Social perception of flood risk in maps – emotions or reality?

Časopis / Konference: 28th ICC, workshop Maps and Emotions (Washington DC, 1.-2. 7. 2017)
Autoři: Jan D. Bláha
Rok: 2017
Druh publikace: Příspěvek ve sborníku konference
Stránky, web: pouze abstrakt / only abstract
Klíčová slova: natural hazards, emotions, floods, mental maps, social perception
Odkaz na plnou verzi:
Abstrakt: Natural hazards still bring today’s society relatively high loss in property, unfortunately, sometimes even in health and life. Numerous physical-geographical surveys are dedicated to floods and flood risk issues, various detailed models and flood maps are created among others. On the contrary, the relatively small amount of research projects is devoted to the social perception of flood and flood risks, although a number of experts and municipality representatives realize that to cope with these events, people’s attitudes are crucial. Willingness of people to engage, cooperation between inhabitants and municipality representatives as well as social interest in natural hazards are important for effective solutions. The paper aims to present the results of research project supported by the Czech Science Foundation, which deals with social perception of flood risk and used mental maps of inhabitants as the significant methodological tool. During a questionnaire survey around 300 mental maps of inhabitants from two small Czech settlements were acquired. Both settlements have significant experiences with floods in recent years. Therefore, it could be assumed that the emotions experienced during flood events are still vivid. The respondents identified in the map, based on their subjective opinion, safe/dangerous locations and they located into the map a set of possible/implemented flood prevention measures they were familiar with. The approximate location of the respondent’s residence and its influence on the respondent’s perception of flood risks were monitored. The aggregation and the analysis of acquired data were managed in ArcGIS using Spatial Statistics Tools, similarly to our previous studies.
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