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Augmenting Satellite Observations with Crowdsourcing

Suvodeep Mazumdar, Stuart Wrigley and Fabio Ciravegna

(Submission #295)


Over the last few decades, satellites have taken a primary role in a large amount of our daily activities. Billions of users across the globe consult weather services, navigation applications, send and receive data, share information online via satellites. Satellite Observations and applications are hence, embedded into the daily fabric of modern life with a large number of application areas such as agriculture, forestry and land monitoring, emergency response to defence and security and natural resource management. The impact of Crowdsourcing and citizen science activities on academia, businesses, governance and society has been enormous. This is more prevalent today with citizens and communities collaborating with organisations, businesses and authorities to contribute in a variety of manner, starting from mere data providers to being key stakeholders in various decision-making processes. The ‘Crowdsourcing for observations from Satellites’ project is a recently concluded study supported by demonstration projects funded by European Space Agency (ESA). The objective of the project was to investigate the different facets of how crowdsourcing and citizen science impacts upon the validation, use and enhancement of Observations from Satellites (OS) products and services. This talk will present the final results of the project from two perspectives: the first being an analysis of the current citizen science and crowdsourcing initiatives, stakeholders, trends and the challenges and opportunities for sustained citizen engagement. The second area is aimed at understanding how crowdsourcing can address key societal and scientific problems via four demonstration projects. The first project exploited participatory sensing from hiker groups via mobile applications and integrated the resulting data with satellite observations to improve the precision of snow coverage in the Spanish Pyrenees Mountains. The second project collected large volumes of opportunistic sensing data from vehicle movement via mobile applications, integrating with remote sensing data for developing improved vehicular pollution models. The third project integrated opportunistic crowdsourced data from social media with satellite observations to improve quality and timeliness of flood emergency mapping. The final project integrated participatory and opportunitistic sensing with land cover data and satellite observations to improve the accuracy and timeliness of land cover for water management. The four demonstration projects involved different type of crowdsourcing in a variety of contexts and hence as a result, some with greater success than others. In this talk, we will present our findings and lessons learned from the project.


Topic Area:  [2.7] Citizen science/crowd sourcing
Abstract Type:  Oral Presentation

Additional fields

Comments:   Crowdsourcing, Satellite Observations, Earth Observations

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