Prepared in cooperation with the National Oceanic and Atmospheric Administration, 

FourBridges, European Space Agency, and European Association of Remote Sensing Companies

Demonstrating the Value of Earth Observations—Methods, 

Practical Applications, and Solutions—Group on Earth 

Observations Side Event Proceedings

Open-File Report 2019–1033

U.S. Department of the Interior

U.S. Geological Survey
Cover. A, Urban flooding. B, Forest fire. C, Dam construction. D, Illustation of a satellite. E, Oil spill investigation. F, Coastal flooding. 

All images from the National Oceanic and Atmospheric Administration.

A

B

C

D

E F
Demonstrating the Value of Earth 

Observations—Methods, Practical 

Applications, and Solutions—Group on 

Earth Observations Side Event Proceedings

By Francoise Pearlman, Collin B. Lawrence, Emily J. Pindilli, Denna Geppi, 

Carl D. Shapiro, Monica Grasso, Jay Pearlman, Jeffery Adkins, Geoff Sawyer, 

and Alessandra Tassa

Prepared in cooperation with the National Oceanic and Atmospheric Administration, FourBridges, European Space Agency, and European Association of Remote 

Sensing Companies

Open-File Report 2019–1033

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2019

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Suggested citation:

Pearlman, F., Lawrence, C.B., Pindilli, E.J., Geppi, D., Shapiro, C.D., Grasso, M., Pearlman, J., Adkins, J., Sawyer, G., 

and Tassa, A., 2019, Demonstrating the value of Earth observations—Methods, practical applications, and 

solutions—Group on Earth Observations side event proceedings: U.S. Geological Survey Open-File Report 2019–1033, 

33 p., https://doi.org/10.3133/ofr20191033.

ISSN 2331-1258 (online)
iii

Acknowledgments

We would like to acknowledge the following organizations for their co-sponsorship of 

the workshop: the Group on Earth Observations, the National Oceanic and Atmospheric 

Administration, the European Association of Remote Sensing Companies, the European 

Space Agency, and FourBridges (nonprofit research organization).

v

Contents

Acknowledgments........................................................................................................................................iii

Executive Summary.......................................................................................................................................1

Major Findings.......................................................................................................................................2

Next Steps..............................................................................................................................................2

Introduction.....................................................................................................................................................2

The Value Chain ....................................................................................................................................3

The Decision Tree .................................................................................................................................4

Meeting Summary..........................................................................................................................................6

Welcome Address ................................................................................................................................6

Methodologies—Session 1.................................................................................................................7

Methodologies—Session 2.................................................................................................................9

Introduction to Value Chains/Decision Trees and Processes Panel—Session 3....................11

Value Chains/Decision Trees Forum—Session 4 ..........................................................................12

Value-Chain and Decision-Tree Working Groups..........................................................................13

Group 1—Effect of Increasing Temperatures on Human Health.......................................13

Group 2—Flooding—Mitigating. Managing, and Avoiding Impacts to Safety 

and Property Damage..................................................................................................14

Group 3—Harmful Algal Blooms—Effects on Human Health, Recreation, 

and Tourism...................................................................................................................16

Group 4—Energy and Mineral Supply—Mitigating, Managing, and Avoiding 

Impacts of Shortfalls on the Economy......................................................................18

Group 5—Effects of Natural Hazards on Transportation Systems—Effects 

on Mobility, Safety, and the Economy.......................................................................22

Open Discussion—Working Group Approaches to Developing Value Chains 

and Decision Trees................................................................................................................24

Synthesis, Findings, and Next Steps ........................................................................................................24

Synthesis..............................................................................................................................................24

Findings.................................................................................................................................................24

Next Steps............................................................................................................................................25

References Cited..........................................................................................................................................26

Glossary.........................................................................................................................................................29

Appendix 1. Attendee List .......................................................................................................................30

Appendix 2. Workshop Agenda..............................................................................................................32

Figures

1. Graph showing GEOValue Community events (2010–17) .......................................................3

2. Diagram showing Earth observation information value chain..............................................4

3. Diagram showing Earth observation decision tree.................................................................5

4. Diagram showing effects of increasing temperatures on human-health

value chain/decision tree..........................................................................................................15

5. Diagram showing flooding: mitigating, managing, and avoiding impacts

to safety and property damage value chain/decision tree..................................................17
vi

6. Diagram showing harmful algal blooms (HAB): effects on human health,

recreation, and tourism value chain/decision tree...............................................................20

7. Diagram showing energy and mineral supply: mitigating, managing, and

avoiding impacts of shortfalls on the economy value chain/decision tree ......................21

8. Diagram showing effects of natural hazards on transportation systems:

effects on mobility, safety, and economy value chain/decision tree.................................23

Tables

1. Group 1 participants...................................................................................................................13

2. Group 2 participants...................................................................................................................14

3. Group 3 participants...................................................................................................................16

4. Group 4 participants...................................................................................................................19

5. Group 5 participants...................................................................................................................22

1.1. GEOValue side event attendee list, Washington, D.C., October 23–24, 2017 ....................30

Abbreviations

3D three dimensional

CRCSI Cooperative Research Centres for Spatial Information

EARSC European Association for Remote Sensing Companies

EO Earth observations

ESA European Space Agency

FAA Federal Aviation Administration

GEO Group on Earth Observations

GRACE Gravity Recovery and Climate Experiment

HAB harmful algal bloom

NASA National Aeronautics and Space Administration

NOAA National Oceanic and Atmospheric Administration

RFF Resources for the Future

USGS U.S. Geological Survey

VOI value of information
Demonstrating the Value of Earth Observations—

Methods, Practical Applications, and Solutions—

Group on Earth Observations Side Event Proceedings

By Francoise Pearlman,1 Collin B. Lawrence,2 Emily J. Pindilli,2 Denna Geppi,3 Carl D. Shapiro,2

Monica Grasso,3 Jay Pearlman,1 Jeffery Adkins,3 Geoff Sawyer,4 and Alessandra Tassa5

1

FourBridges.

2

U.S. Geological Survey.

3

National Oceanic and Atmospheric Administration.

4

European Association of Remote Sensing Companies.

5

European Space Agency.

Executive Summary

The U.S. Geological Survey, the National Oceanic and 

Atmospheric Administration, the European Association for 

Remote Sensing Companies, and the European Space Agency 

in coordination with the GEOValue Community hosted a side 

event to the Group on Earth Observations Plenary on October 

23–24, 2017, in Washington, D.C. The workshop, entitled 

“Demonstrating the Value of Earth Observations: Methods, 

Practical Applications and Solutions,” brought together more 

than 60 international experts including economists, scientists, 

and engineers to consider the state of the science and applications of valuing Earth observations (EO).

This 2-day workshop built upon previous activities developed under the GEOValue initiative. This workshop brought 

together expert analysts from multiple disciplines and backgrounds who are developing methods to identify and measure 

the value of information generated from the use of satellite and 

in-situ data. The mix of government agencies, international 

financial institutions, and independent consultants who participated in the workshop blended to develop a rich mix of views, 

approaches, and outcomes.

During the first part of the workshop, the focus was on 

the latest science in valuing EO. A number of methodologies were described. Approaches generally assess the societal 

benefits of specific actions (for example, investments in EO). 

Some methods focus on broad measures of economic activity 

(for example, gross domestic product) or methods to assess 

total economic value such as contingent valuation surveys. 

Alternatively, use-case approaches (a use case is defined as 

an evaluation in which one or more decisions, applications, 

or other uses of data, information, and information products 

are specifically considered) start with the specific actions and 

how information is used to support decision making and affect 

outcomes.

The second part of the meeting was focused on the use 

and development of value chains and decision trees. A value 

chain can be defined as the set of value-adding activities that 

one or more organizations perform in creating and distributing 

goods and services. In terms of EO, the value chain approach 

can be applied to consider societal benefits of the data and 

assess the value of data and data features. The EO value chain 

considers the geospatial data sources and the processing of 

the data into value added information to be incorporated into 

decision-support systems, leading to decision makers’ actions. 

To understand the value of EO, one would also need to recognize the demand side of the equation or how EO benefits users. 

Extending the value chain concept and incorporating tenets 

of Bayesian decision making, a decision tree would include 

one or more use cases. The value provided by the marginal 

increase in information could flow from one or several parts of 

the supply side of the value chain. The decision tree is based 

on the premise that information has no value if it is not used 

in at least one decision. By connecting the value chain and the 

decision tree, a framework is created that allows for conceptualizing the value of EO in its many uses. One can then apply 

economic techniques to monetize the marginal benefit of an 

outcome with information versus one without.

A third part of the meeting applied the value chain and 

decision-tree frameworks to five specific thematic areas, each 

with the focus of using information for a decision point:

• Effect of increasing temperatures on human health;

• Flooding—Mitigating, managing, and avoiding impacts

to safety and property damage;

• Harmful algal blooms—Effects on human health, recreation, and tourism;

• Energy and mineral supply—Mitigating, managing,

and avoiding impacts of shortfalls on the economy; and

• Effects of natural hazards on transportation systems—

Effects on mobility, safety, and the economy.
2 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

During the working session, five separate groups worked 

to define and delineate the value chains and decision trees 

associated with each topic, discussing the related challenges 

and data needs. The outcomes were reported back to the full 

group. Because of the complexity of the topics, most groups 

first identified a network of value chains and then narrowed 

the scope to develop a single value chain to address their 

group’s topic. Although they worked separately and on different topics, the groups came to similar conclusions, concurring 

that the value chain and decision-tree frameworks are very 

effective for informing quantitative impact assessments and 

developing a relatable narrative to assist the public in understanding the link between EO and citizens.

Major Findings

Finding 1.—It is critical that improved understanding of 

the value of EO be developed.

Finding 2.—The understanding of the value of EO is 

facilitated by a description or narrative clearly explaining the 

basis for societal benefits from EO and a quantified estimate of 

the value in monetary or nonmonetary terms.

Finding 3.—Narratives that explain the basis of the 

societal benefits from the use of EO need to provide a clear 

and relatively simple explanation of how EO can create an 

improved societal outcome.

Finding 4.—Value chains and decision trees can be useful 

tools in understanding the value of EO.

Finding 5.—Use cases help advance the state of the science of valuing information.

Finding 6.—Innovations in quantifying the value of information are needed.

Finding 7.—Group on Earth Observation provides an 

institutional pathway for engaging an international community 

for the research and application of valuing EO.

Next Steps

The workshop was successful in highlighting and 

understanding value chains and decision trees relating to EO. 

Participants supported the ongoing role and importance of 

the GEOValue Community. Initial value-chain decision-tree 

frameworks were developed for five topics and will continue to be worked with different subsets of groups. The next 

GEOValue Community meeting is expected to further consider 

this methodology and tackle other common issues with valuing EO. The following future directions will enhance efforts to 

develop improved understanding of the value of EO.

1. Innovative approaches need to be discovered and

leveraged.

2. The GEOValue community needs to continue and be

strengthened.

3. More case studies should be developed to cover as wide

a range as possible of thematic, product, and geographical dimensions.

4. The different methodologies should continue to be

developed and compared to explore the viability, effectiveness, and best practices for the use of value chains

and decision trees in analyzing the value of EO.

5. Practical illustrations of value-chain and decision-tree

applications through results from case studies should be

shared and discussed at a future GEOValue workshop.

6. The international, interdisciplinary dimensions should

continue to be developed to draw out the richness of case

analyses.

Introduction

The U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the European 

Association for Remote Sensing Companies (EARSC), and 

the European Space Agency (ESA) in coordination with the 

GEOValue Community hosted a side event to the Group on 

Earth Observations (GEO) Plenary on October 23–24, 2017, 

in Washington, D.C. The workshop, entitled “Demonstrating 

the Value of Earth Observations: Methods, Practical Applications and Solutions,” brought together an international, 

interdisciplinary group of economists, scientists, and engineers 

to consider the state of the science on valuing Earth observations (EO). This report provides a summary of the workshop 

as well as a set of future directions for advancing the science. 

The workshop was video recorded and can be found at Group 

on Earth Observations (2017a, 2017b, 2017c). 

The value of information (VOI) has been a subject of 

interest for decades with rich literature focused on the use 

of weather information for agriculture production and management as reported by Johnson and Holt (1986), Adams 

and others (1995), Lave (1963), Sonka and others (1987), 

Babcock (1990), Pielke (1995), Nordhaus and Popp (1997), 

and Hersh and Wernstedt (2002). These studies tie the input 

of additional information to an increase in economic value. 

Nordhaus (1986) derived the VOI for hurricane data in 1986 

and is one of the most often cited for estimating VOI. In recent 

years, understanding the value of EO has become increasingly 

important because budget constraints require enhanced understanding of return on investment.

The GEOValue Community (http://www.geovalue.org/) 

was formed to bring together a wide range of natural science, 

social, economic, management, and communication experts to 

share information, collaborate, and build capacity to understand the benefits from geospatial and environmental information for complex socioeconomic decisions. The GEOValue 

Community has held several meetings over the course of the 

last decade. See figure 1 for the number and types of meetings 
Introduction 3

held by the GEOValue Community since 2010. The workshop described in this report was designed to share the latest 

science and applications of valuing EO and to advance the 

state of the science by considering a set of EO applications 

and the benefits of information for these uses. The workshop 

program was therefore divided into three activities: (1) a series 

of presentations on recent studies on the value of EO; (2) a 

panel and open discussion on the value-chain/decision-tree 

approach; and (3) facilitated break-out sessions to brainstorm and develop value chains/decision trees for a set of EO 

informed decisions.

The first part of the workshop focused on the latest 

science in valuing EO. Several methodologies were described. 

Approaches generally assess the societal benefits of specific 

actions (for example, investments in EO). Some methods 

focus on broad measures of economic activity (for example, 

gross domestic product) or methods to assess total economic 

value such as contingent valuation surveys. Alternatively, 

use-case approaches start with the specific actions and how 

information is used to support decision making and effect 

outcomes.

Presentations included international case studies and 

provided theoretical underpinnings and specific application 

of VOI analysis. A cross-sector assessment of the Copernicus 

Programme was presented. Other presentations illustrated 

differing methodologies with specific case studies including 

early warning systems for weather information in France, an 

analysis of the value of EO in Australia, the marginal value of 

three-dimensional (3D) geo-information, the value of Landsat 

moderate EO, a case study on the value of a dedicated national 

spatial data agency in Albania, a case study on the use of radar 

imagery to help icebreakers navigate in the Baltic Sea, and the 

use of EO for mitigating the impacts of drought on agriculture. 

After a morning of presentations on methodologies, the workshop was narrowed to focus on value-chain and decision-tree 

analytic frameworks.

The Value Chain

A value chain can be defined as the set of value-adding 

activities that one or more organizations perform in creating 

and distributing goods and services (Longhorn and Blakemore, 

2007). The concept was initially introduced by Porter (1985) 

and is widely used in evaluating business management and 

profitability. By understanding the ultimate “value” of a product and the components along the value chain, businesses can 

consider how to optimize processes. In terms of EO, the valuechain approach can be applied to consider societal benefits of 

the data and assess the value of data and data features. The EO 

value chain considers the geospatial data sources and the processing of the data into value added information to be incorporated into decision-support systems, leading to decision 

makers’ actions. Workshop participants believed that it may 

be best to start from the end (from the users) and approach the 

value chain in reverse order. The supply side of a generic EO 

value chain can be illustrated by figure 2; to consider the users, 

a decision tree is one approach to conceptualize the demand 

side and is illustrated in figure 3.

Figure 1. GEOValue Community events (2010–17). Number of events per year

2010

Year

0

2

3

1

2011 2012 2013 2014 2015 2016 2017

Other

Group on Earth Observations 

Tutorial

Workshop

EXPLANATION
4 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

Figure 2. Earth observation information value chain.

Observation

platform Sensors Data Analysis Information

Final

products/

services 

The Decision Tree

To understand the value of EO, one would also need to 

recognize the demand side of the equation or how EO benefits 

users. Extending the value-chain concept and incorporating 

tenets of Bayesian decision making, the following represents 

a generic demand side of a value chain for EO or a decision 

tree. There could be one or more “decisions” or other uses 

of data, information, and information products (often termed 

“use case”). The value provided by the marginal increase in 

information could flow from one or several parts of the supply 

side of the value chain (fig. 2).

The decision tree is based on the premise that information 

has no value if it is not used in at least one decision. Therefore, the purpose of the decision tree is to consider the types of 

decisions made using information and compare scenarios with 

and without information. A simplified form is assumed where 

the with information is reality and decision pathways are 

known. The without-information scenario, or counterfactual 

needs to be considered. One identifies the potential alternative decision pathways, the outcomes of those pathways, the 

probability of a decision maker choosing any pathway given 

the next best information, and the monetized value of each 

decision pathway. Each of the decision points in figure 3 illustrate the simplified derivation of the value of information. To 

quantify the value of information under these assumptions the 

following formula would estimate the value:

[(P*×M*)] – [([P1×M1] + [P2×M2] + [P3×M3])] = VOI (1)

where

P is the probability of a given decision pathway,

M is the monetized value of a given decision 

pathway, and

VOI is the value of information.

It should be noted that this formula is associated with figure 3, 

which assumes that the decision pathway for the with information is known (i.e., there is no uncertainty in the with information case). The illustration has three possible decision pathways, there may be more or less decision pathways that could 

be considered in estimating the value of information. Finally, 

this estimates a one-time or annual value, it does not consider 

the net present value of a decision over time. 

By connecting the value chain and the decision tree, a 

framework is created that allows for conceptualizing the value 

of EO in its many uses. One can then apply economic techniques to monetize the marginal benefit of an outcome with 

information versus one without. At the workshop, an expert 

panel discussed the use of the value-chain/decision-tree framework. The panelists also introduced questions about the type 

of information needed to develop value chains/decision trees. 

Panelists discussed a wide range of applications that have 

been considered using a value-chain/decision-tree framework 

including human health, ecosystems, emergency management, 

and resource allocations. During the workshop, three different 

perspectives were examined in this regard:

• Product value chains/decision trees (analyzing the 

impact of a single information product),

• Thematic value chains/decision trees (analyzing the 

impact in a thematic area [for example, flooding] from 

a suite of products), and

• Market value chains/decision trees (analyzing the 

impact of products within the context of the market 

sectors within which they are used).

After the conceptual review of the value-chain/decisiontree framework, the workshop focused on the development of 

value chains/decision trees for five specific topics:

1. Effect of increasing temperatures on human health;

2. Flooding—Mitigating, managing, and avoiding impacts 

to safety and property damage;

3. Harmful algal blooms (HABs)—Effects on human 

health, recreation, and tourism;

4. Energy and mineral supply—Mitigating, managing, and 

avoiding impacts of shortfalls on economy; and

5. Effects of natural hazards on transportation systems—

Effects on mobility, safety, and economy.

To address these five topics, workshop participants 

divided into small working groups to define and develop the 

value chains/decision trees associated with each topic. During 

these breakout sessions, participants discussed the related 

challenges and data needs, and presented their group’s results 

when workshop participants reconvened. From the outcomes 

shared by each group, it was evident that the descriptions of 

the value chains/decision trees stimulated interesting insights 

into the multiple impacts of EO data to society and the international economy.
Figure 3. Earth observation decision tree.

Decision 

point

A

BC

A

BC

---

B B -

Without 

information

With information

Final 

products/ 

services

A1

A3

A*

A2

O1

O3

O2

P1

P3

P2

O* P* 

Alternatives Outcomes Probability 
6 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

The use of EO in decision making results in economic 

impacts to society; however, these impacts are difficult to 

quantify. The goal of this workshop was to identify methods 

and solutions needed to develop robust and reliable estimates 

of the value of EOs in decision making. This is needed to 

assess and prioritize investments in EO research, development, 

and operations. To advance the state of the science and test 

a value-chain/decision-tree framework, five use cases were 

examined to understand the crosscutting methodological elements for assessment.

The long-term objective of this workshop is to lay a foundation for the consistent valuation of EO within and across 

government agencies and other organizations. This document 

describes the workshop proceedings, the results of the breakout activity, and significant findings and future directions 

for the GEOValue Community. The main body of the report 

provides proceedings from the workshop in the next “Meeting 

Summary” section. After that section, findings and next steps 

are provided.

Meeting Summary

The “Demonstrating the Value of Earth Observations: 

Methods, Practical Applications and Solutions” workshop 

was held as a GEO Plenary side event on October 23–24, 

2017, in Washington, D.C. The 60 participants attending the 

workshop were primarily from U.S. academia and government backgrounds, including the USGS, NOAA, National 

Aeronautics and Space Administration (NASA), U.S. Environmental Protection Agency, East Carolina University, and the 

University of New Mexico. Nongovernmental organizations 

were also represented, including Resources for the Future 

(RFF). Multiple private and international organizations were 

also represented, including the World Bank, ESA, EARSC, 

the European Commission, as well as private companies such 

as Esri and ACI Consulting. Participants represented multiple domains including natural sciences, social sciences, and 

economics. A list of attendees and their contact information is 

provided in appendix 1, table 1.1. The meeting was facilitated 

by Aimee Cooper (USGS) pursuant to the agenda (the detailed 

agenda is available in appendix 2).

Welcome Address

Monica Grasso (Chief 

Economist, NOAA) welcomed workshop participants 

and introduced the agenda, 

noting that the first day of 

the event would focus on the 

theoretical basis for valuing EO, whereas the second 

day would be a working 

session to develop a set of 

value chains/decision trees. 

Grasso noted the importance 

to NOAA of valuing EO 

considering NOAA’s role in collecting EO.

Carl Shapiro (Director 

of the Science and Decisions 

Center, USGS) noted that the 

USGS operates in a multidisciplinary environment. 

Because many government 

agencies make decisions 

in this environment, it is 

important to communicate 

and demonstrate the use and 

value of scientific information within and across these 

environments. He added that during the morning session, the 

invited presenters would address methods and practices; then 

together, participants would look at the value-chain/decisiontree framework and how to identify the source of value. 

Shapiro explained that the second day would be focused on 

applications. Five examples that are important to the attendees 

and the USGS would be considered in terms of the valuechain/decision-tree perspective. Lastly, Shapiro discussed how 

Monica Grasso and he would moderate a discussion of strategies for valuing future EO to identify future directions for the 

community.

Alessandra Tassa 

(ESA) welcomed participants next. The ESA builds 

Earth observing satellites 

and operates them (for 

example, the Copernicus 

Sentinels, CryoSat, Gravity field and steady-state 

Ocean Circulation Explorer) 

or hands them over to the 

European Organization for 

the Exploration of Meteorological Satellites or the 

European Commission. As a provider, ESA is an enabler of the 

benefits from EO; however, Tassa mentioned that ESA knows 

Monica Grasso, NOAA.

Photograph credit: Jay Pearlman. Used with permission.

Carl Shapiro, USGS.

Photograph credit: Jay Pearlman. Used with permission.

Alessandra Tassa, ESA.

Photograph credit: Jay Pearlman. Used with permission.
Meeting Summary 7

too little about what users do with their data. This is especially 

true for data distributed under a completely free and open data 

policy like the ones from the Copernicus Sentinel satellites. 

She stated that there is pressure to provide evidence about the 

contribution of satellite data to the economy, addressing the 

value chain/decision tree from satellites to citizens. Highlighting the link between citizens and satellites has been compelling in demonstrating the value of their data.

Finally, Geoff Sawyer (EARSC) welcomed 

participants. He explained 

that EARSC represents 

the space and technology 

industry. Sawyer discussed 

how most studies to date 

have been based on topdown macroscale analysis. 

EARSC, with the ESA, has 

been working on a bottom-up 

value-chain approach based 

on a single product leading to 

an actionable decision. He added that this has been presented 

at the GEO work plan symposium in Pretoria, South Africa, 

leading to the request to establish a side event in Washington, 

D.C. He was happy that this had led to the joint event starting that day. Lastly, he discussed his intention for continued 

engagement and referenced the GEOValue Community.

After the introductions from the workshop organizers, 

participants briefly introduced themselves and described their 

interest in attending the event.

Geoff Sawyer, EARSC.

Photograph credit: Jay Pearlman. Used with permission.

Panel 1—From left to right: Andreas Veispack, Stephane Hallegatte, Andrew Coote, and Alan Smart.

Methodologies—Session 1

Steve Ramage (GEO Secretariat) introduced the first 

session on methodologies, which included the following 

presentations:

• Andreas Veispak, “Demonstrating the Value and Benefits of the Copernicus Programme” (Veispak, 2017).

• Alan Smart, “Estimating the Value of Earth Observation—Methodologies” (Smart, 2017).

• Stephane Hallegatte, “Simple Assessments of the Benefits from Early Warning Systems and Stronger HydroMeteorological Systems” (Hallegatte, 2017).

• Andy Coote, “Value Chain and Cost-Benefit Analysis: 

Applied to 3D Geo-Information” (Coote, 2017).

Veispack presented a study on demonstrating the value of 

Copernicus (Veispak, 2017). Veispack is head of the European 

Commission’s Space Data for Societal Challenges and Growth 

Unit. The European Copernicus program monitors the environment and security using six dedicated Sentinel satellites 

and a set of contributing missions. It provides six Copernicus 

services (land, marine, atmosphere, climate change, emergency management, and security). All data are distributed 

following a free, full, and open data policy. The program has 

cooperation agreements with peer-to-peer data hubs in the 

United States and Australia. They have a budget of 4.3 billion 

euros for 2014 through 2020.

The value chain spans the space and in-situ data provided 

by the ESA, the European Organization for the Exploration of 

Meteorological Satellites, the Copernicus services, and others. 

Downstream services are tailored for users. The European 

Commission’s aim is to optimize the benefits that space technologies bring to society and the wider European economy. As 

budgetary constraints grow, policymakers put greater emphasis on the usefulness of space technologies.
8 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

Three complementary approaches are used to develop 

value chains: case studies, market reports, and ex-ante evaluation. The bottom-up case studies developed by EARSC and 

ESA are used to illustrate this strategy. The resulting estimates 

are robust and quite specific; however, extrapolation is not 

always easy, and the resulting estimates are conservative and 

labor intensive. 

The second approach focuses on market reports and 

includes the following phases:

• Characterizing the value chain,

• Mapping the players in the value chain,

• Selecting a representative sample of users,

• Engaging sampled users in direct interviews, and

• Extrapolating results to all users.

The third approach is an ex-ante benefit evaluation. An 

example of this approach centers on impact pathways for 

crop monitoring. A methodology is designed for each impact,

including hypotheses on uptake, projected growth of the market, and societal valuation. The Copernicus benefits are estimated for each impact, and the results are aggregated. Ex-ante 

estimates are comprehensive (including economic, societal, 

and environmental benefits) and useful for decision making; 

however, many hypotheses are needed, and the reliability 

decreases with long time horizons. Some of the challenges are 

associated with double counting across sectors, and long-term 

unknowns (for example, how do you quantify time series 

value and how do you establish a price based on autonomy 

and independence?).

Alan Smart is a senior associate for ACIL Allen Consulting, in Sydney, Australia. He gave a brief overview of the 

methodologies associated with estimating the value of EO and 

discussed an example from Australia (Smart, 2017). Smart distinguished between the use value, which is direct, application 

related, and where someone makes use of the information; and 

the nonuse value, which is subjective, and is associated with 

such concepts as satisfaction and preservation of a good or 

service. The Earth Observation from Space value chain starts 

with data acquisition; includes processing, storage/archiving, 

and extracting information; and concludes with user products 

and services. Users are grouped into categories such as government, industry, and research.

One approach for estimating the value of EO is to 

consider how the use of this information can shift “production possibility frontiers,” increasing total production in the 

economy. The economic contribution of EO can be estimated 

by comparing total production in a reference case that includes 

production associated with EO to a counterfactual case that 

excludes it. The benefit attributable to EO is the difference in 

total production under the two scenarios.

Using input-output models, direct and indirect impacts 

can be estimated; these models are limited, however, in 

that they are static and do not account for the ability of the 

economy to adapt to changes over time. This limitation can be 

overcome by using dynamic computable general equilibrium 

models, which account for the ability of the economy to adapt 

to change and are better for assessing the productivity changes 

associated with the use of EO.

Smart concluded by presenting the report entitled “The 

Value of Earth Observations from Space to Australia” (ACIL 

Allen Consulting, 2015) which includes direct and indirect 

effects. This report highlighted the importance of weather 

forecasts for farmers, ocean observations for the Great Barrier 

Reef, and the price of water for improved water management.

Stephane Hallegatte presented “Simple Assessments of 

the Benefits from Early Warning Systems and Stronger HydroMeteorological Systems” (Hallegatte, 2017). Hallegatte works 

in the Global Facility for Disaster Reduction and Recovery 

program at the World Bank. He opened his presentation by 

noting that the value of a weather forecast depends on who 

uses it and for what purpose. He stressed the complexity of 

assessments, which includes the multiplicity of timescales, 

multiplicity of actors, and multiplicity of use. For example, 

a flood brings different and unexpected decision-making 

responses from people, such as whether there is time to move 

the piano or the vacuum cleaner. For this reason, interaction 

with data users needs to be a priority during design.

A framework can be used for assessing the value of early 

warning systems to determine the economic loss corresponding to a 30-minute warning, 1-hour warning, and so on, comparing the expected losses under each scenario. Loss reductions (that is, economic value) do not increase linearly with the 

lead time or the quality of the forecast. Imperfect forecasts are 

difficult to use, especially if they result in false alarms, which 

can result in citizens ignoring future alarms. The value of a 

forecast depends on the cost and benefit of early actions and 

must account for unexpected human behavior.

Andrew Coote presented the “Value Chain and CostBenefit Analysis: Applied to 3D Geo-Information” (Coote, 

2017). Coote is a consultant for ConsultingWhere Ltd. He 

discussed how the quantification of socioeconomic benefits 

is increasingly critical in making the business case for EO 

projects. Value-chain analysis and cost-benefit analysis are 

well developed and understood general methodologies, which 

can be applied where geoinformation is the primary deliverable. These methodologies work best when applied to welldefined use cases with good sources of primary evidence. The 

VOI should not be confused with the value of benefits from 

policies, systems, or both, that use it in decision making (the 

apportionment problem). There is almost always alternative 

evidence to support decisions, and this counterfactual scenario 

must be considered in valuation; an information source is 

only worth the “delta” in value between it and the next best 

alternative.

The Environmental Value Reference Inventory 

(https://www.evri.ca/) is a database with empirical studies on 

the economic value of environmental assets that demonstrate 

the use of a wide range of methodologies. The 3D geoinformation case study was undertaken for EuroSDR (a research 

body funded by National Mapping and Cadastral Agencies) 
Meeting Summary 9

to identify potential use cases and apply either a value-chain 

analysis or cost-benefit analysis. For each use case, a workshop approach was used to identify the actors, the information 

they produce, and the processes where value is added. The 

resulting value chain can be very complex.

Cost-benefit analysis is commonly used to help assess the 

business case for investment in a project or proposal. It provides a means of objective comparison between projects with 

different costs, benefits, and durations. Three methods can be 

used on the benefits side: cost avoidance, case-study evidence, 

and benefits transfer. Coote concluded his remarks by stating 

that we are not alone in seeking solutions to information quantification, and we must learn from environmental economists 

and transport engineers. Databases similar to the Environmental Value Reference Inventory are needed for EO.

Steve Ramage 

started a short discussion with the panelists. 

He discussed how there 

is a lack of agreement 

on how to measure the 

VOI. Is gross domestic 

product the right unit 

of measure? Others, but 

relatively few, use the 

concept of happiness 

(Bhutan, for example) 

as a measure of societal 

wellbeing. Virtually all of Google (and its high value) is information, but that is difficult to put on the balance sheet.

One panelist described the need to incorporate communication experts into reporting the VOI. Another panelist mentioned that one needs to focus on the audience (for example, 

decision makers) when developing narratives that explain the 

importance of EO. The panelists agreed that space technology, information technology, and other disciplines must work 

together to design and execute value of EO studies.

Methodologies—Session 2

Steve Ramage introduced the second session, which 

included the following presentations:

• Rudy Schuster, “Communicating the value of Landsat 

Imagery Using Case Study Narratives” (Schuster and 

others, 2017).

• Aanchal Anand, “The Economic Value of Geospatial 

Information: An Albania Case Study” (Anand and 

Kelm, 2016).

• Rich Bernknopf, “A Decision Framework for Quantifying the Economic Value of Information (VOI) of Earth 

Observation: Case of the NASA Gravity Recovery 

Steve Ramage, GEO.

Photograph credit: Jay Pearlman. Used with permission.

and Climate Experiment (GRACE) Enhanced Drought 

Severity Index” (Bernknopf, 2017).

• Geoff Sawyer, “A Bottom-Up Approach to Assessing 

the Value of Satellite EO Data” (Sawyer, 2017).

• Gerry Kinn, “Esri Perspective” (Cummens and Kinn, 

2017).

Rudy Schuster 

presented “Communicating the Value 

of Landsat: Imagery 

Using Case Study 

Narratives” (Schuster 

and others, 2017). 

Schuster is branch 

chief of the Social and 

Economic Analysis 

Branch at the USGS. 

His team has been 

working continuously 

with land remote 

sensing since 2007 to 

better understand the users, uses, and value of Landsat imagery. This project includes two main components: (1) surveys 

of Landsat imagery users in the United States and around the 

world and (2) case studies of the value of Landsat imagery. In 

total, 35 case studies on Landsat imagery use have been completed. These studies enrich understanding by providing context for the economic-benefit modeling. These case studies are 

a combination of investigative journalism, economic analysis, 

and quantitative evaluation of benefits. The case studies are 

organized into categories such as agriculture, forestry, technology, environment, humanitarianism, and water. Schuster 

described four specific examples: the search for water in West 

Darfur, innovations with Landsat, Landsat use by a forest 

management startup, and improving irrigation technology and 

grape and wine quality. It is important to complement communication of value by communicating the scientific context for 

those values.

Aanchal Anand 

presented on the “Economic and Financial 

Analysis of Geospatial 

Information: The Albania Case Study” (Anand 

and Kelm, 2016). 

Anand is a member of 

the World Bank Group, 

Global Land and Geospatial Team. Albania 

is a small country with 

many infrastructure 

problems. To address 

Rudy Schuster, USGS.

Photograph credit: Jay Pearlman. Used with permission.

Aanchal Anand, World Bank Group. Photograph credit: Jay Pearlman. Used with permission.
10 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

this, an integrated land and geospatial infrastructure project is 

being planned. Albania has a new dedicated national spatial 

data agency, Autoriteti Shtetëror për Informacionin Gjeospazial (translated “State Authority for Geospatial Information”). 

A component of this project is the creation of an integrated 

geospatial data system for Albania that is consistent with 

European standards for National Spatial Data Infrastructure. A 

first step is the acquisition of rights to use a cadastral dataset 

showing the ownership and other attributes of land.

Richard Bernknopf presented “A Decision Framework for 

Quantifying the Economic Value of Information (VOI) of EO: 

Case for a NASA Gravity Recovery and Climate Experiment 

(GRACE) Enhanced Drought Index” (Bernknopf and others, 

2017). Bernknopf is a research professor in the economics 

department at the University of New Mexico, Albuquerque. 

He discussed how the U.S. Agricultural Act of 2014 identified 

the U.S. Drought Monitor (USDM) drought-severity classification to determine eligibility for drought disaster assistance. 

He described the linkage between the Gravity Recovery and 

Climate Experiment (GRACE) satellites and the USDM updating and production process. The GRACE satellites are used to 

monitor gravity to detect variations in the Earth’s mass that are 

due to surface and groundwater storage changes. An ensemble 

of GRACE data and a catchment land surface model provide 

spatial water storage information. Three weekly GRACE data 

assimilation drought indicators are produced: surface soil 

moisture, root zone soil moisture, and groundwater. This study 

investigated the possibility of including GRACE indicators in 

the USDM and the usefulness of doing so. Information from 

the USDM is used by the U.S. Department of Agriculture in 

identifying regions for drought assistance.

A retrospective analysis of drought severity classifications was performed with and without GRACE data. A 

conceptual framework for estimating the socioeconomic value 

of GRACE information products was developed to evaluate 

the correlation between economic impact and the quality of 

geospatial information. Adding GRACE indicators reduced 

the number of high-value prediction errors. Statistical tests 

indicate that use of the three GRACE indicators in the drought 

monitor formulation increased the correlation between farm 

income/corn yield and the USDM. Also, goodness-of-fit criteria indicate statistically significant improvements.

Geoff Sawyer presented “A Bottom-Up Approach to 

Assessing the Value of Satellite EO Data” (Sawyer, 2017). He 

is the Secretary General of the EARSC, a membership-based, 

European trade association that provides business intelligence 

to their members, maintains knowledge of the industry, and 

promotes the industry and its capabilities. Sawyer discussed a 

study EARSC is performing on behalf of the ESA, quantifying 

the economic value created through the use of satellite data 

(see Sawyer and others 2016a and 2016b). In this study, a bottom-up, product-based approach is used working through the 

value chain. A counterfactual was obtained by considering the 

approach that was used before satellite imagery was available. 

The effort, in part, is to reach out to the level of the citizens so 

information regarding willingness to pay can be gathered.

Three case studies and reports were published (see 

http://earsc.org/library/media-material): Synthetic Aperture 

Radar imagery for ice-breakers in the Baltic Sea, optical data 

for forestry in Sweden, and Synthetic Aperture Radar interferometry providing ground displacement maps used to monitor 

gas pipelines in Netherlands. The following steps were used 

for each case study:

• Identify the information type, characterizing the value 

chain and how it benefits each user;

• Develop a model that allows the benefits to be assessed 

in economic terms;

• Assess how much of the value can be attributed to the 

use of satellite data;

• Identify factors that should be considered when 

extrapolating results; and

• Calculate the economic value for the product.

Sawyer noted that, where assumptions are made, they 

should be visible and validated as much as possible. The ability to measure the benefits in economic terms is also important. The value chain for ice breaker ships was discussed as an 

example. As the ice breaker guides ships through the ice to a 

port, delays and potential loss of cargo are reduced. The use 

of satellite data allows ice breakers to optimize the routes. As 

in all these cases, expert interviews are used to back-up desk 

research. Strong engagement of the primary user is a necessity 

to develop cases.

For this (and other) use cases, the contribution of imagery 

is shown in economic terms. A model is used to translate the 

reality into economic benefits. The model may be statistical as in the ice navigation case, financial as in the pipeline 

infrastructure case, or economic as in the forestry case. Further 

cases to be analyzed will enable an understanding of how 

generic or transferable each of these models will be. It is suspected that they are each highly specific to the case.

Gerry Kinn presented Esri’s perspective on valuing EO 

methodologies (Cummens and Kinn, 2017). He discussed how 

a key part of working with the imagery and understanding the 

value of imagery is to be able to make the collected imagery accessible to the many users that need this information. 

Clearly, the value of imagery needs to exceed the cost of the 

investment. In the time before imagery, weather caused many 

fatalities because we did not have the ability to forecast the 

severity of storms. With imagery we can predict, assess, and 

provide information to make decisions in many situations.

Imagery archives are time machines that highlight circumstances that would have otherwise been missed. Users are 

not only interested in the imagery, or geographic information 

system, but also about using the two together. In the last couple of years, the publishing of maps has changed; for example, 

story maps have increased in popularity and are being produced every day. In their presentation, Kinn expressed the 

need to communicate the value of our work more effectively. 

He presented an example from the Chesapeake Conservancy 
Meeting Summary 11

showing that multiple scales of information are important—

medium-scale data can identify issues and even assist policymaking, whereas high-resolution data can be used to produce 

land-cover/land-use mapping and to inform site-specific 

actions. Remote sensing should be about image analysis, not 

technology because a lot of other contextual information is 

needed to complete the analysis.

Steve Ramage, moderator of session 2, started a short 

discussion with the participants. He asked why none of the 

presenters mentioned the financial services sector. Participants 

discussed how financial systems are very complicated and 

sharing information and making modifications to the system is 

difficult.

Introduction to Value Chains/Decision Trees and 

Processes Panel—Session 3

Emily Pindilli introduced the third panel, which introduced the value-chain/decision-tree framework. Panelists 

included the following:

• Tim Stryker

• Jeff Adkins, “Economic Valuation of NOAA Products 

& Services: A Value Chain Approach” (Adkins, 2017).

• Jamie Kruse, “Valuation of Geospatial Information”

• Yusuke Kuwayama, “The Value of Value Chains for 

Evaluating the Socioeconomic Benefits of Earth Observations” (Kuwayama, 2017).

Tim Stryker described the use of EO at the USGS. He 

stated that EO is critical information infrastructure; we need to 

find better ways of characterizing its socioeconomic impacts 

because without it, lives will be lost, properties will be damaged, and the economy will be harmed. The U.S. Congress 

has directed the Office of Science and Technology Policy to 

develop a triennial National Plan for Civil Earth Observations, which prioritizes Federal agency activities in accordance 

with societal benefit. He emphasized the importance of a 

wide range of observing systems that together help generate 

forecasts, warnings, and other environmental analyses. For 

example, NOAA’s tsunami-warning systems depend on data 

from NOAA’s and various other agencies’ observing systems. 

Because of these dependencies, it is important to be as granular as possible when characterizing the benefits of individual 

EO systems.

Jeff Adkins described economic valuation of NOAA 

products and services (Adkins, 2017). He is an economist 

working with NOAA’s Chief Economist’s team. Adkins has 

completed three studies on the VOI. He discussed how the 

value of goods and services produced by the Government lies 

in their use to change societal outcomes for the better. This is 

done by increasing productivity, lowering costs, and reducing 

losses from natural disasters. The value-chain approach that 

was described in this presentation reflects this relationship 

between the production of goods and services, the consumption of those goods and services, and the associated societal 

impacts.

In a simple model, observational platforms equipped 

with data-collecting sensors are launched and operated. The 

collected data have to be put into a usable format, stored, and 

made accessible to analysts. These data are then analyzed, 

producing information used to generate final products and 

services. Ongoing research supports all aspects of this work, 

from the design and manufacturing of observational platforms 

and sensors to the delivery of final products and services. The 

latter includes, for example, research in risk communication 

that helps users translate information into beneficial protective 

actions.

As we move into the demand part of the model, all the 

investments required to generate final products and services 

that generate value are measured against the impacts they 

have in improving societal outcomes. It is important to note 

that the demand side is different for each user. In assessing the 

value of a product or service, it is critical to know who uses 

it, how they use it, and how they benefit from its use. It is also 

important to know threshold values and degrees of change that 

are needed to change societal outcomes. An important question to ask is, “Where does an improvement in quality make a 

difference?”

Panel 3 (left to right)—T. Stryker (USGS), J. Adkins (NOAA contractor), J. Kruse (East Carolina University), and Y. Kuwayama (RFF).
12 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

Some of the products and services that NOAA produces 

are used directly by society. Others are used by intermediaries 

who produce value-added products and services that provide 

additional societal benefits. For example, NOAA’s weather 

information and the underlying data and models provide the 

foundation for an additional $1.7 billion in investments annually by the private weather information sector (U.S. Department of Commerce, 2014). In conclusion, Adkins added that it 

should be noted that research has value by itself, which creates 

another value stream.

Jamie Kruse is a professor at the East Carolina University 

Center for Natural Hazard Research. During her presentation, 

she addressed several questions:

• Do we all mean the same thing when we say valuation?

• What is being “valued?”

• Who is the VOI exercise for?

• And what is the purpose of the VOI exercise?

Developing a value chain is a multidisciplinary effort. 

Kruse discussed examples of decisions that were made in 

response to two natural disasters: Hurricane Matthew and the 

flooding of the Tar River in Greenville, North Carolina. Measurable differences in outcomes when geospatial information 

is included can be characterized by the following:

• Number of lives saved,

• Improved mental and physical health outcomes,

• Reduced property damage,

• Reduced disruption of economic activity, and

• Reduced business interruption.

In conclusion, Kruse discussed attribution of the value—

the incremental benefit of a specific decision-support system 

or dataset.

Yusuke Kuwayama is Director of Socioeconomic Studies 

for the Consortium for the Valuation of Applications Benefits 

Linked with Earth Science cooperative agreement between 

RFF and NASA. He shared a generic representation of a 

value chain for EO (Kuwayama, 2017). He then shared two 

examples. The first example addressed integrating GRACE 

and GRACE follow on data into river flow and flood forecasts. 

The value chain expresses the value of avoided flood damages from mitigation actions that would take place as a result 

of improved knowledge of precursor terrestrial water storage 

and subsequent flow forecasts for the Red River of the North. 

The actual historical information was compared with a current 

forecast and retrospective simulations. The second example is 

about climate observing systems, looking at the value of the 

proposed Climate Absolute Radiance and Refractivity Observatory system relative to current space borne systems.

Emily Pindilli, the Natural Resource Economics Lead at 

the USGS Science and Decisions Center moderated session 3. 

Pindilli started a short discussion with the participants on use 

cases. She discussed how the use cases provide an anchor to 

reality. Value chains/decision trees are useful frameworks to 

help understand where the value for data comes from, particularly regarding a policy perspective. During the discussion, 

there was a mention of the “garden of forking paths.” For 

example, when considering a flood situation, the flood could 

be related to an ice dam or to another cause for high soil moisture; therefore, it is important to define the scope of decisions 

and benefits.

The question regarding why we do not see more value 

studies also came up. The panel discussed that these studies 

are primarily conducted at the end of the research process, 

once the objective systems have been funded. Through econometric analysis, we are able to extract information that we 

could not access otherwise. It was suggested during the panel 

discussion to look at the information that program managers 

need, what measurements are needed, and how products and 

services lead to a value tree.

In conclusion, the panel discussed approaches to identifying who is using your products. Taking the approach of 

an investigative reporter was suggested, and some strategies 

include looking at web statistics, and emailing questions and 

sending surveys to users.

Value Chains/Decision Trees Forum—Session 4

Jay Pearlman, 

Director, FourBridges, 

opened the fourth session, an open discussion. He stated that 

each team would be 

requested to provide a 

report addressing the 

basic structure of their 

value chain/decision 

tree, the challenges, 

the data requirements, 

and any unanswered 

questions. He discussed 

how with the transition 

toward open data, there 

is a change in paradigm. With this change, we find ourselves 

asking, “Who are the users and in what context are they using 

the data?” The value is easier to understand if it is measured 

within a particular sector. In all cases, the human is at the end 

of the value chain/decision tree.

Carl Shapiro suggested that one should start from the 

final products and services of the value chain and how they are 

used. He added that how we use the value chain is critical; not 

only do we have different methods between domains, but we 

also have different vocabularies. Jeff Adkins mentioned the 

need to focus on the production component to attribute value 

to inputs to production; “denial of data” experiments are quite 

useful because they illustrate how much worse off one would 

be without the data.

Jay Pearlman, FourBridges. 

Photograph credit: Jay Pearlman. Used with permission.
Meeting Summary 13

Andrew Coote stated how EuroSDR approached the 

value chain systematically, decomposing the components 

according to a work breakdown structure and looking at the 

added value starting with the supply chain. Monica Grasso 

shared that she is looking for information that she can take 

back to the NOAA leadership. Alessandra Tassa discussed how 

we need to go beyond economic quantification and increase 

the emphasis on narratives that help decision makers understand and interpret results.

Value-Chain and Decision-Tree Working Groups

During this series of breakouts, each participant was 

assigned to one of five groups to develop a value chain/decision tree for a predetermined science application. Each group 

had 1 hour to consider its science application. In the next 

hour, each group identified the data needs associated with that 

same question. Each team worked with a trained facilitator to 

develop a value chain/decision tree and discuss data needs. 

They then summarized their findings and reported back to the 

entire group once the workshop reconvened. The discussion 

and findings of each of the groups are detailed below. The 

value chains/decision trees should be considered preliminary 

because they are largely based on the brainstorming from a 

short break-out session. The writing team revised value chains/

decision trees for clarity.

Group 1—Effect of Increasing Temperatures on 

Human Health

The first group included experts from diverse disciplines 

and perspectives (see table 1). They started at the end of the 

value chain/decision tree and discussed the effects of heat 

stress on the cardiovascular system during a heat wave. They 

interpreted the topic without an example of an existing product 

or set of information, rather as a what-if scenario. The group 

discussed a public-alert system as a near-term solution and a 

mitigation system for human health as a long-term solution.

Table 1. Group 1 participants.

Name Organization

Rich Bernknopf University of New Mexico.

Vankita Brown1 National Oceanic and Atmospheric 

Administration.

John Firth Acclimatise.

Pierre Glynn2 U.S. Geological Survey.

Al McGartland U.S. Environmental Protection Agency.

Bob O’Connor National Science Foundation.

Rajendra Poudel National Oceanic and Atmospheric 

Administration.

Geoff Sawyer European Association of Remote Sensing 

Companies.

Rudy Schuster U.S. Geological Survey.

1

Facilitator.

2

Rapporteur.

Regarding applications, the group discussed a traffic 

management system, which could minimize air pollution during a heat wave. The information needed for this application 

includes simplified material for use by decision makers and 

the general public. This would include graphics presenting 

data (heat stress days for example) and analysis and synthesis 

for various kinds of data into models (water data, medical 

data, and others). The challenges that the group discussed in 

this application include the following:

• Narrowing the scope,

• Defining indicators of success (different kinds of success),

• Performing user-centric design.

• Performing counterfactual management,

• Reducing the number of false positives,

• Multiple feedbacks,

• Short-circuits, and

• Garden of “forking paths.”

Questions that arose during this discussion focused 

around defining the counterfactuals. The group asked, “How 

do you define the counterfactual?” It is a hypothetical system 

or do you plan for something that could happen. The group 

discussed potential examples, such as the management of the 

traffic light system, management of emergency vehicles, or 

both.

An initial value chain/decision tree for this topic is shown 

in figure 4. To the far left, the types of observation systems, 

both satellite systems and in-situ monitors, are listed that 

would provide useful information for reducing the impact of 

Photograph credit: Jay Pearlman. Used with permission.

increasing temperatures on human health. Moving to the right 
14 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

are the specific types of data that the group discussed would be 

useful. The analytical tools such as weather forecasts are the 

next step in the value chain/decision tree. The decision-ready 

information and the final information product are identified 

next. This is the complete supply side of the value chain for 

this topic.

The breakout group discussed how the information could 

be used in terms of an actual decision. The right side of figure 

4 represents the potential outcomes and values associated 

with having the data and the counterfactual if the data are not 

available. The group discussed the need for information for a 

public health alert system. If the information is not precise, it 

is possible (with some unquantified probability) that alerts will 

occur too frequently. This will lead to unnecessary sheltering and associated costs. It is also possible that with many 

unneeded warnings, people may become less responsive to 

warnings and that could in turn result in health effects. On the 

contrary, not enough information could lead to an alert system 

that does not provide warnings when it should. This has risks 

associated with human-health effects and the associated costs. 

Perfect information would support optimization of the alert 

system and that would balance the risk to human health with 

the costs associated with sheltering. The breakout group also 

began another branch on the decision tree (right side) of the 

value chain for which they considered applying the information in a traffic management system. In that case, perfect 

information would support optimization of traffic controls to 

reduce emissions during high-heat events leading to reduced 

human-health effects. The counterfactual (without information) was not developed during the session. The preliminary 

value chain/decision tree helps to consider how weather and 

temperature information could be used to reduce human-health 

effects, who the users might be, and the value of collecting 

and analyzing additional information.

Group 2—Flooding—Mitigating. Managing, and 

Avoiding Impacts to Safety and Property Damage

The second group included hydrologists, economists, 

and engineers (table 2). They addressed the flood issue with 

a specific focus on Hurricane Matthew, which resulted in 

inland and coastal impacts. They worked backwards, asking 

who the actors are and what decisions and processes should 

be resolved. There were several phases to consider: pre-event 

planning and preparedness, response activities, recovery 

phase, and economic impacts. After approaching the flood 

issue at a high level, they went into detail to select a single 

thread, isolating one actor and one decision—focusing on a 

dam operator.

Photograph credit: Jay Pearlman. Used with permission.

Table 2. Group 2 participants.

Name Organization

DaNa Carlis1 National Oceanic and Atmospheric 

Administration.

Nancy Colleton Institute for Global Environmental 

Strategies.

Andrew Coote ConsultingWhere Ltd.

Pat Cummens Esri.

Jason Gallo Science and Technology Policy Institute.

Monica Grasso National Oceanic and Atmospheric 

Administration.

Robert Mason U.S. Geological Survey.

Francoise Pearlman FourBridges.

Tim Stryker U.S. Geological Survey.

Toste Tanhua Global Ocean Observing System.

1

Facilitator.

Residents being evacuated from high flood waters.

Photograph credit: Coastal and Inland Flooding Observation and Warning Project (https://ciflow.nssl.noaa.gov/), NOAA. Used with permission.
Figure 4. Effects of increasing temperatures on human-health value chain/decision tree.

Public alert 

system

False positive alert

Optimal alert

False negative alert

Decision point Alternatives Outcomes Probabil

Unnecessary sheltering; credibility 

reduced

Alert and intervention is timed for 

minimizing public health risk

Public health risks

?

%

?

%

?

%

Optimal alert Alert and intervention is timed for minimizing public health risk ?% 

Without 

information

With information

Ocean buoys

Public alert 

Social media system

Temperatures

Risk analysis

Heat stress 

days, 

demographics, 

migration 

opportunities

Weather 

forecast

Observation 

platform

Data Analysis Information Final products/ services

Traffic 

management 

system

Mitigated traffic flows Lessen air pollution and exposure; emergency vehicles prioritized ?% 

With 

information

Healthcare 

capabilities

Meteorological 

observations

Satellites

Health 

treatments

Traffic 

conditions

Air quality

Census

Trade-off 

analysis

Optical 

sensors
16 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

Looking at the supply chain, group 2 considered the 

decisions being made (which include when to release water 

from the dam, how much to release, and for what duration), 

what information the dam operator needed to make a decision 

(hydrology, upstream data, downstream data, and reservoir), 

and the systems providing the information (platforms, sensors, 

and decision-support systems).

The group identified several challenges in determining 

the VOI for this application:

• There are multiple criteria to be applied regarding 

multiple decisions or parts of decisions that eventually 

need to be merged.

• The situation is highly complex.

• There is a need for a wide variety of expertise.

• There is a risk of double counting.

• Federal dam operators have a Federal plan to comply 

with, leading to interplay between policy and decisions.

A question that arose during this discussion included 

looking at a complexity and authority chain—who is making decisions and where? Also, how is the decision modified 

by information sharing and communication? The decision 

tree developed by the group (fig. 5) included three branches: 

one for a decision on dam release, a second for emergency 

management response, and a third for flood-plain management. The dam release branch was the most developed. The 

group identified the counterfactual scenario (without information) and the possibilities that there could be too much 

water released associated with flooding downstream or too 

little water released leading to damage to the dam itself. With 

perfect information, the release of water could be optimized to 

balance all the risks and associated costs.

Group 3—Harmful Algal Blooms—Effects on 

Human Health, Recreation, and Tourism

The third group focused on an early warning forecast for 

HABs. The forecast incorporates upstream models, which use 

in-situ and satellite data, some of which were produced for 

other purposes. The group considered the information product 

users and the beneficiaries, which include drinking water producers, aquaculture operators, wild fisheries, municipalities, 

charter boat operators, and recreationists. Participants included 

hydrologists, economists, and data managers with expertise in 

HABs (table 3).

Table 3. Group 3 participants.

Name Organization

Jim Boyd National Socio-Environmental Synthesis 

Center, Resources for the Future.

Max Craglia European Commission, Joint Research 

Centre.

Jennifer Graham U.S. Geological Survey.

Yusuke Kuwayama Resources for the Future.

Doug Lipton National Oceanic and Atmospheric 

Administration.

Lou Nadeau Cooperative Research Centre for Spatial 

Information.

Michael Ott Intergovernmental Oceanographic 

Commission.

Emily Pindilli1 U.S. Geological Survey.

Theodore Stawecki LimnoTech.

Steven Thur2 National Oceanic and Atmospheric 

Administration.

1

Facilitator.

2

Rapporteur.

MODIS (aqua) satellite image of Lake Erie harmful algal bloom, 

August 22, 2015.

Photograph credit: NOAA Great Lakes CoastWatch (https://www.flickr.com/photos/noaa_glerl/23597606861/in/album-72157639592150973/). Used with permission.
Figure 5. Flooding: Mitigating, managing, and avoiding impacts to safety and property damage value chain/decision tree.

Dam 

release

Too much release

Optimal release

Too little release

Decision point Alternatives Outcomes Probability 

Increased flooding downstream

Water release is optimal in 

quantity, timing, and duration

Potential dam damage, dam 

flooding

?%?%?%

Optimal release Water release is optimal in quantity, timing, and duration ?% 

Without 

information

With information

SST6, 

winds, 

pressure

Hurricane 

forecast

Hydrologic 

modeling Winds, stream 

flows, river 

levels, 

reservoir 

levels, 

capacity

Weather 

forecast

Observation 

platform

Data Analysis Information Final products/ 

services

Emergency 

management

response

Optimal emergency 

management

First responders, law 

enforcement deployed 

optimally

?% 

With 

information

Floodplain 

management Optimize zoning, insurance underwriting Limited property exposure to flood risk ?% 

With 

information

GOES

satellite2

NEXRAD 

radar3

ARGO 

floats4

USGS 

streamgages

Sondes5

Mesonets1

Tide gages

Mixed 

layer depth

Wind 

profiles, 

moisture

Precipitation

Stream 

levels, 

flows

Definitions: 1. A network of automated weather and environmental monitoring stations that observe mesoscale meteorological phenomena; 2. National Oceanic and Atmospheric Administration's Geostationary Environmental Satellite System; 3. National Oceanic and Atmospheric Administration's Next Generation Weather Radar; 4. International ocean-observing system of drifting floats that gather temperature and sa

the world’s oceans. 5. Multi-parameter water monitoring systems; 6. SST = sea surface temperature.
18 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

Photograph credit: Jay Pearlman. Used with permission.

During the discussion, participants considered the longevity of the VOI if the goal is to avoid HABs; eventually we 

will not benefit from early warning systems. Participants also 

discussed if public confidence in the government and information could be accounted for.

The value chain/decision tree that the group developed is 

shown in figure 6. The final information product that was used 

to consider the decision-tree branches was an early warning 

system that relies on satellite imagery, in-situ observations, 

and additional analytic capabilities. Five different branches 

were considered with drinking-water management being the 

most developed. In the case of drinking-water management, 

participants identified the different decision paths that might 

occur without information. It is possible that there could be 

too much treatment (that is, too many chemicals or starting 

treatment before needing to) or too little treatment. In the case 

of too much treatment, there are costs associated with the 

treatment itself and potentially alternative sources of water 

(such as bottled water). If there is too little treatment, there 

are human-health risks including gastrointestinal illness and 

amnesia; there are also less well understood long-term health 

risks. For this application, perfect application can support 

the optimization of balancing intervention costs with humanhealth risks. The value of cyanobacteria HABs science is 

currently being researched at the USGS to better understand 

users, priority information, and benefits of the science.

Group 4—Energy and Mineral Supply—

Mitigating, Managing, and Avoiding Impacts of 

Shortfalls on the Economy

EO data can be used at different stages of energy and 

mineral supply management: from exploration to planning and 

from monitoring to environmental impact assessments. The 

fourth group narrowed the scope of its topic to the siting of 

wind farms. Group 4 participants included energy economists, 

geologists, and engineers (table 4). Potential users of information include investors, regulators, citizens, energy producers, 

and energy users. The information needed includes data on 

weather, climate, and terrain, which leads to mapping products. Critical analysis for wind-farm siting includes cadaster 

(that is, property) and terrain analysis to better understand the 

landscape including human dimensions where a wind farm 

may be placed. During the discussion, participants considered 

whether the value chain/decision tree should be developed 

from the perspective of project planning or project operations. 

The participants also considered political will and societal 

willingness to accept wind farms in one’s community and 

the influence that these factors have on the decision-making 

process. 
Meeting Summary 19Photograph credit: Jay Pearlman. Used with permission.

Table 4. Group 4 participants.

Name Organization

Steven Anderson U.S. Geological Survey.

Tom Crafford U.S. Geological Survey.

Denna Geppi1 National Oceanic and Atmospheric 

Administration.

Josh Jankot National Oceanic and Atmospheric 

Administration.

Graeme Kermich Cooperative Research Centre for Spatial 

Information.

Haris Kontoes University of Athens.

Lef Mamais Evenflow Consulting.

Larry Meinert U.S. Geological Survey.

Kevin Schrab National Oceanic and Atmospheric 

Administration.

Alessandra Tassa European Space Agency.

Jeff Williams2 National Oceanic and Atmospheric 

Administration.

1

Rapporteur.

2

Facilitator.

A representative value chain/decision tree based on the 

group’s discussion is shown in figure 7. The application, windfarm siting, potentially relies on several different types of satellite imagery. Meteorology, wind climatology, off-shore near 

surface wind fields, and terrain all feed into analysis of the 

wind capacity in an area. The group discussed the importance 

of overlaying this information with property cadaster and other 

sociopolitical constraints to inform siting in areas that have 

high wind-energy capacity, and are not disruptive to existing 

housing developments, do not intersect with environmentally 

sensitive areas, or both.

The decision-tree component of the value chain focused 

on the benefit of the information for informing optimal 

wind-farm siting. In the counterfactual, it is possible that a 

wind farm is sited in an area that is ultimately not feasible for 

development based on either societal constraints of environmental sensitivities. Although this may be a high wind-energy 

capacity area, a decision to pursue siting in that area without 

relevant information would likely lead to wasted infrastructure 

and administrative costs. On the other branch of the counterfactual, there may not be any barriers to wind farm development; however, the area may not be ideal for wind energy 

generation. This could lead to reduced energy generation, 

foregone revenues, and lower return on investment.
Figure 6. Harmful algal blooms (HAB): Effects on human health, recreation, and tourism value chain/decision tree.

Drinking 

water 

management

Too much treatment

Optimal treatment

Too little treatment

Decision point Alternatives Outcomes Probabili

High treatment or alternative water 

costs; low public health risk

Treatment or shutdown timed with 

public health risk

Public health risks: gastrointestinal 

illness, amnesia

?

%

?

%

?

%

Optimal treatment Treatment or shutdown timed with public health risk ?% 

Without 

information

With information

Sentinel 

Satellite

Indication 

of event

Early 

warning 

system

In-situ 

baseline 

testing

Campaign 

in-situ 

testing

Hydrodynamic 

modeling Probability 

of toxicity, 

event 

occurrence 

Other and location

analysis/ 

modeling 

Observation 

platform

Data Analysis Information Final products/ services

Aquaculture/ 

hatchery 

farming

Optimal harvest 

timing/sales restriction

Early harvest/sales restrictions; 

Avoid public health risks

?

%

With 

information

Beach closure Optimal timing/extent beach closure Beach closure timed with public health risk ?% 

With 

information

Recreational 

guides Optimize destination Destination location does not have bloom; travel times minimized ?% 

With 

information

Livestock Optimize livestock restrictions Livestock intervention timed/scaled to bloom ?% 

With 

information
Figure 7. Energy and mineral supply: Mitigating, managing, and avoiding impacts of shortfalls on the economy value chain/decision tree.

Wind farm located outside of high wind area, no sociopolitical siting barriers

Optimize location with high wind potential and low land use obstaclesHigh wind potential, sociopolitical siting barriers

Alternatives Outcomes 

Final products/ 

services 

Probability

Less wind energy; wasted 

infrastructure costs

More wind energy for less 

infrastructure investment; reduced 

externalities

More wind energy; high externality 

costs

?

%

?

%

?

%

Geostationary 

orbit 

satellite 

Low earth 

orbit 

satellite 

Meteorological 

data 

Wind 

resource 

maps 

Terrain 

analysis 

Observation 

platform Data Analysis Information Decision point

Medium 

earth orbit 

satellite 

Weather 

station

Wind 

speed

Radar 

imagery 

Lidar 

(wind) 

Wind 

climatology

Terrain

Wind farm 

siting 

Optimize location with high wind potential and low land use obstacles

More wind energy for less 

infrastructure investment; reduced 

externalities

?

%

Without 

information

With 

information

Wind 

resource
22 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

Group 5—Effects of Natural Hazards on 

Transportation Systems—Effects on Mobility, 

Safety, and the Economy

The fifth group looked at the impact of ash from volcanic 

eruptions on transportation (especially air traffic). Participants 

included a volcanologist, economists, and engineers (table 5). 

The major user of information is the Federal Aviation Administration (FAA), which decides whether or not flight routes are 

modified or cancelled. The information needed for this application includes ash cloud forecasts and metrics associated with 

air traffic, which may be derived from satellite and ground 

instrumentation. The group considered the commercial case, 

DHL a cargo handler, as the beneficiary of the decision.

The value chain/decision tree for the effects of a volcano 

eruption on the transportation system is shown in figure 8. 

Observations from satellite and doppler radar provide data on 

sulfur dioxide cloud location, density, and direction. Together 

with weather and ash models, this ultimately provides an ash 

forecast. This information may be used by many transportation 

managers; the group focused on decisions made by the FAA 

on whether or not to modify flights with an example benefactor of DHL, a commercial cargo carrier. In the counterfactual 

scenario, without information, there is a chance that the FAA 

would ground or divert air traffic too often with associated 

costs of fuel and lost time. Alternatively, the FAA may not 

ground or divert traffic soon enough. This could have safety 

impacts, costs associated with equipment damage or loss, 

or both. There are many additional uses of ash cloud maps 

that could be considered when estimating the value of this 

information.

Table 5. Group 5 participants.

Name Organization

Jeffery Adkins National Oceanic and Atmospheric 

Administration.

Aanchal Anand World Bank.

Victoria Avery1 U.S. Geological Survey.

Christopher Katalinas2 National Oceanic and Atmospheric 

Administration.

Jamie Kruse East Carolina University.

Jay Pearlman FourBridges.

Steven Ramage Group on Earth Observations 

Secretariat.

Carl Shapiro U.S. Geological Survey.

Alan Smart ACIL Allen Consulting.

1

Rapporteur.

2

Facilitator.

Photograph credit: Jay Pearlman. Used with permission.
Figure 8. Effects of natural hazards on transportation systems: Effects on mobility, safety, and economy value chain/decision tree.

Air traffic 

diversion

Too much diversion

Optimal diversion

Under diversion

Decision Alternatives Outcomes 

point

Probability

Too much diversion, wasted fuel costs, 

cost of time

Reduced fuel costs, reduced cost of travel 

time, low safety risk, low equipment risk

Too little diversion, safety risks, 

equipment risks, cargo risks

?%?%?%

Optimal diversion ?%

Without 

information

With 

information

Weather 

models Ash cloud 

vectors and 

content 

(direction and 

density)

Observation 

platform

Data Analysis Information Final products/ 

services

Satellite

Doppler 

radar

Ash 

models

Ash 

forecast

Reduced fuel costs, reduced cost of travel 

time, low safety risk, low equipment risk

Sulfur 

dioxide 

cloud 

location, 

density, 

direction
24 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

Open Discussion—Working Group Approaches 

to Developing Value Chains and Decision Trees

After the breakout group discussions and report out, the 

full group reconvened to discuss value-chain/decision-tree 

development and the approach identified by each working 

group. Workshop participants discussed the value in addressing actual systems that exist now (such as the National Water 

Model) instead of hypothetical situations. Jay Pearlman 

mentioned the use of historical use cases, such as the eruption 

in Iceland and Hurricane Sandy. Alan Smart discussed the 

importance of attribution to a specific input and incremental 

improvements. Victoria Avery and Rich Bernknopf discussed 

the value of recasting a historical event in current or future 

contexts.

Andy Coote stated that it is great if you can go back and 

look at data; however, in the developing world, those data are 

not always available. Also, Andy mentioned how value chains/

decision trees are often described as linear but, in fact, are 

networks. A lot of information is lost in analyzing networks as 

linear processes. Participants also discussed how value chains/

decision trees are based on existing products. Carl Shapiro discussed ex-ante and ex-post analyses and how this information 

going forward can create societal benefits. For this to occur, 

it is critical to do a retrospective analysis to anchor the value 

chain/decision tree in reality.

Regarding the need for public engagement, Pierre Glynn 

mentioned how thinking about the value chain/decision tree 

can help create opportunities for participatory planning and 

public understanding. Another participant discussed how the 

climate resilience toolkit can document how communities 

prepare themselves and how its use can help to promulgate 

solutions. Value chains/decision trees can be used as a communication tool to demonstrate the value of this tool kit. Lastly, 

another participant mentioned using the value of loss of life as 

a means of assessing tradeoffs faced by the airline industry in 

dealing with volcanic ash (as one constraint to its decision).

Synthesis, Findings, and Next Steps

Synthesis

This workshop was organized in three distinct parts: an 

overview of methodologies to value EO, a focus on the use of 

value chain and decision-tree frameworks, and the application 

of these frameworks for several predetermined applications. 

During the first part, a series of briefings was provided to 

examine different approaches to estimating the value of EO. 

The latest methods were discussed. The presentations included 

a number of case studies and applications. One approach 

to estimating the VOI is to derive users’ willingness to pay 

either via revealed preference (that is, market prices) or stated 

preference (such as choice experiments). An example of this 

approach is the estimation of the value of Landsat moderate 

resolution data, which used a survey technique (Miller and 

others, 2011), and a second example can be found in Europe, 

where work has focused on the value of the data coming from 

Copernicus Sentinel satellites.

Three use-case studies have been completed based on 

a product value-chain methodology. Reports and a video 

are available through EARSC (https://earsc-portal.eu/pages/

viewpage.action?pageId=35620366). A similar approach was 

also used to consider a specific application of information to 

estimate the value of the NASA GRACE for enhanced drought 

severity index. In this case, researchers determined that adding 

GRACE indicators reduced the number of prediction errors 

in the larger dollar value ranges accruing cost savings (Bernknopf and others, 2017). Each approach has benefits and 

drawbacks. Approaches that look at national-scale or economic-wide impacts may be most appropriate when needing 

to estimate the total economic value of EO; however, it does 

not always provide a clear narrative of the use and benefits of 

information. Focusing on a single application too has constraints. Estimating the value of a single use may not provide a 

good indicator of the full VOI. Another common issue with all 

approaches is being able to discern the value of any component of EO and its contribution to benefits.

A framework that can help overcome some of the limitations of other approaches is the value-chain/decision-tree 

framework. During the workshop, the traditional value chain 

derived from business models was discussed. The purpose of 

the supply of information value-chain delineation supports an 

understanding of the share of contribution from each type of 

data in the flow to the information and to the benefits. Importantly, in addition to the traditional value chain, the addition 

of a decision tree was discussed as a way to understand the 

qualitative relationship between information and decisions. 

The actual monetization of benefits could take many different forms, including market, nonmarket, revealed preference, 

and stated preference approaches. The uniting theme is the 

framework that puts EO into the context of the user and the 

decisions being made that the information supports.

Findings

Finding 1: It is critical that improved understanding of 

the value of EO be developed.—This understanding is important to science and policy. Policymakers and scientists benefit 

from an understanding of the value of EO to improve development and use of EO and to effectively capitalize on key opportunities. Managers and policymakers need this understanding 

so that informed decisions and priorities can be developed to 

use scarce resources or make new investments most effectively. Industry can use the information to promote the benefits 

of the technology and hence its capabilities.

Finding 2: The understanding of the value of EO is facilitated by a description or narrative clearly explaining the basis 

for societal benefits from EO and a quantified estimate of the 

value in monetary or nonmonetary terms.—The narrative and 
Synthesis, Findings, and Next Steps 25

the quantification are important components of an understanding of the value of EO. The narrative provides the intuition or 

description of how benefits are created and the quantification 

provides a measure of the magnitude or size of the benefits. 

Together they develop an understanding of the value of EO.

Finding 3: Narratives that explain the basis of the 

societal benefits from the use of EO need to provide a clear 

and relatively simple explanation of how EO can create an 

improved societal outcome.—With a multidisciplinary team 

that integrates the knowledge base of economists, physical and 

biological scientists, decision scientists, and science communicators, narratives of societal benefits can be addressed 

comprehensively in a short time if the concept remains clear 

and simple. A common language and set of concepts is also 

critical for the advancement of the value of EO.

Finding 4: Value chains and decision trees can be useful tools in understanding the value of EO.—It is important 

to extend the value chain concept beyond the development 

of an information product from EO and to consider how the 

information product impacts societal decisions. As a result, 

value chains can be useful in describing the process of producing information products from EO, as well as illustrating how 

an information product impacts a societal decision. A counterfactual can be obtained by considering the approach that 

was used before information became available. It is important 

when considering a counterfactual scenario that other factors 

that may influence the decision are held constant or otherwise 

incorporated into the analysis. Value chains and decision trees 

provide an analytical framework for evaluating the impact of 

EO in decision making and clearly describe what happens with 

and without the knowledge gained from the EO.

Finding 5: Use cases help advance the state of the 

science of valuing information.—Use cases provide clear 

examples of how EO information is used by a specific set of 

stakeholders for a specific use. By narrowing down several 

uses or decisions that EO could be used for, a use case allows 

for detailed analysis of the VOI for that purpose.

Finding 6: Innovations in quantifying the value of information are needed.—Currently, valuing EO is done largely on 

an ad-hoc basis and requires a lot of time and resources to conduct. Innovations in the types of data used, ways that data are 

collected, or both could create efficiencies so that EO could 

more readily be evaluated.

Finding 7: GEO provides an institutional pathway for 

engaging an international community for the research and 

application of valuing EO.—GEO has 105 member countries 

and 127 participating organizations and has been considering 

the use of EO for more than a decade. GEO’s international 

membership provides expertise in EO along with interested 

stakeholders that make it a great connection for the small 

community that is actively engaged in valuing EO. It would be 

useful to strengthen the linkage with GEO to increase visibility and leverage expertise.

Next Steps

The workshop was successful in highlighting and 

understanding value chains and decision trees relating to EO. 

Participants provided important input on developing five 

initial value chains/decision trees. There was support for the 

ongoing role of the GEOValue Community and for organizing 

meetings in varying locations to extend the GEOValue Community to other nations and most importantly to promote the 

key messages. The European Space Agency offered to host a 

next meeting in 12 to 18 months (late 2018 or early 2019). The 

value chains/decision trees developed in the workshop will 

continue to be worked with different subsets of groups. The 

next GEOValue Community meeting is expected to further 

consider this methodology and tackle other common issues 

with valuing EO.

Research on understanding and quantifying the value of 

EO is advancing, but additional progress is still needed. The 

following future directions will enhance efforts to develop 

improved understanding of the value of EO.

1. Innovative approaches need to be discovered and leveraged.—The process of developing value chains is key for 

the understanding of all potential benefits of EO but can 

be very costly and time consuming. The EO community 

needs to leverage and foster innovations to strengthen 

its ability to develop these complex and important value 

chains. For example, the use of a platform to develop a 

crowdsourced value chain where all experts and users 

have access, can provide their input, and can get feedback.

2. The GEOValue Community needs to continue and be 

strengthened.—Assessing the VOI is a broad challenge 

that affects diverse disciplines and organizations around 

the world. The GEOValue Community provides structure 

and organization for sharing best practices, opportunities, and challenges in efforts to understand and communicate the value of EO. It provides an international 

perspective across multiple disciplines and experiences. 

Linking with GEO can be a useful way to extend the 

international reach of GEOValue. The GEOValue community should continue to convene workshops and other 

meetings to facilitate information sharing and collaboration across its broad set of stakeholders.

3. Further case studies should be developed to cover as 

wide a range as possible of thematic, product, and 

geographical dimensions.—EO derived information 

covers many thematic areas and is applicable to many 

market sectors. It is also global in dimension. As wide 

a coverage as possible should be encouraged to provide 

comparisons and complementary case results.
26 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

4. The different methodologies should continue to be developed and compared exploring the viability, effectiveness, 

and best practices for the use of value chains and decision trees in analyzing the value of EO.—There seems to 

be great potential in the use of this approach in understanding and in communicating the benefits from the use 

of EO. The development of case studies across different 

organizations in different contexts and policy situations 

can provide additional understanding of the usefulness 

and best implementation practices for the effective use 

of value chains and decision trees. 

5. Practical illustrations of value-chain applications 

through results from case studies should be shared and 

discussed at a future GEOValue workshop.—It is noted 

that much progress was made in understanding the value 

of EO for five examples in short breakout sessions with 

experts from different disciplines and organizations. 

With the development of case studies focusing on the 

use of this method, there is great potential for more 

effectively enhancing the use of value chains and decision trees to advance understanding, quantification, and 

communication of the value of EO. Some of the examples, such as toxic HABs are being used as a framework 

to further study the benefits of information by the USGS.

6. The international, interdisciplinary dimensions should 

continue to be developed to draw out the richness of 

case analyses.—Environmental satellites create value 

for society through value chains that include instrument 

design and deployment, data collection and management, research and analysis, and the production of final 

products that inform decisions across a wide range of 

economic sectors and government agencies. The data 

collected by a global system of environmental satellites 

are not constrained by political boundaries and are, thus, 

international in nature and utility. Case studies must 

reflect the contributions of the full range of disciplines 

involved in creating societal value with data collected 

by environmental satellites, including the engineers 

who design and deploy instruments, the full spectrum 

of scientists required to use these data to create useful 

products, and the operational staff in industry and government who use these products. Benefit assessments, 

which more commonly focus on the benefits to a nation 

or other political entity, should be broadened to include 

or at least acknowledge the international and sometimes 

global scope of societal benefits.

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Copernicus Programme: GEOValue side event workshop, 

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Glossary 29

Glossary

Copernicus The European Union’s Earth 

Observation Programme, which provides 

satellite and in-situ data and information prod-

ucts.

counterfactual A scenario used in valuation 

studies that simulates the outcome of a policy 

or decision being analyzed, which can be 

used with baseline scenarios to demonstrate 

economic impacts of a policy or decision.

decision tree A framework for showing 

what data inputs are considered in a decision 

and what outcomes (and their respective prob-

abilities) result.

Earth observation Spatial, temporal infor-

mation, or both that represents a quantity, 

state, flux, or other quantitative measure of a 

physical, chemical, or biological process in 

the Earth system.

GRACE Gravity Recovery and Climate 

Experiment (GRACE) Satellites were a joint 

mission of National Aeronautics and Space 

Administration and the German Aerospace 

Center that detected anomalies of Earth’s 

gravity field in an effort to track changes in 

the distribution of water on the planet. 

Landsat A joint U.S. Geological Survey and 

National Aeronautics and Space Administra-

tion satellite program that has acquired imag-

ery of Earth since 1972. It has applications in 

agriculture, geology, forestry, surveillance, 

and other fields.

revealed preference An economic valuation 

method that estimates prices by observation of 

consumer preferences.

stated preference Also referred to as con-

tingent valuation, it is a method of valuing 

nonmarket resources by determining consum-

ers’ willingness to pay from survey responses.

value chain The connection of data sources, 

analyzed information, and decision points that 

enables the evaluation of how value-added 

information is integrated into the decisionmaking process.
30 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

Appendix 1. Attendee List

Table 1.1. GEOValue side event attendee list, Washington, D.C., October 23–24, 2017.

[NOAA, National Oceanic and Atmospheric Administration; USGS, U.S. Geological Survey; SESYNC, The National Socio-Environmental Synthesis Center; 

IGES, Institute for Global Environmental Strategies; EC–JRC, European Commission’s Joint Research Centre; NASA, National Aeronautics and Space Administration; PRSS, Performance, Risk and Social Science Office; CRCSI, Cooperative Research Centres for Spatial Information; RFF, Resources for the Future; 

EPA, U.S. Environmental Protection Agency; ERG, Eastern Research Group, Inc.; NSF, National Science Foundation; ESA, European Space Agency; GEO, 

Group on Earth Observations; EARSC, European Association for Remote Sensing Companies; DOI, U.S. Department of the Interior; NCEI, National Centers 

for Environmental Information; NOS, National Oceanic Service; NCCOS, National Centers for Coastal Ocean Science; EC, European Commission; DG GROW, 

Directorate-General Internal Market, Industry, Entrepreneurship and SMEs]

Last name First name Organization Contact information (email)

Adkins Jeff NOAA jeffery.adkins@noaa.gov

Anand Aanchal World Bank aanand1@worldbank.org

Anderson Steve USGS sanderson@usgs.gov

Austin Matt NOAA matthew.austin@noaa.gov

Avery Victoria USGS vavery@usgs.gov

Bernknopf Richard University of New Mexico rbern@unm.edu

Boyd Jim SESYNC boyd@rff.org

Brown Vankita NOAA vankita.brown@noaa.gov

Carlis DaNa NOAA dana.carlis@noaa.gov

Colleton Nancy IGES nancy_colleton@strategies.org

Cooper Aimee USGS abcooper@usgs.gov

Coote Andy ConsultingWhere andrew.coote@consultingwhere.com

Crafford Tom USGS tcrafford@usgs.gov

Craglia Max EC–JRC massimo.craglia@jrc.ec.europa.eu

Cummens Patricia EsriI pcummens@esri.com

Firth John Acclimatise j.firth@acclimatise.uk.com

Friedl Lawrence NASA lfriedl@nasa.gov

Gallo Jason Science and Technology Policy Institute jgallo@ida.org

Geppi Denna NOAA denna.geppi@noaa.gov

Glynn Pierre USGS pglynn@usgs.gov

Graham Jennifer USGS jlgraham@usgs.gov

Grasso Monica NOAA Monica.grasso@noaa.gov

Hallegatte Stephane World Bank shallegatte@worldbank.org

Jankot Josh NOAA PRSS josh.jankot@noaa.gov

Katalinas Christopher NOAA christopher.katalinas@noaa.gov

Kernich Graeme CRCSI gkernich@crcsi.com.au

Kinn Gerald (Jerry) Esri GKinn@esri.com

Kontoes Haris University of Athens kontoes@noa.gr

Kruse Jamie East Carolina University krusej@ecu.edu

Kuwayama Yusuke RFF kuwayama@rff.org
Appendixes 31

Table 1.1. GEOValue side event attendee list, Washington, D.C., October 23–24, 2017.—Continued

[NOAA, National Oceanic and Atmospheric Administration; USGS, U.S. Geological Survey; SESYNC, The National Socio-Environmental Synthesis Center; 

IGES, Institute for Global Environmental Strategies; EC–JRC, European Commission’s Joint Research Centre; NASA, National Aeronautics and Space Administration; PRSS, Performance, Risk and Social Science Office; CRCSI, Cooperative Research Centres for Spatial Information; RFF, Resources for the Future; 

EPA, U.S. Environmental Protection Agency; ERG, Eastern Research Group, Inc.; NSF, National Science Foundation; ESA, European Space Agency; GEO, 

Group on Earth Observations; EARSC, European Association for Remote Sensing Companies; DOI, U.S. Department of the Interior; NCEI, National Centers 

for Environmental Information; NOS, National Oceanic Service; NCCOS, National Centers for Coastal Ocean Science; EC, European Commission; DG GROW, 

Directorate-General Internal Market, Industry, Entrepreneurship and SMEs]

Last name First name Organization Contact information (email)

Lawrence Collin USGS cblawrence@usgs.gov

Lipton Doug NOAA douglas.lipton@noaa.gov

Mamais Lef Evenflow Consulting lefteris@evenflowconsulting.eu

Mason Robert USGS rrmason@usgs.gov

McGartland Al EPA McGartland.al@Epa.gov

Meinert Larry USGS lmeinert@usgs.gov

Nadeau Lou ERG Lou.Nadeau@erg.com

O’Connor Robert NSF roconnor@nsf.gov

Ott Michael Intergovernmental Oceanographic Commission m.ott@unesco.org

Pearlman Francoise FourBridges jsp@sprintmail.com

Pearlman Jay FourBridges jay.pearlman@jandfent.com

Petiteville Ivan ESA ivan.petiteville@esa.int

Pindillli Emily USGS epindilli@usgs.gov

Poudel Rajendra NOAA rajendra.poudel@noaa.gov

Pulwarty Roger NOAA roger.pulwarty@noaa.gov

Ramage Steve GEO Secretariat sramage@geosec.org

Sawyer Geoff EARSC geoff.sawyer@earsc.org

Schrab Kevin NOAA kevin.schrab@noaa.gov

Schuster Rudy USGS rschuster@usgs.gov

Shapiro Carl USGS cshapiro@usgs.gov

Simon Benjamin DOI benjamin_simon@ios.doi.gov

Slawecki Theodore LimnoTech tslawecki@limno.com

Smart Alan ACIL Allen Consulting or Geoscience Australia a.smart@acilallen.com.au

Stryker Tim USGS tstryker@usgs.gov

Tanhua Toste Global Ocean Observing System ttanhua@geomar.de

Tanner Michael NCEI Michael.Tanner@noaa.gov

Tassa Alessandra ESA alessandra.tassa@esa.int

Thur Steven NOAA/NOS/NCCOS Steven.Thur@noaa.gov

Veispak Andreas EC–DG GROW andreas.veispak@ec.europa.eu

Williams Jeff NOAA jeff.l.williams@noaa.gov
32 Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings

Appendix 2. Workshop Agenda

Day 1—Monday, October 23

9:00 a.m. Welcome address

Monica Grasso, National Oceanic and Atmospheric Administration (NOAA)

Carl Shapiro, U.S. Geological Survey (USGS)

Alessandra Tassa, European Space Agency (ESA)

Geoff Sawyer, European Association for Remote Sensing Companies (EARSC)

9:20 a.m. Round table participant introductions

Participants provide 15 second self-introductions.

9:30 a.m. Methodologies—Session 1

Moderator: Steven Ramage, Group on Earth Observations (GEO) Secretariat

1. Andreas Veispak, “Demonstrating the Value and Benefits of the Copernicus Programme”

2. Alan Smart, “Methodologies for Evaluation”

3. Stephane Hallegatte, “Simple Assessments of the Benefits from Early Warning Systems and Stronger Hydro-Meteorological Systems”

4. Andy Coote, “Value Chain and Cost-Benefit Analysis Applied to 3D Geo-Information”

11:15 a.m. Break

11:30 a.m. Methodologies—Session 2

Moderator: Steven Ramage, GEO Secretariat

1. Pat Cummens, “Esri Perspective”

2. Rudy Schuster. “Communicating the Value of Landsat Imagery Using Case Study Narratives”

3. Aanchal Anand, “The Economic Value of Geospatial Information: An Albania Case Study”

4. Rich Bernknopf, “A Decision Framework for Quantifying the Economic Value of Information 

of Earth Observation: Case of the NASA Gravity Recovery and Climate Experiment (GRACE) 

Enhanced Drought Severity Index”

5. Geoff Sawyer “A Bottom-Up Approach to Assessing the Value of Satellite EO Data”

1:15 p.m. Lunch

2:15 p.m. Introduction to value chains and processes panel—Session 3

Moderator: Emily Pindilli, USGS

1. Tim Stryker, USGS 

2. Jeff Adkins, NOAA

3. Jamie Kruse, East Carolina University

4. Yusuke Kuwayama, Resources for the Future

3:45 p.m. Break

4:00 p.m. Value chains forum: Session 4

Moderator: Jay Pearlman, FourBridges 

Open discussion on value chains, data/information requirements, and instructions for developing value 

chains and identifying data requirements in topic areas.

4:25 p.m. Wrap up of day 1 and plan for day 2

4:30 p.m. Adjourn
Appendixes 33

Day 2—Tuesday, October 24

9:00 a.m. Welcome address, recap of day 1, plan for day 2

9:30 a.m. Value chain development working groups (group members predetermined) for monitoring and 

forecasting:

Group 1: Effect of increasing temperatures on human health

Group 2: Floodings—Mitigating, managing, and avoiding impacts to safety and property damage

Group 3: Harmful algal blooms—Effects on human health, recreation, and tourism

Group 4: Energy and mineral supply—Mitigating, managing, and avoiding impacts of shortfalls on the 

economy

Group 5: Effects of natural hazards on transportation systems—Effects on mobility, safety, and the 

economy

10:30 a.m. Break

11:00 a.m. Identifying data requirements work groups (same groups)

12:00 p.m. Lunch

1:00 p.m. Group sharing activity (describe results of working session)

2:15 p.m. Break

2:30 p.m. Guidance document scoping

Moderator: Monica Grasso, NOAA

Participants will be engaged in discussion of a guidance document that uses the methodologies, value 

chains, and information needs determined during the workshop to provide recommendations for 

ongoing socioeconomic data monitoring and next steps.

3:30 p.m. Wrap up, next steps, and commitments

4:00 p.m. Adjourn
For more information about this publication, contact: 

Science and Decisions Center 

U.S. Geological Survey 

913 National Center 

12201 Sunrise Valley Drive 

Reston, VA 20192 

gs_emeh_sdc@usgs.gov

https://www2.usgs.gov/sdc/ 

Publishing support provided by the 

Reston and Rolla Publishing Service Centers

Pearlman and others—Demonstrating the Value of Earth Observations—Group on Earth Observations Side Event Proceedings—Open-File Report 2019–1033

ISSN 2331-1258 (online)

https://doi.org/10.3133/ofr20191033