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Making International Collaboration Work: A View from Brazil

This article explores the challenges and opportunities of international collaboration in Earth observation (EO) programs, focusing on the perspective of Brazil. It examines the key factors that contribute to successful collaboration, including strategy, societal benefits, industrial innovation, and cost. The article also highlights the need to improve the conversion of EO data into valuable information and proposes strategies to remove barriers to information use and foster innovation in the EO market.

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Making International Collaboration Work: A View from Brazil

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  1. Earth Observation Business Network Vancouver, CA, May 2002 Making International CollaborationWork: A View from Brazil Gilberto Câmara Director for Earth Observation National Institute for Space Research (INPE) Brazil

  2. Introduction • International co-operation • Key issue in civilian EO programmes • Major obstacle to success • “My Fair Lady” syndrome • How to improve? • Understanding each partner’s motivation • Proposal: framework with four critical factors

  3. Introduction • Brazilian Space Program • Basis for the position stated • Hope that rationale can be generalized • Relevant experience • LANDSAT data reception and use since 1974 • CBERS China-Brazil Earth Resources Satellite • RADARSAT reception and use

  4. Introduction • Position paper • Perspectives from a DSP (developing country with space program) • User and producer of EO data • Government perspective • “Public good” must prevail • “Best use” of citizen’s money • We support the high-tech industry • (our own, preferably....)

  5. Government and Job Creation

  6. Assessing International Collaboration • Four Key Factors • Strategy • Societal Benefits • Industrial Innovation • Cost • Based on Porter’s Approach • “Competitive Advantage of Nations”

  7. The Strategy Factor • Impact of the program in the nation-wide policymaking • When presidents meet, is the program in their agenda? • Is the program seen as influencing positively the commercial balance of trade? • Is the imagery provided capable of making a novel contribution to the management of country’s territory?

  8. The Industrial Innovation Factor • Impact of the program in fostering innovation in its high-technology sector • Governments • expect some form of spillover effect • reluctant to spend public funds in supporting high-tech jobs abroad • Requirement • Tangible compensation for the local high-technology industry

  9. The Societal Benefits Factor • “Public good” component of EO data • Assessment criteria • Proven applications that can be derived from satellite imagery • Data reliability • Data quality • Data continuity.

  10. The Cost Factor • Expected cost reduction by international collaboration • EO programs in DSP • High degree of government intervention. • Seen as R&D investment • Right question • Not “how much does the program cost?” • But “what fraction of a country’s R&D budget is being committed to the program?”.

  11. EO-diamond: An example • Hypothetical situation • Useful type of EO satellite • Ground segment = Us$ 50 million (public money)

  12. EO-diamond: LANDSAT • Societal benefits (0.95) • Helping Brazil manage its large territory • Cost (0.75) • US$ 60 million in 18 years • Acquisition of ground stations and satellite access fees • Strategy (0.6) • Foundation for the establishment of the Brazilian Earth Observation program • Changes in program status in the US administration • Industrial Innovation (0.3) • Development of Image Processing and GIS technology

  13. EO-diamond • Assessment of an EO-program • Benefits of LANDSAT Program to Brazil (1974-2002)

  14. Applying the EO-diagram • How Can International Collaboration Work in EO? • when all four decision-making factors (strategy, industry, society and cost) have properly been taken into account and each partner is satisfied that his objectives are met • (in practice....)

  15. Improving Societal Benefits • Perspective for increasing market returns • EO from a government-led program to a commercially-led one • Uncertainty in terms of market growth • perception about the limitations of the information content of the satellite data • “Knowledge gap” (MacDonald) • Data-to-information conversion

  16. Improving Societal Benefits • Removing barriers to information use • Some high-resolution imagery companies • Restrictions on data distribution • Aerial imagery companies • less restrictive dissemination policy • provide the data integrated into a GIS • Increasing EO market share • Requires changing commercial EO practices

  17. Improving Societal Benefits • “Knowledge gap” from EO data • Result of market segmentation • Satellite operators == data providers, • Image processing software companies == systems for information extraction • Market comparison • Spatial information systems = $1.08 billion (1999) • ESRI, leading GIS = US$340 million (1999) • ERDAS, leading IP = US$23.5 million (2000)

  18. Improving Societal Benefits • “Deadlock” situation • Small size of commercial IP • Not enough income for R&D investment • Improvements on information extraction • Needed for the market to grow • Knowledge extraction procedures • very litlle technological innovation • limited academic research in EO-GIS integration

  19. Improving Societal Benefits • Most applications of EO data • “Snapshot” paradigm • Recipe analogy • Take 1 image (“raw”) • “Cook” the image (correction + interpretation) • All “salt” (i.e., ancillary data) • Serve while hot (on a “GIS plate”) • But we have lots of images!

  20. Landsat Image – Rondonia (Brazil)

  21. Landsat Image – Rondonia (Brazil)

  22. Landsat Image – Rondonia (Brazil)

  23. Improving Societal Benefits • What’s in an Image? • Is an image a field of energy received by a sensor? • Are images instruments for capturing landscape dynamics?

  24. Improving Societal Benefits • In search of a “killer-app” • How many cutting-edge applications exist for extracting information in large image databases? • How much R&D is being invested in spatial data mining in large repositories of EO data? • How do we put our image databases to more effective use?

  25. Improving Societal Benefits • Breaking the “deadlock” in knowledge extraction for EO data • Partnerships between data providers and IP software companies • Government-funded research programmes • Co-operative development environments (“the Linux of EO”)

  26. Improving Societal Benefits • International co-operation • Co-operative research programmes • Emphasis on complete cycle of information processing • Research, applications, and technological developments • “Knowledge gap” is tough to remove • Requires a lot of talented researchers • Incompressible amount of time

  27. Improving Industrial Innovation • EO industrial components • Commodity-based • Critical technologies • Commodity-based segment • Solar panels, on-board computers, ground stations, launching services • Worldwide market • Russia, India, China, Ukraine and Brazil are potential suppliers.

  28. Improving Industrial Innovation • Commodity-based market • Still heavily regulated • Reduced competitiveness • Increased cost • International co-operation • Confidence building • Developing countries becoming major suppliers • “Balanced mutual dependence”

  29. Improving Industrial Innovation • Critical technologies • Guidance systems, high-quality optics and electronics, fault-tolerant computing • Technology transfer is very restricted • Countries with EO programs • Cannot affort critical dependence • International co-operation • Step-by-step confidence building • Long-term agreements for reducing tensions

  30. Improving Strategy • Key factor • Diplomatic and economic relations • EO development partnerships • No longer limited to G-7 countries • China-Brasil agreement • High-technology development can happen outside of the G-7 world

  31. Improving Strategy • Current Situation • Many alternatives for EO collaboration • Negotiations between G-7 and DSP countries • DSP countries no longer simply a market for EO data • DSP countries • More demanding in technology transfer • Access to G-7 markets

  32. Improving Cost • Least independent component of the “EO-diamond” • Theory • Co-operation can reduce cost of EO programs • Practice • Relative distortions = preferred allocation to country’s own industry

  33. Improving Cost • Can we achieve productivity gains from scale effects? • Requires co-operation at a global scale • Process of industry consolidation • Each major component of a EO mission • available from a small number of industries • Unlikely situation?

  34. EO-diamond: CBERS • Expected benefits of CBERS (2000-2010) • Strategy (1.0), Society (0.8), Cost (0.3), Industry (0.65)

  35. Co-operation at a Global Scale • “How many EO satellites does the world need?” • Utopian, not superfluous question • Increase scale effects and cost reduction • Avoid duplication in missions • Enhance complementarity

  36. Co-operation at a Global Scale • “How many EO satellites does the world need?” • Example from meteorological community • Coordination Group for Meteorological Satellites (CGMS) • Five geostationary satellites (2 US, 1 EU, 1 Russia, 1 Japan) + China + India • Could CEOS play a similar rôle?

  37. Co-operation at a Global Scale • Utopia or Possible Realization? • Imperfect, Regulated Market • “Invisible hands” are tied • Need for an international consensus • Requires positive climate for international relations • May take time, but we’ll get there.... • EOBN is an important part of such positive build-up

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