From chains to platforms: valuing remote sensing
data for environmental management
Case of oceanography and hydrology
Marie Le Pellec-Dairon
PREG-CRG Ecole Polytechnique
Paris, France
marie.lepellec@polytechnique.edu Abstract — Remote sensing systems contribute to the
understanding, management and protection of the environment. Their global and continuous products can improve monitoring and prediction capabilities of numerous environmental processes such as climate change, depletion of natural resources, natural disasters, etc. Even though earth observations from satellite, combined with in situ data, are critical for an ever-increasing number of applications related to well-being of society [1], most national space agencies are facing budgetary restraints on earth observation programs that raise doubt about future programs management [2]. This paper suggests a new approach for future programs selection and management, based on a broaden valuation method and stakeholders involvement. This approach will be validated with an on going study on oceanography and hydrology systems.
Keywords- earth observation program; environmental management; value of information; environmental economics; concept valuation; platforms; stakeholders.
I. INTRODUCTION
Although several reports (see, for example [1] and [2]) stressed the need for new investments in earth observing systems, the actual situation suggests a decline of instruments in space, for both American and European agencies. In a time of budget constraints, justification of investments and efficient management of space programs are required to maintain earth observations from satellites and face the environmental and climate challenge.
For some space applications, such as telecommunication, markets, end users and proven cost benefits are quite easy to identify. Selection and management of such satellite programs can be based on this information. However, it is difficult to manage earth-observing systems in the same way, mainly because they involve societal and environmental issues such as society well being that are sovereign functions carried out by States.
One of the major obstacles is the difficulty to demonstrate benefits, since environmental management benefits cannot be reduced to an economic point of view. Positive externalities, such as biodiversity conservation, water
preservation, must be taken into account, as they are valuable societal outcomes on a very large time scale. Thus, it is necessary to broaden the notion of value in order to implement new programs selection and management strategies.
In addition to the valuation work carried out in the early stage of the mission, that provides the mission potential value, efforts should be made on the achievement of that value once the mission has started. A good understanding of the stakeholders concerned with the mission products and a suitable organization of the ecosystem is crucial to make the data known and used by the community.
Traditionally, literature on remote sensing data value focuses on weather forecast valuation for agricultural production [3]. More recently, a few studies assessed the value of remote sensing data for environmental management issues [4]. Most of those studies are focusing on the value of additional information for a given application to assess the benefits of earth observing systems. Those methods and results can be used to assess the potential value at an early stage of the mission and be a management instrument to follow the fulfillment of the value throughout the mission life. Furthermore, highlighting the value can raise interest of the concerned stakeholders and help in increasing the final value of the mission.
In the course of the study, the notion of stakeholders network appeared to be critical for the success of a mission. If the concept of value chain has often been put forward to represent mission’s participants, it seems that stakeholders are actually organized has a platform, where the value-added roles of each stakeholder within the network is essential. Remote sensing observations, in situ data, models, have to be combined to transform a raw data in useful information for end users. As a consequence, the platform organization is an important part of the mission management that has to be considered from the very beginning of the mission. Platform and network theories are a valuable literature for earth observing system management.
Study on management strategy for Earth observation management mission illustrates a more general issue: the
ex-ante valuation and management challenge regarding emerging concepts. The French Spatial Agency (CNES, Centre National d’Etudes Spatiales) is an attractive case study because of (1) the wide range of heterogeneous stakeholders, (2) the very long time scale of space missions and (3) its central role in Earth observation in Europe and worldwide.
This article is divided in six sections. In the next section, the methodology of the on going study is developed. The section 3 is devoted to an analysis of the value issue, including environmental economics and value of information theories, to propose a new mission valuation tool. Section 4 focuses on the achievement of the potential value by rethinking stakeholders organization as a platform. First results of the study are presented in Section 5 and Section 6 is dedicated to the conclusion.
II. METHODS
A. Conceptual framework
A new approach for Earth observation mission selection and management could involve two steps: First, the total environmental potential value of a mission has to be made explicit. Second, the stakeholders network has to be explored, completed and organized in a efficient platform, in order to achieve the potential value. We believe that this distinction between value estimation on one side, and its realization on the other should constitute a fundamental pillar in the design of alternative management system for Earth observation missions dedicated to environmental issues.
B. The empirical approach
This study has been conducted as an embedded (or multiple units of analysis) single-case study [5]. In the context of Earth observation, the French space agency, CNES has been chosen as a single-case in which two embedded units of analysis has been selected: oceanography and hydrology domains with the Jason and SWOT (Surface Water and Ocean Topography) missions. The chosen design is illustrated in Fig. 1.
The choice of these two subunits has been based on their complementarity. Whereas the oceanography is now considered as a successful operational domain with more than twenty years background, the SWOT mission should be launched in 2019. The CNES/NASA Jason satellite, following on the TOPEX/Poseidon mission, is the subject of an a posteriori study aiming at understanding triggering factors of its success. It will be examined on two points of view: environmental value and stakeholders organization evolution at different stages of the mission.
The SWOT mission, as it is at an early stage of development, will allow a follow-up of value and stakeholders involvement during an on going process.
Figure 1. Study design inspired from basic types of designs for case studies (Yin, 2009 [5])
C. Data collection
This study is based on several reports from CNES, ESA, NASA and organizations interested in space fields such as OECD. Several interviews have been conducted with CNES agents involved in the two domains, as well as with stakeholders: CLS, Mercator Ocean and Météo France for instance.
D. Description of case studies
1) TOPEX/Poseidon and Jason: Ocean altimetry provides measurements on sea surface height. This ocean data is being used to map sea surface height, geostrophic velocity, significant wave height, and wind speed over the global oceans [6]. Data and images are available in near real-time for some uses. They are used for a wide range of scientific as well as commercial and practical applications: climate research and forecasting, hurricane forecasting and tracking, ocean forecasting systems, ship routine and marine operation, marine mammal habitat monitoring, education, etc.
Ocean topography from space using radar altimeters was conceived in the 1960s. The U.S. Navy first used radar altimetry for operational needs in 1985. Then, several missions were launched by the European Space Agency (ESA), where radar altimeters were sharing platforms with other sensors, and thus a constrained orbit not optimal for studies of ocean topography (ERS-1 and 2, ENVISAT). The first dedicated mission was TOPEX/Poseidon, a joint NASA-CNES program, launched in 1992 [7]. Jason 1 has followed in 2001, with the comparable performance on a platform which weight had been divided by 5 (500kg). NOAA (National Oceanic and Atmospheric Administration) and EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) have taken the lead for operational responsibility for the next mission Jason 2. These satellites launching have been managed so as to allow overlaps and continuity on altimetry data (fig. 2).
Figure 2. TOPEX/Poseidon and Jason constellation roadmap Lastly, the Jason 3 mission should be launched in 2013, entirely funded by NOAA and EUMETSAT, the two operational agencies.
2) SWOT: The Surface Water and Ocean Topography mission is being developed jointly by a collaborative effort of the international oceanographic and hydrological SPACE-BASED EARTH OBSERVATION
CNES Oceanography
TOPEX/Poseidon Jason
Oceanography/Hydrology
SWOT (Surface Water and Ocean Topography)
TOPEX/Poseidon
Jason 1
communities for making high-resolution measurement of water elevation for both oceans and land surface water, in order to answer the questions about the oceanic submesoscale processes and the storage and discharge of land surface water [8]. NASA and CNES joined their efforts to propose a satellite able to completely cover the world's oceans and freshwater bodies with repeated elevation measurements.
That information should extend the success of ocean altimeters to inland and coastal waters and would provide a basis for directly measuring the storage of water in lakes, reservoirs, and wetlands globally [1]. It will provide valuable data for water management, flood forecasting, sea level, marine operations, etc.
The CNES-NASA cooperation led to a first agreement on feasibility studies regarding the SWOT mission, signed by NASA and CNES in 2009. It is actually in a A phase status: It includes exchanges of staff, ground validation activities, and scientific campaigns, including airborne campaigns (with the AirSwoT instrument) [39]. SWOT is anticipated to be launched in 2019.
III. BROADEN VALUE FOR ENVIRONMENTAL MISSIONS Missions are evaluated under specific criteria. The French space agency, CNES, establishes its criteria on economic, political, technical and societal points of view. The contract between CNES and the French government highlights priority missions to be carried out, to which values can be associated, listed in Table 1.
Those values become technical, political and economical criteria in the selection instrument. However, the environmental value hardly fit into the model, because of (1) its difficult economic valuation and (2) its long-term time scale. Earth observation systems could suffer from this method, in which environmental and societal benefits are not enough considered. Whereas environmental assessment studies have been carried out on several earth observation missions such as MetOp and SWOT, they focus on direct use value of the environment, which is the short-term part of the its value.
TABLE I. PRIORITY MISSIONS AND ASSOCIATED VALUES FOR CNES
A possible solution to complement this approach is to evaluate and select future projects considering their total potential value, including environmental and societal point of view. An enlarged sense of “valuation” should include the notion of total economic value suggested by environmental economics. Then, the assessment is based on the hypothesis that remote sensing data are a source of useful information for environmental decision makers, as it has been done for meteorological data. The aggregation of different values – economic, environmental, societal, technical and political – allows a better assessment of Earth observation systems, securing practical benefits for mankind.
This section proposes to address the problem of assessment of satellite data with a two-step methodology. The first step is to assess the value of environmental goods for which space missions provide useful information. How to allocate an economic value to the world's forests and water resources conservation? This first problem requires considering the specificities of environmental goods and analyzing how to aggregate the different environmental values identified. It will be treated in section A.
However, the value of the environmental good, for which the remote sensing data provides information, must not be confused with the mission value itself. For instance, it is not because a satellite data provides information about improving climate change models that its value is the climate management value. Then, the second step is to identify methods to move from environmental goods value to mission value. Value of information theories, presented in section B, provide some answers on this point.
Then, a new selection and management tool, based on disclosure of total potential value, can be proposed to adapt missions’ management strategy related to environmental fields.
A. Environmental goods valuation
Environmental benefits generated – or costs avoided – thanks to Earth observation missions can not always be measured on a market: we usually describe it as positive or
negative externality. The air quality and biodiversity are examples of environmental goods that are not traded on a market. They have no price but they have value. It is therefore necessary to assign a monetary value on these externalities in order to provide a common basis for comparison. It allows projects ranking and selection on a global value. In 1986, Thompson [9] already described the need to integrate the notion of value to the field of environment:
“One consequence of lack of greater competence in environmental values and ethics is that environmental problems traditionally are analyzed in separate fact-value terms.”
1) Environmental management specificity: The usual short-term point of view lead to a focus on direct use value
Priority missions (from
CNES-French government contract) Associated values
Time scale
Support industrial development
and competitiveness Job creation, turnover Short term Long term Support communities of excellence Global recognition of areas of excellence (altimetry), international partnerships, offsets Support the foreign policy of
France
Implement innovative satellite solutions in the areas of environmental monitoring and
climate
Optimization of environmental resources and their
future use Management of public policies
National and international decision
of environmental assets, which value is the price defined on a market. Hydroelectric production, based on water flow measurement is an example. However, in the longer term, other notions of value related to the environment have to be considered: option and existence values. Thus, biodiversity conservation and climate change understanding have a value, even if it is not given in a monetary form.
The failure to take into account all the different values, corresponding to different forms of humankind incentive [34] of an environmental good, results in what environmental economists call "incomplete value" of the environment. This value leads to reduce the value of water resource to its price, resulting from its operating cost, while other values (e.g. biodiversity) should also be taken into account.
Environmental economics suggests breaking down environmental value in several concepts: direct use value and existence value for instance. The direct use value is tangible and corresponds to the environmental good used as a production function in the short term. At the other end of the scale of time, the existence value is worth far less tangible since it represents the value assigned to an ecosystem or an endangered species. The set of values assigned to the environment is gathered under the term "total economic value" (fig. 3).
Figure 3. Water total economic value (Source: Economics for the Environment Consultancy Ltd, 2010 [10])
2) Valuation of environmental goods methods: The asset of values mentioned above cannot be measured with the same method. For the direct use value, the value is given by the price on an existing market where the environmental good is considered as a production function for hydropower production or wood, for instance.
If the market does not directly reveals the environmental good price, the hedonic price method can be used. It relies on the idea that environmental quality affects prices of other goods and services, as a factor involved in the consumer choice. The hedonic price method proposes to disclose the price related to the environmental quality (air pollution, noise, etc.) throughout the price of an apartment for instance.
The difference in price between two apartments whose characteristics are identical except the noise reveals the price allocated to the silence. The transport cost method is generally used for assessing the value of the environment based on recreational and natural areas. It measures the marginal willingness to pay according to the time and money spent to get to a place of interest.
Finally, if no market or substitute market exists, a hypothetical market has to be considered. The contingent valuation method is most commonly used to assess natural assets by estimating their use or non-use value [40]. It reveals the preferences of agents by direct consultation through a questionnaire. The latter should detail the environmental changes expected and the financing rules available, before asking the agent willingness to pay to avoid or compensate the environmental change mentioned.
All these methods (fig. 4) make possible to reveal the total economic value of environmental assets. This monetary value can then be included, as well as other expected benefits, in the economic evaluation of an Earth observation mission.
3) Time scales and discount rates: The total economic value of the environment is divided into different time horizons. As with any monetary value with a long time scale, a discount rate has to be used to bring future value back to present value. The chosen discount rate depends on the weight given to future consequences of a project. As space missions often stretch over fifteen years form R&D to operation phases, using relevant discount rate is essential for
project assessment.
Figure 4. Environmental goods valuation methods
In the case of environmental management, timescale may be even longer because of the impacts of the mission to be spread over thirty years or more. If the rate is usually chosen to be about 4%, it is customary to reduce this rate to 2% for projects as long as environmental projects. For comparison, the Stern Review on climate change impacts analysis uses a 0.1% discount rate. This choice has become a controversial matter among economists [11], especially North American economists [12, 13] arguing that a very low discount rate excessively favors future generations.
The choice of discount rate has a significant impact on the conclusions of the economic study for a long-term
REVEALED PREFERENCES EXPRESSED PREFERENCES
EXISTING MARKET SURROGATE MARKET HYPOTHETICAL MARKET
Market price Production function
Remediation cost
Hedonic price Transport cost price
Contingent valuation method Conjoint analysis
project. For a mission that can have important impacts on climate change adaptation, for instance, choosing a high discount rate will give a very low weight to these future values and may lead to missions cancellation.
4) Aggregation of the set of values: We have established that different values should be taken into account when estimating the total value of an environmental asset. Once the values estimated, however, it is dangerous to conduct a simple addition, as their characteristics are not uniform. The direct use value will be built on an economic market study for which data are tangible when the existence value may be based on a contingent valuation questionnaire whose results are more uncertain. Sum up these values lead to a loss of meaning. Differences in time horizon and impact of discount rate is another risk factor for adding values.
Thus, a suitable tool should display different values in the form of a diagram (Fig. 5). The area then represents the total economic value of the environmental good.
The total environmental value is not the only value to be taken into account for a mission assessment. This would not disrupt the current selection tools but complement them. The project managers could also benefit from this tool to follow the value achievement.
Figure 5. Diagram for a environmental good valuation tool (Source: Le Pellec-Dairon, 2012 [14])
B. Valuation of earth observation data
The previous section has highlighted the plurality of values related to environmental goods. Earth observation programs, as they can play a role in their management and protection - forest conservation, biodiversity management - thanks to the data they produce, have then a value.
Nevertheless, the environmental good value must not be confused with the data value. For instance, it is not because the SPOT satellite can provide data on Earth forest cover, whose value is estimated at $ 3 700 billion according to the
United Nations Environment Program experts, that SPOT worth $ 3 700 billion.
The concept of value of information is then essential to separate the data value from the environmental good value. This reflection was first conducted in the field of meteorology in the nineties. At first, meteorology emerged owing to a strong need related to major customers (marine, aviation). However, technological change and arrival of new customers brought up new opportunities and need for economic justification of projects. Studies to assess the value of satellite data, based on the information they provide, have enabled policy makers to develop new guidelines to implement new strategies for meteorological services. This concept applies to all environmental data.
This section traces how the value of information was discussed in the literature, generally, or in narrower field such as meteorology, to identify how to use these theories for environmental spatial data.
1) Overview on value of information: Howard [15] and Matheson [16] have made early studies on value of information for decision support in the sixties. Their work provided the concept of perfect information and a methodology to calculate the expected value of perfect information. In this first approach, the value of information is described as the maximum price that an agent would pay to acquire perfect information. This value is the difference between the expected payoff with perfect information and the expected gain from the best decision without information. Although relatively easy to implement, this valuation method using the ex-post model assigns a value to the information after it has been given (but before the state of the world has been revealed), which does not match the reality of decision-making for which value must be assigned before knowing the information.
The ex-ante decision model makes possible to assign a value to information before it is known. Not knowing the information that will be given, this method sums all possible messages weighted by their associated probabilities.
Thus, two types of models can illustrate decision processes resulting from the acquisition of information: models of decision ex-post or ex ante. They use the assumptions of utility [17] and decision theory with uncertainty [18].
2) Determinants of the value of information: Other approaches have then proposed new factors to build the value of information. Hilton [19] and Repo [20] have gathered these various approaches and additional factors. Merkhofer [21] has analyzed the impact of the flexibility of decision maker, showing that the value of information was bigger for decision makers in flexible position. Uncertainty and irreversibility of the decision are two other value determinants, studied by Claude Henry [22]. The characteristics of the information system [19] have an impact on the decision maker's confidence in the veracity of the information, which will impact on its value [23]. Other determinants, such as the level of wealth and the degree of risk aversion of the decision maker, have been proposed.
DIRECT USE VALUE
OPTION VALUE INDIRECT VALUE
However, various studies show conflicting results regarding the impact of these two variables on the value of information. Finally, Miller [24] shows that the value also depends on the price of other available data, obtained by other means. This is an important factor for space-based Earth observation, as alternative solutions exist for some applications (airborne campaign, for instance).
Beyond these factors, the literature relies on the concept of value chain of information [25], borrowed from the industrial value chain composed of a series of sequential steps following each other. Initial processing of information, its dissemination, its combination with other data, influence the final value of information. For instance, altimeter data gathered by the satellite Jason is first processed by the satellite operators, then integrated into models where remote sensing data are combined with in situ data. Dissemination of the information contained in the initial data is then provided by service companies, and used by end users (fishermen, scientists, etc.). This chain (or platform, as we will see it in the next section) of actors transforms raw data in useful information with high added value.
One factor influencing the value of information, the degree of uncertainty, has been particularly studied [22] since it has a strong influence on the estimated value. Information can improve decision making if the initial choice was uncertain. If the decision maker is absolutely certain of the results of his choices, additional information will not influence his decision, no significant impact on the well being, and therefore no value will be added [26]. However, environmental issues are characterized by very high uncertainty decision, which can give even more value to the information contained in the Earth observation products.
3) Consequences for Earth observation data valuation: These methods and determinants have been used to assess the value of information in several studies related to environmental management. Specifically, they enabled the assessment of weather data from satellites used for weather management related to agricultural production [3, 27]. The aversion risk level was significant for determining the value of information and was estimated to an average of $100/ha/yr for the first study in the U.S. and $A 12/ha/yr for the second in Australia.
For historical reasons, studies mainly concern the field of meteorology. Whereas Bayesian theory and theories of decision under uncertainty have been studied by several authors [38], few studies have attempted to estimate the prior and updated beliefs to define probability functions.
Only few studies have been based on environmental applications of satellite data. Most of them deal with the potential benefits of these missions without empirical analysis [28, 29]. Nevertheless, studies on the value of information for the water quality management in the North Sea [26] or Great Barrier Reef management [30] proposed a quantitative analysis based on the Bayesian theory. This study has evaluated the value of satellite information to €74000 per week and compared it to the cost of implementing this new system of €50000 per week. A stakeholders survey has been conducted through a questionnaire. This questionnaire has been used to conduct an assessment of the added value of satellite observations for various factors such as eutrophication, suspended sediments or algal bloom episodes. Possible actions and distributions of prior probabilities (based on questionnaire responses), and according to information provided by the satellite data, have been established. The application of Bayesian theory was finally assessed at €74000 per week the value of satellite information for fisheries management based on potential algal blooms.
These studies demonstrate that an appropriate quantitative analysis of Earth observation is possible. However, they currently focus on direct use value, market prices and short-term time scales. Previous sections highlighted the need to consider the multiplicity of environmental values. Then, these results should be combined with other environmental studies to fill in the diagram previously proposed. This work is on going for the Jason missions, on an a posteriori approach, and on the SWOT mission.
The valuation method proposed is summarized in table 2.
TABLE II. EARTH OBSERVATION DATA VALUATION METHOD STEPS A Evaluate the total economic value of an environmental good - natural resource management, biodiversity conservation, etc.
1
Estimate the various values (direct use value, existence value, etc.) of an environmental good with the methods proposed by environmental economics theory
2 Take into account the different time scales and identify the appropriate discount rate 3 Aggregating these values in a diagram to obtain the total economic value of environmental project
B Move from the total economic value of environmental goods to the value of Earth observation data
1
Take into account the various factors influencing the value of information: decision maker's flexibility, characteristics of information system, political factors, uncertainty of choice, etc. 2
Use the total economic value previously estimated and the Bayesian theory - within the limits of validity of the theory - to estimate the prior and updated belief by interviewing experts in environmental goods
3
Take into account the robustness of the results by analyzing the possible errors in the production system and the variance of responses of specialists
4
Compare the value of information carried by the satellite data to the cost of setting up such an information system to justify the interest of a mission
IV. ACHIEVEMENT OF THE TOTAL VALUE DUE TO STAKEHOLDERS ORGANISATION
The previous section highlighted the need for specific valuation methods for environmental benefits, in order to include this data in the whole missions selection and management method. This value can be a tool to justify a mission or select among various missions the most suitable one. This element can also be the driving force behind stakeholders’ involvement and total value achievement in the course of the mission.
The committee on NASA-NOAA transition from Research to Operations [7] suggests ways to increase the return to society for satellite observations of the Earth’s environment. The third recommendation highlights the need to include an early evaluation of each mission for potential applications to operations in the short, medium, or long term. In other space domains, stakeholders’ involvement has been demonstrated as an important element of mission success. This section gives an overview of network and stakeholder theories that throw light on Earth observation ecosystem and the relevance of the platform concept.
A. Contribution of Stakeholder and network theories for Earth observation missions
Freeman [31] first described the need for stakeholders analysis and presented a mapping technique that considers an organization and its stakeholders, as well as their interactions (fig. 6). One of the goals of this map is to provide a structured template for articulating stakeholder needs and objectives [32]. It also gives the opportunity to gather different types of interactions between stakeholders, such as policy, monetary, information, etc.
Chanal [33] also argues that a systemic vision, where ecosystem replaces classical linear innovation process vision, should be adopted. Inspired by biology, Iansiti and Levien suggested the concept of Business Ecosystem [34] in which company’s strategy aims largely to create conditions that are favorable for its own activity. Only a business ecosystem could then supports the emergence and diffusion of original
value propositions. Stakeholders, goals, objectives and needs designation enable an ecosystem mapping, necessary for value capture.
Figure 6. Stakeholder mapping technique with direct interactions (Source : Freeman, 1984)
The concept of stakeholders network being preferred to stakeholders chain, Brandeburger and Nalebuff [35] introduced the value network concept instead of value chain. Thus, identifying stakeholders and their interactions is a step to a stakeholder value network model.
Once this mapping carried out, another key factor is what Cusumano and Gawer calls platform leadership [36]. Using Intel as a seminal case study, authors demonstrate that a platform is usually made up of a leader and complementors, which are dependent on each other. Intel’s microprocessor illustrates the issue since it can do little or nothing by itself and is a component of a broader platform. Without the whole components of a computer (BUS, graphic card, etc.) evolving together, a microprocessor has no value. This example can be transposed to Earth observation systems, as a virtual platform where stakeholders bring data, algorithms, models, technical skills, expertise. These elements cannot gain in value but altogether.
B. Stakeholders mapping framework
The framework chosen for this study follows the work carried out by the previous authors and combines some of their contributions.
• The first step consists in identifying stakeholders. The community has to be listed, and roles, objectives and needs to be revealed.
• The second step is the understanding of stakeholders’ interactions so as to visualize the community platform.
• Besides usual interactions, innovation diffusion has often been described as a consequence of one or several special events. Some space sector agents are even talking about a bet when describing mission success. It is then interesting to analyze previous successful missions to identify and understand these particular events or favorable conjunction, in order to “force the hand of destiny”.
An illustration of the stakeholders mapping framework will be provided in the next section.
V. FIRST RESULTS
This on going study has first consisted in defining and designing the case study. The theory framework has been developed and presented in this paper, regarding (1) valuation methods and (2) stakeholders platform organization. The two case studies are currently conducted and no final results can be given. Nevertheless, preliminary results can be introduced.
A. Valuation methods
The valuation process, as it needs numerous data to be completed, is still at an early stage. Results at this stage would not be relevant.
B. Stakeholders platform
The study focusing on stakeholders has been conducted on the space oceanography domain, to understand a posteriori how the community has organized itself and why this leads to success. It consists in a list of stakeholders and their roles, objectives and needs. These results are not exhaustive but highlight the mapping method.
1) Stakeholders mapping
In France, satellite altimetry is considered as a center of excellence. Five major French agencies – CNRS (National Centre of the Scientific Research), IFREMER (French Research Institute for Sea operations), IRD (Development Research Institute), METEO FRANCE (French National Weather Service) and SHOM (Oceanographic Department of the French Navy) – have joined with CNES to create in 2002 a non-profit company, Mercator Ocean, aiming at developing and running operational systems able to describe, to monitor and to forecast the ocean at any location in the world, from the deep ocean to the surface.
Scientific partners are also involved in satellite altimetry: French laboratories such as LEGOS (Geophysics and spatial oceanography laboratory) and CNRM (MétéoFrance, National research center for meteorology). French and international institutional organizations are key stakeholders: ESA (European Space Agency), EEA (European Environmental Agency), EMSA (European Marie Safety Agency) and the French Ministry for ecology.
CLS (Collecte Localisation Satellites), a subsidiary of CNES, IFREMER and several French financial institutions, offers satellite services in environmental data collection, ocean observations and monitoring to a broad range of professionals including government, industry and the scientific community. A list, which will be completed, is given in table 3.
A specific study of each stakeholder is then necessary to identify links between stakeholders and the type of their interaction (action, funding, communication, etc.). It can be visualized in a diagram, for the Mercator Ocean example (fig. 7).
TABLE III. IDENTIFICATION OF STAKEHOLDERS AND THEIR ROLES
Stakeholders identification
Stakeholder Role
CNES
Provide means in order to expand human knowledge of the Earth and space. Responsible for program organization, management and data acquisition. NASA
Provide means in order to expand human knowledge of the Earth and space. Responsible for program organization, management and data acquisition. SHOM Collect marine environment to insure marine safety as a public service; Insure submarines safety
IFREMER
Contribute to knowledge of the oceans and their resources, monitoring of marine and coastal environments and sustainable development of marine activities; Conceive and operate tools for observation, experimentation and monitoring, and manage the
oceanographic databases. IRD
Contribute to the social, economic and cultural development of southern countries by research, training
and innovation activities CNRS
Evaluate and carry out all research capable of advancing knowledge and bringing social, cultural, and
economic benefits for society. METEO
FRANCE Provide weather forecasts and climate knowledge MERCATOR
OCEAN
Develop and run operational systems able to describe, monitor and forecast the ocean and provide products
and services
EUMETSAT Deliver weather and climate-related satellite data, images and products. NOAA
Deliver products and services from daily weather forecasts, severe storm warnings and climate monitoring to fisheries management, coastal restoration
and supporting marine commerce CLS
Offer satellite services in environmental data collection and ocean observations and monitoring to a broad range of professionals including: government, industry and
the scientific community.
LEGOS information; develop science systems; provide science Provide algorithms that transform raw data in a useful knowledge and opinions on the systems specifications CORIOLIS
Provide the French ocean forecasting centers, MERCATOR Ocean and French Hydrographic Service
(SHOM) with oceanographic data obtained by diverse means including in-situ (ships, drifters, floats,
moorings, etc.)
My Ocean
Deliver and operate an ocean monitoring and forecasting system of the GMES Marine Service (OMF/GMS) to users for all marine applications: maritime safety, marine resources, marine and coastal
environment and climate, seasonal and weather forecasting.
Figure 7. An example of stakeholder’s interactions diagram: Mercator Ocean
2) Triggering factors: Beyond these ordinary interactions, the analysis of TOPEX/Poseidon and Jason development reveals that particular events have probably turned the tide of the story.
• Mutual needs: The development of a dedicated altimetry mission required specific instruments and a suitable launcher. This equipment was shared between France and the U.S.A., leading to their collaboration.
• Political events: At the time when the TOPEX/Poseidon mission was under discussion between France and the United States, the political relationship between the two countries was damaged. The mission, only joint project at the time, has been encouraged to reassert the French-American friendship.
• Important persons: Operational altimetry has probably succeeded thanks to the vision of few people, generally with cross-disciplinary backgrounds, who early felt the need to consider operational applications.
• Community homogeneity: the oceanographic community is mainly made up of scientific and institutional stakeholders. Most of the applications are destined for public services or research programs. Commercial services are still considered as niche markets. The platform organization is made easier as stakeholders are similar.
3) Platform leadership: Mercator Ocean, given is position in the oceanography ecosystem, could be considered as the leader of the French oceanographic platform. It is a visible and strong stakeholder, jointly created by five major French agencies involved in oceanography. They provide a reliable funding system, ensuring capacity to combine various data and process value-added products.
VI. CONCLUSION
Earth observing systems have been presented in several international reports as valuable solutions to face up to
environmental challenges and many applications can result from data they collect. These applications can be included in commercial services or be a part of sovereign functions carried out by States. In the first case, direct economical benefits will come from product sale, as a return on investment in the space infrastructure. In the second one, benefits will be both environmental and economical, as the firms created to provide services to public organizations will create employment and be taxed, which can be considered as an indirect return on investment in the satellite.
In consequence of budget constraints, the strategy for Earth observation missions management have to be much more efficient, in order to select and manage the missions with the largest positive effects (aggregation of economical, political, technical, environmental values etc.), especially when indirect return on investment is at stake. This paper suggested two lines of work: a broader assessment of the potential value assessment in the first stages of the mission and during its development; and an organization of stakeholders around platforms, suitable for achieving the potential value. The on-going study on Jason provides an ex post analysis of the two lines of work as well as some explanations of the space-based oceanography success. The study carried out on the developing mission SWOT provides an ex ante analysis which can be confronted to theory and lessons from Jason.
Further research is required to turn the theory on valuation and stakeholders’ organization, as well as the determinants of previous missions’ success into a management tool.
ACKNOWLEDGMENT
This research could not have been carried out without the help of the French space agency, CNES, and its agents who gave time for interviews. Stakeholders have also been a major source of information, especially Pierre Bahurel from Mercator Ocean, who participated in the reflection on stakeholders’ interactions.
REFERENCES
[1] National Research Council, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond. Washington, DC: The National Academies Press, 2007.
[2] National Research Council, Earth science and Applications from Space : A midterm Assessment of NASA’s implementation of the Decadal Survey. Washington, DC: The National Academies Press, 2012.
[3] G. Fox, J. Turner, T. Gillespie, The value of precipitation forecast information in winter wheat production, Agricultural and Forest Meteorology, Vol. 95, Issue 2, 1999, Pages 99-111.
[4] T. Borisova, J. Shortle, R. D. Horan, D. Abler, Value of information for water quality management, Water Resources Research, Vol. 41, 2005, pp. 1-11.
[5] R. K. Yin, Case Study Research: Design and Methods, Thousand Oaks: Sage publications, 2009
[6] M. Srinivasan, R. Leben, Societal benefits of ocean altimetry data, Geoscience and Remote Sensing Symposium, IGARSS '04, 2004. [7] National Research Council. Satellite Observations of the Earth's
Environment: Accelerating the Transition of Research to Operations. Washington, DC: The National Academies Press, 2003.
MERCATOR OCEAN IFREMER, IRD, CNRS, SHOM, METEO FRANCE (MF) CNES CORIOLIS Scientific community Funding Action plan Space-acquired data In-situ data
Algorithms & model METEO FRANCE Meteorological data IFREMER, IRD, CNRS, SHOM, MF My Ocean Oceanographic data CLS, commercial service providers Products Scientific community My Ocean All users Specific expertise Knowledge MF, SHOM, IFREMER, public services Scientific community
[8] L.L. Fu et al, The SWOT (Surface Water and Ocean Topography) Mission: Spaceborne Radar Interferometry for Oceanographic and Hydrological Applications, OCEANOBS’09 Conference, 2009. [9] P.B.Thompson, Uncertainty arguments in environmental issues,
United States : Environmental Ethics; Vol. 8 (1), 1986, pp. 59-75. [10] Economics for the Environment Consultancy Ltd (eftec), Scoping
study on the economic (or Non-Market) valuation issues and the implementation of the WFD – Final Report for the EC DG Environment, 2010.
[11] O. Godard, Climat et générations futures - Un examen critique du débat académique suscité par le Rapport Stern, n° 2007-13, Ecole Polytechnique, 2007, Working Paper
[12] W.D. Nordhaus, A Review of the" Stern Review on the Economics of Climate Change", Journal of Economic Literature, 2007, pp. 686-702.
[13] M.L. Weitzman, A review of the Stern Review on the economics of climate change, Journal of Economic Literature, Vol. 45(3), 2007, pp. 703-724.
[14] M. Le Pellec-Dairon, La valeur environnementale des programmes spatiaux : Concepts et méthodes, (chap. 4), in Midler C., Ben Mahmoud-Jouini S., Maniak R., Management de l’innovation de rupture Nouveaux enjeux et nouvelles pratiques , Paris: Les Editions de l’Ecole Polytechnique, 2012, pp 42-55.
[15] R.A.Howard, Information value theory, Systems Science and Cybernetics, IEEE Transactions, Vol. 2(1), 1966, pp. 22-26. [16] J.E. Matheson, The economic value of analysis and computation.
Systems Science and Cybernetics, IEEE Transactions, Vol. 4(3), 1968, pp. 325-332.
[17] J. Von Neumann, O. Morgenstern, Theory of games and economic behaviour, Princeton University Press, 2007
[18] J.W. Pratt, H. Raiffa, and R. Schlaifer, The foundations of decision under uncertainty: An elementary exposition, Journal of the American Statistical Association, 1964, pp. 353-375.
[19] R.W.Hilton, The determinants of information value: Synthesizing some general results, Management Science, 1981, p. 57-64. [20] A.J. Repo, The value of information: Approaches in economics,
accounting, and management science, Journal of the American Society for Information Science, Vol. 40(2), 1989, pp. 68-85. [21] M.W. Merkhofer, The value of information given decision flexibility,
Management Science, 1977, pp. 716-727.
[22] C. Henry, Investment decisions under uncertainty: the" Irreversibility Effect", The American Economic Review, Vol. 64(6), , 1974, pp. 1006-1012.
[23] J. Hirshleifer, J.G. Riley, The analytics of uncertainty and information-an expository survey, Journal of Economic Literature, Vol. 17(4), 1979, pp. 1375-1421.
[24] A.C. Miller, The value of sequential information, Management Science, 1975, pp. 1- 11.
[25] B. Delecroix, La mesure de la valeur de l’information en intelligence économie, unpublished thesis (Ph.D), Université de Marne la Vallée, 2005.
[26] J.A. Bouma, H.J. van der Woerd, O.J. Kuik, Assessing the value of information for water quality management in the North Sea, Journal of environmental management, Vol. 90(2), 2009, pp. 1280-1288. [27] G.Y. Abawi, R.J. Smith, D.K. Brady, Assessment of the value of long
range weather forecasts in wheat harvest management, Journal of agricultural engineering research, Vol. 62(1), 1995, pp. 39-48. [28] M.K. Macauley, The value of information: Measuring the
contribution of space-derived earth science data to resource management, Space Policy, Vol. 22(4), 2006, pp. 274-282.
[29] R.A. Williamson and al., The socioeconomic benefits of Earth science and applications research: reducing the risks and costs of natural disasters in the USA, Space Policy, Vol. 18(1), 2002, pp. 57-65. [30] J. Bouma and al., Assessing the value of Earth observation for
managing the coral reefs: an example from the great barrier reef, Science of the Total Environment, 2011, pp. 4497-4503
[31] R.E. Freeman, Strategic Management: A stakeholder approach. Boston: Pitman, 1984.
[32] T.A. Sutherland, Stakeholder Value Network Analysis for Space-Based Earth Observations, unpublished thesis, Massachusetts Institute of Technology, 2003.
[33] V. Chanal, Rethinking Business Models for Innovation Lessons from entrepreneurial projects, Paris: Valérie Chanal, 2011.
[34] M. Iansiti, R. Levien, Strategy as Ecology, Harvard Business Review, Vol. 82(3), 2004.
[35] A.M. Brandenburger, B.J. Nalebuff, The Right Game: Use Game Theory to Shape Strategy, Harvard Business Review, Vol. 73(4), 1995, pp. 57-71.
[36] M.A. Cusumano, A. Gawer, The elements of platform leadership, MIT Sloan Management Review, Vol. 43(3), 2002, pp. 51-58 [37] F. Yokota, K.M. Thompson, Value of information analysis in
environmental health risk management decisions: past, present, and future, Risk Analysis, Vol. 24(3), 2004, pp. 635-650.
[38] CNES press release, 22 sept 2011
[39] R.C. Mitchell, R.T. Carson, Using surveys to value public goods: The contingent valuation method, Washington, DC: Resources for the Future, 1989.
