Abstract

The increased ease for individuals to create, share and map geographic information combined with the need for timely, relevant and diverse information has resulted in a new disaster management context. Volunteered geographic information (VGI), or geographic information voluntarily created by private citizens enabled through technologies like social media and web-based mapping, has changed the ways people create and use information for crisis events. Research has focussed on disaster response while largely ignoring prevention and preparedness. Preparing for disasters can reduce negative impacts on life and property, but despite strategies to educate communities, preparation remains low. This study assesses the application and value of VGI in bushfire risk reduction through a participatory mapping approach. It examines VGI as a social practice and not simply a data source by considering the user experience of contributing VGI and the potential for these activities to increase community connectedness for building disaster resilience. Participatory mapping workshops were held in bushfire-risk communities in Tasmania. Workshop activities included a paper-mapping exercise and web-based digital mapping. Survey results from 31 participants at three workshops indicated the process of mapping and contributing local information for bushfire preparation with other community members can contribute to increased social connectedness, understanding of local bushfire risk, and engagement in risk reduction. Local knowledge exchange was seen as valuable, but the social dimension appeared even more engaging than the specific information shared. Participants reported collaborative maps as effective for collating and sharing community bushfire information with a preference for digital mapping. Some limitations of online sharing of information were also reported by participants, however, including potential issues of privacy, data quality and source trustworthiness. Further work is needed to extrapolate findings from the study sample to the broader population.

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