IEEE Geoscience and Remote Sensing Magazine - December 2020 - 9

a significant supply of satellite imagery [4], bringing countless benefits to societies and humankind such as the saving
of many lives, improvements in environmental quality, enhanced regulatory and efficiency [7], [15]. In fact, the growing
trend of free access to satellite images raises the question of
valuation with particular acuity [45]. The valuation of EO is
still in its infancy due to the difficulties it presents [30]. Valuing satellite images is not a simple process. Asking " How valuable is a satellite image? " should be followed by the question,
" How valuable to whom? "
In recent literature, the social value of satellite images is
assessed either qualitatively, as for Landsat and Sentinel images
[36], [39], or quantitatively: some econometric modeling and
estimation examples for the value of satellite information include analyses of agricultural productivity and vegetation dynamics [14], [63], land use and management [67], [68], air
and water quality [9], [20], [53], and so on. Although most
approaches are based on cost-benefit studies [21], other
evaluations consist of statistical analyses [34]. In fact, a distinction must be made between the impacts of using satellite images, which can be determined through the number
of lives saved, the time saved, reduction of uncertainty, and
so on, and quantitatively measuring the value of the images,
which is about estimating the value that users draw directly
from the data [33]. Recently, Laxminarayan and Macauley
[32] stated that the contingent-valuation method, which refers to consumers' WTP, can be the most important method
for assessing the benefits derived from EO data. Thus, WTP
could be a very useful tool for assessing the value of satellite
images. Although this method has been cited in more than
2,000 works on diverse subjects [37], it was applied for the
first time to satellite imagery in 2015 to evaluate the Landsat
satellite images [34]. To our knowledge, our study is the first
application of this method to HR satellite images.
This article explores the economic valuation of geospatial information as perceived by the direct users of a SDI.
The study is based on HR satellite images provided by the
GEOSUD (http://ids.equipex-geosud.fr/) Theia (http://www
.theia-land.fr/ed) SDI, located in France. In general, satellite
images can be distinguished on the basis of their spatial resolution or ground spatial distance (GSD). In the absence of an
established standard, we use the following categories:
◗◗ medium resolution (MR), referring to greater than 5 m of
GSD [e.g., Landsat, Sentinel, Satellite pour l'observation de la
Terre (SPOT) 1-5, RapidEye]
◗◗ HR, from 1 to 5 m of GSD (e.g., SPOT 6/7)
◗◗ very HR (VHR), indicating less than 1 m of GSD (e.g., Pleiades, WorldView).
Since 2011, the GEOSUD SDI has made it possible to acquire homogeneous coverage of the French national territory
each year. From 2011 to 2013, this acquisition was based on
MR images (from RapidEye and SPOT 5). Later, from 2014
to 2019, the HR SPOT 6/7 images were used to produce the
national map; the installation in 2014 of a direct receiving
station with a SPOT 6/7 telemetry contract for the period
2015-2019 made it possible to continue acquiring annual
DECEMBER 2020

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE

HR national-coverage maps and meet specific HR-image requests worldwide from GEOSUD SDI platform subscribers.
From the very beginning of the project, all images were acquired with a single multiuser license for public and research
purposes only. These images (raw and rectified images, annual national coverage, and so on) differ in terms of fitness
for use and price versus those acquired directly from the basic
image providers (i.e., Airbus Defense and Space [ADS]). For
instance, at the end of 2018, if these images were not available through the pooling system developed by GEOSUD (an
investment of €11 million), it would have cost €110 million
for all SDI users to acquire them separately from the image
providers at their preferential rates. Many users would have
given up due to budget constraints.
The valuation shows the importance of satellite imagery in
supporting territorial planning and development economics
in a context of open and distributed innovation within networks, where information is considered a specific asset [25],
[65]. In addition, it provides elements that allow the establishment of pricing scenarios to sustain the GEOSUD business model in the long run. In mid-2018, the launch date of
the study, several debates on the question of the sustainability of GEOSUD beyond 2019 were taking place regarding the
establishment of a national access mechanism for satellite
imagery. In fact, the access that GEOSUD has been providing since 2011 for a wide range of images covering different
themes is the result of an increasingly costly structure for the
continuous development of new systems and maintenance
of existing ones. At the current stage of GEOSUD's development, the first socioeconomic impacts are the costs avoided
in the purchase of images by public actors and the scientific
community due to pooling and the beneficial effects linked to
user networking and training.
A first study was conducted concerning the direct impacts
of the use of GEOSUD satellite imagery in the control of forest clear-cuts in France; an average ratio of €24 of productivity
gains was obtained for every €1 invested in GEOSUD [26],
[40]. An economic value assessment may address important
policy questions and the way HR satellite images contribute
to economic activity. Our study targets a multitude of users,
most from public bodies, for whom current access to images
through the SDI is free. In addition, it clarifies the sustainability issues of the HR-imaging system used since 2014, with the
receiving station and SPOT 6/7 terminal. Hence, by presenting elements to establish possible funding scenarios for the
future, this study helps justify past and future investments to
ensure the sustainability of this type of data.
METHODOLOGY
PARTICIPANTS AND DATA CHARACTERISTICS
In 2007, the first regional and European funding programs
made it possible to initiate the GEOSUD project by financing
a future extension of the Remote Sensing Center facilities in
Montpellier, France. A SDI was created consisting of a satellite reception station, a SPOT 6/7 satellite reception terminal,
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IEEE Geoscience and Remote Sensing Magazine - December 2020

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