Providing Earth Observation Data from Space: Economics and Institutions
Burgeoning interest in understanding global environmental change has greatly increased demand for remote sensing of the earth from space.1 Over 60 percent of a $1 billion U.S. budget to study global change during fiscal year 1991 was allocated to space-based environmental data collection, including down payment on a $52 billion space data program, the Earth Observing System (EOS), planned for the next 15 years. This substantial expenditure, together with the huge technological scale of EOS (it will consist of large orbital platforms each carrying a multitude of sensors), have promoted considerable debate and alternative proposals for smaller-scale, modular spacecraft each carrying one or a few sensors. Proponents of the alternatives hold that the smaller-scale approach, in addition to being less expensive, foregoes few scale economies and avoids the eggs-in-one-basket risk of EOS, in which failure in launching a spacecraft or failure of one instrument on a multi-instrument spacecraft causes failure of the whole system. Advocates of EOS are concerned that the small-scale approach not only fails to exploit scale economies but may yield much lower information content, claiming that significant economies of scope are obtainable in operating and taking measurements from sensors aggregated on large spacecraft. In this paper we first ask whether scale and scope economies appear substantial enough, and risk small enough, to justify the large-scale approach presently envisioned.2 We then ask two separate but related questions about the organization of the project, namely whether these supply attributes require the technology to be an almost exclusively governmental activity. A dearth of information about remote sensing economics forces our approach to the production technology to be heuristic rather than empirical. Subject to this constraint, we fail to find evidence of significant scale and scope effects in large spacecraft and sensor manufacturing and launch, even after taking account of risk differentials among largerscale and smaller-scale systems (the former tDiscussants: Arthur DeVany, University of California-Irvine; Nancy Rose, MIT; James Dearden, Lehigh University.
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