Earth observation is diversifying, and now includes new types of systems, such as citizen observatories, unmanned aerial vehicles and wireless sensor networks. However, the Copernicus Programme vision of a seamless chain from satellite data to usable information in the hands of decision makers is still largely unrealized, and remote sensing science lacks a conceptual framework to explain why. This paper reviews the literatures on citizen science, citizen observatories and conceptualization of remote sensing systems. It then proposes a Conceptual Framework for Earth Observation which can be used in a new Earth observation science to explain blockages in the chain from collecting data to disseminating information in any Earth observation system, including remote sensing systems. The framework differs from its predecessors by including social variables as well as technological and natural ones. It is used here, with evidence from successful citizen science projects, to compare the factors that are likely to influence the effectiveness of satellite remote sensing systems and citizen observatories. The paper finds that constraints on achieving the seamless “Copernicus Chain” are not solely technical, as assumed in the new Space Strategy for Europe, but include social constraints too. Achieving the Copernicus Chain will depend on the balance between: (a) the ‘forward’ momentum generated by the repetitive functioning of each component in the system, as a result of automatic operation or human institutions, and by the efficiency of interfaces between components; and (b) the ‘backward’ flow of information on the information needs of end users. Citizen observatories will face challenges in components which for satellite remote sensing systems are: (a) automatic or straightforward, e.g., sensor design and launch, data collection, and data products; and (b) also challenging, e.g., data processing. Since citizen observatories will rely even more on human institutions than remote sensing systems to achieve repetitive functioning, one of their greatest strengths—using a “crowd” of hand-held sensors to cover large areas—could also be one of their greatest weaknesses.
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