Value Analytics for Earth Observing Systems

Value-centric approaches for Earth Observation System (EOS) design and use have long been advocated in principle, but operationally remain rare in practice. Here, an integrative framework for quantifying value is presented that connects architecture and design, data processing, and data use. Examples in constellation design, calibration for data quality, and decision applications from remote sensing data demonstrate how the approach can be applied. Additionally, closed form analytical models are formulated to show how system design, operation, and data use variables connect with value metrics relevant for different stakeholders. The models presented here offer a basis for informing and negotiating choices by designers, operators, and users of emerging EOS.