2014, London: Sage

[30] Reichel C, Frömming UU. Participatory mapping of local disaster risk reduction knowledge: An example from Switzerland. International Journal of Disaster Risk Science, 2014, 5(1): 41-54

[31] Seebauer S, Babcicky P. Trust and the communication of flood risks: Comparing the roles of local governments, volunteers in emergency services, and neighbours. Journal of Flood Risk Management, 2017, 11(3): 305-316

[32] Shi J, Visschers VHM, Siegrist M, Arvai J. Knowledge as a driver of public perceptions about climate change reassessed. Nature Climate Change, 2016, 6: 759-762

[33] Singh, D. 2011. The wave that eats people—The value of indigenous knowledge for disaster risk reduction. Geneva: United Nations Office for Disaster Risk Reduction. https://www.unisdr.org/archive/21236. Accessed 9 Dec 2019.

[34] Soden, R., N. Budhathoki, and L. Palen. 2014. Resilience-building and the crisis informatics agenda: Lessons learned from open cities Kathmandu. In Proceedings of the 11th International Conference on Information Systems for Crisis Response and Management, 18–21 May 2014, University Park, Pennsylvania, USA.

[35] UNDRR (United Nations Office for Disaster Risk Reduction). 2019a. Hyogo Framework for Action (HFA) and Sendai Framework for Disaster Risk Reduction. https://www.unisdr.org/we/coordinate. Accessed 23 Mar 2019.

[36] UNDRR (United Nations Office for Disaster Risk Reduction). 2019b. Terminology on disaster risk reduction. https://www.unisdr.org/we/inform/terminology. Accessed 8 Jan 2020.

[37] Usón TJ, Klonner C, Höfle B. Using participatory geographic approaches for urban flood risk in Santiago de Chile: Insights from a governance analysis. Environmental Science & Policy, 2016, 66: 62-72

[38] Wachinger G, Renn O, Begg C, Kuhlicke C. The risk perception paradox—Implications for governance and communication of natural hazards. Risk Analysis, 2013, 33(6): 1049-1065

[39] Wagner K. Mental models of flash floods and landslides. Risk Analysis, 2007, 27(3): 671-682

[40] Weinstein ND. Unrealistic optimism about future life events. Journal of Personality and Social Psychology, 1980, 39(5): 806-820

[41] Yumagulova L, Vertinsky I. Moving beyond engineering supremacy: Knowledge systems for urban resilience in Canada’s Metro Vancouver region. Environmental Science & Policy, 2019, 100: 66-73