1

Making International Collaboration

Work: A View from Brazil

Gilberto CâmaraDirector for Earth Observation

National Institute for Space Research (INPE)Brazil

Earth Observation Business NetworkVancouver, CA, May 2002

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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

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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

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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....)

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Government and Job Creation

Low-Tech High-Tech

Fixed Waiter Surgeon

Mobile Assembly-line worker

Aeronautics Engineer

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Assessing International Collaboration

Four Key Factors Strategy Societal Benefits Industrial Innovation Cost

Based on Porter’s Approach “Competitive Advantage of Nations”

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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?

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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

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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.

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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?”.

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EO-diamond: An example Hypothetical situation

Useful type of EO satellite Ground segment = Us$ 50 million (public

money)

0

0,5

1STRATEGY

COST

INDUSTRY

SOCIETY

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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

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

0

0,25

0,5

0,75

1STRATEGY

COST

INDUSTRY

SOCIETY

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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....)

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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

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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

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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)

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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

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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!

Landsat Image – Rondonia (Brazil)

Landsat Image – Rondonia (Brazil)

Landsat Image – Rondonia (Brazil)

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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?

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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?

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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”)

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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

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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.

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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”

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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

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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

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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

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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

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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?

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EO-diamond: CBERS Expected benefits of CBERS (2000-2010)

Strategy (1.0), Society (0.8), Cost (0.3), Industry (0.65)

0

0,5

1STRATEGY

COST

INDUSTRY

SOCIETY

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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

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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?

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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