Spatial data infrastructures, which are Internet-based mechanisms for the coordinated production, discovery, and use of geospatial information in the digital environment, have diffused worldwide in the last two decades. Currently, there are about one hundred spatial data infrastructures at the national level and many other at supra-and sub-national levels. These contemporary spatial data infrastructures operate with two main assumptions: formal organizations are the producers and suppliers of geospatial information; users are the passive recipients of information. The recent phenomenon of volunteered geographic information departs from these assumptions. In this paper, we argue that reconceptualizing the user of a spatial data infrastructure can accommodate this new phenomenon. Such a reconceptualization creates a middle ground between spatial data infrastructure and volunteered geographic information, which has important implications for future research.

This article presents an examination of motivational factors relating to contribution to the wiki OpenStreetMap, a site for voluntary geographic information. Based on a wide literature review of motivation, open source, volunteerism, and serious leisure, a questionnaire was created and completed by 444 OpenStreetMap contributors. Results of judgments of the motivational importance of 39 reasons for contribution are presented and considered in relation to models of contributory behavior for crowd- and community-based online collaborations. Positive and important motivators were found that accorded with ideas of the “personal but shared need” associated with contribution to open-source projects, co-orientation to open-source and geographic knowledge, and attention to participation in and by the community. Differences in motivation between serious and casual mappers showed that serious mappers were more oriented to community, learning, local knowledge, and career motivations (although the latter motivation is low in general), and casual mappers were more oriented to general principles of free availability of mapping data.

While unprecedented amounts of building damage data are now produced after earthquakes, stakeholders do not have a systematic method to synthesize and evaluate damage information, thus leaving many datasets unused. We propose a Geospatial Data Integration Framework (G-DIF) that employs regression kriging to combine a sparse sample of accurate field surveys with spatially exhaustive, though uncertain, damage data from forecasts or remote sensing. The framework can be implemented after an earthquake to produce a spatially distributed estimate of damage and, importantly, its uncertainty. An example application with real data collected after the 2015 Nepal earthquake illustrates how regression kriging can combine a diversity of datasets—and downweight uninformative sources—reflecting its ability to accommodate context-specific variations in data type and quality. Through a sensitivity analysis on the number of field surveys, we demonstrate that with only a few surveys, this method can provide more accurate results than a standard engineering forecast.

Critical knowledge gaps seriously hinder efforts for building disaster resilience at all levels, especially in disaster-prone least developed countries. Information deficiency is most serious at local levels, especially in terms of spatial information on risk, resources, and capacities of communities. To tackle this challenge, we develop a general methodological approach that integrates community-based participatory mapping processes, one that has been widely used by governments and non-government organizations in the fields of natural resources management, disaster risk reduction and rural development, with emerging collaborative digital mapping techniques. We demonstrate the value and potential of this integrated participatory and collaborative mapping approach by conducting a pilot study in the flood-prone lower Karnali river basin in Western Nepal. The process engaged a wide range of stakeholders and non-stakeholder citizens to co-produce locally relevant geographic information on resources, capacities, and flood risks of selected communities. The new digital community maps are richer in content, more accurate, and easier to update and share than those produced by conventional Vulnerability and Capacity Assessments (VCAs), a variant of Participatory Rural Appraisal (PRA), that is widely used by various government and non-government organizations. We discuss how this integrated mapping approach may provide an effective link between coordinating and implementing local disaster risk reduction and resilience building interventions to designing and informing regional development plans, as well as its limitations in terms of technological barrier, map ownership, and empowerment potential.

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