Crowdsourcing and volunteered geographic information (VGI) collection by so called human sensors is an emerging field in GIScience and remote sensing to create reference data sets, to train models and to enrich automated mapping results. Crowdsourcing is distinguished in human sensor activities, which means VGI by everybody who wants to contribute, collective sensing, which is the information extraction of aggregated anonymised data (e.g. from web 2.0 content and social networks), and citizen science, which is the information collection by local experts and citizens. Most developments in this field rely on densely built-up areas i.e. cities and concentrate on mapping of infrastructures and buildings, though also distributed contributions (collaborative mapping, or remote sensing analysis by distributed experts) are increasingly common. There is a large potential making use of this new kind of participatory approach in the field of Geoscience e.g. to improve mapping and monitoring of natural environments, natural hazard consequences, and to better understand landscape dynamics.

This session searches for crowdsourcing studies tackling the following issues:
(i) Crowdsourcing in Geoscience such as natural environment mapping, geomorphology, landscape development and natural hazard management.
(ii) Crowdsourcing data quality in terms of coverage (spatial and temporal) and accuracy (spatial and semantic).
(iii) How to motivate participants with local knowledge (long term perspective) but also of temporary visitors (e.g. tourists) (short term perspective) to collect relevant data (e.g. using gaming approaches).
(iv) How to bridge the gap between crowdsourced data and automated mapping from remote sensing (data integration).