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Crowd4Sat: Crowdsourcing for Observations from Satellites

Thu, 02/21/2019 - 18:56
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University of Sheffield

The Crowd4Sat project explored a range of crowdsourcing methodologies and technologies, from opportunistic sourcing ­ the ability to extract relevant data from unrelated activities ­ to participatory sourcing, where citizens and authorities explicitly participate in the data collection. The crowdsourced data and information collected ranged from real time pollution data from cars (via the The Floow's technologies who have hundreds of thousands of users on four continents), to crowdsourced geotagged images from sites like Panoramio, Flicker and Twitter, to social media messages (e.g. from Facebook, Twitter, Foursquare, etc.). Observations from Satellites (OS) data was be sourced from a wide range of ESA missions and products including ERS/Envisat and Sentinel­ 1 and additional OS sources such as Landsat­8 and MODIS. A variety of stakeholders such as authorities, emergency responders, city councils, insurance companies, as well as single individuals and citizens associations have been involved throughout the process. The project addressed concrete scientific and societal problems through four use cases demonstration projects, targeted at key scientific and societal issues: pollution in metropolitan areas, land use, water management and snow coverage, and flood management and prevention.

A variety of activities were conducted throughout the project ­ conducting reviews of relevant initiatives, roadmapping activity, stakeholder analysis, requirements analysis, technology design and development, user evaluations and stakeholder feedback. These activities resulted in several findings, all of which have been documented in several reports and deliverables. This chapter summarises the findings and provides recommendations for ESA and the citizen science and crowdsourcing communities. The recommendations are in line with the ones identified by the roadmapping and state of the art activities of Work Package 1, with key findings from the demonstration projects. The following section provides a brief summary of the lessons learned in the demonstration projects.

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Generic Technologies
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