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Geoforum 80 (2017) 24–38
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Geoforum
journal homepage: www.elsevier.com/locate/geoforum
Satellites and the New War on Infection: Tracking Ebola in West Africa
Robert Peckham ⇑, Ria Sinha
Centre for the Humanities and Medicine, The University of Hong Kong, Hong Kong
a r t i c l e
i n f o
Article history:
Received 16 September 2016
Received in revised form 15 December 2016
Accepted 3 January 2017
Keywords:
Satellites
Epidemic intelligence
Ebola
West Africa
Digital divide
Vertical geopolitics
a b s t r a c t
Satellite technologies are increasingly being deployed to manage infectious disease outbreaks. Although
there is a substantive literature concerned with the geopolitics of space and the ethical issues raised by
the use of remote sensing in warfare and counterinsurgency, little study has been made of the critical role
played by satellites in public health crises. In this paper, we focus on the 2014–2015 Ebola virus disease
(EVD) epidemic in West Africa, which saw the widespread use of public and commercial satellite-derived
data, to investigate how overhead orbital and close-up viewpoints enabled by satellites are shaping attitudes to disease and determining responses to infectious threats. We argue that high-resolution satellite
imagery is acting as a spur to a new spatio-temporal targeting of disease that parallels the ever more vertical dimension of contemporary warfare. At the same time, this new visualization of disease is promoting
a broader ecological perspective on pathogen emergence. How can these divergent perspectives be reconciled? In addressing this question, we analyze the different uses to which satellite imagery has been
put in tracking and mapping Ebola ‘hotspots’ across Guinea, Liberia, and Sierra Leone. We also consider
the institutional contexts that have enabled the acquisition of this imagery. Given the rapid integration of
space technologies in epidemiology and health logistics, there is now a need to examine how and with
what consequences remote-sensing and communication technologies may be reconfiguring the practices
and scope of global health.
Ó 2017 Elsevier Ltd. All rights reserved.
1. Introduction: technological convergence
Between December 2013 and December 2015, West Africa
experienced the largest epidemic of Ebola virus disease (EVD) in
history, with more than 28,000 suspected cases across Guinea,
Liberia, and Sierra Leone, and over 11,000 deaths.1 On 9 October
2014, the International Charter for Space and Major Disasters – an
agreement between ‘‘Authorized Users” to provide free space data
‘‘to those affected by natural or man-made disasters” – was activated
by the US Geological Survey (USGS) on behalf of the US National
Geospatial-Intelligence Agency (NGA) to monitor the Ebola outbreak
in Sierra Leone (UK Space Agency, 2014). This marked the first time
the Charter’s space assets had been deployed to assist in containing
an epidemic (CERN, 2014).2
⇑ Corresponding author.
E-mail address: [email protected] (R. Peckham).
The Ebola outbreak has been traced to a two-year-old boy, who died in December
2013 in Meliandou, a village in southeastern Guinea (Maron, 2014).
2
‘‘Authorized Users” for the main part comprise national space agencies but also
include Airbus Defence and Space, and the companies DigitalGlobe and GeoEye
(Satellite Imagining Corporation) that formally merged in January 2013. See http://
www.disasterscharter.org/web/guest/-/other-in-sierra-leone.
1
http://dx.doi.org/10.1016/j.geoforum.2017.01.001
0016-7185/Ó 2017 Elsevier Ltd. All rights reserved.
While the effectiveness of the World Health Organization’s
(WHO) response to the Ebola epidemic was widely criticized
(Moon et al., 2015; Stocking et al., 2015), the epidemic crisis saw
a significant number of remote-sensing initiatives that involved
partnerships between multiple national and international agencies
and commercial companies. The outbreak instigated a rush for
high-resolution satellite imagery that would furnish the basis for
more comprehensive mapping. As Mapbox – a company involved
in a humanitarian mapping project during the Ebola outbreak –
notes on its website: ‘‘This is a region where the best available
maps are often antiques from the colonial era, two generations
ago.”3
Space data also acted as a spur to discussions across disciplines
about the practical application of innovative technologies in the
management of infectious disease. An international conference,
‘Technology for Ebola’, sponsored by Microsoft, was held in Cairo
in December 2014 under the motto ‘‘The tech industry can
empower Africa in its fight against Ebola”. As one commentator
noted during the crisis: ‘‘The Ebola scare may turn out to be one
3
Charlie Loyd, ‘Ebola mapping in Guinea: Humanitarian OpenStreetMap Team’
(March 25, 2014). Retrieved from: http://www.mapbox.com/blog/osm-ebola-mapping/.
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
of health care technology’s important trial runs, given the sheer
number of apps, mapping tools, collaboration platforms and even
robots that have been recruited for duty.”4
In this paper, we focus on the Ebola outbreak in West Africa to
examine how epidemiological knowledge and communication systems are becoming increasingly entwined. What are the implications of this intertwinement for global health? In addressing this
question, we draw upon – and seek to contribute to – a growing literature concerned with the way that orbital and aerial perspectives
‘‘structure particular ways of engaging with the world” (Parks,
2012, p. 196). The emphasis in this scholarship has been on exploring the role of media technologies, such as satellites, in reconfiguring visual practices and shaping how the ‘global’ is understood.
Satellite images of earth are the upshot of complex interdependencies between state and non-state agencies, and are practically
enabled by state and multinational financing. Rather than viewing
such imagery as neutral data – the way that those promoting and
selling the technology encourage us to do – the focus has shifted
onto the geopolitical contexts that determine how data is produced, interpreted, and disseminated.
Epidemic image data generated by remote-sensing technologies, we argue in this paper, are the outcome of a complex technological and institutional matrix that extends from optical
instruments to computer processing. During the Ebola crisis, the
UN’s Operational Satellite Applications Programme (UNOSAT), a
division of the UN’s Institute for Training and Research (UNITAR),
produced an Atlas of Ebola Care Facilities in Guinea, Liberia & Sierra
Leone to support emergency humanitarian assistance activities on
the ground (Figs. 1 and 2). The atlas relied on high-resolution imagery from three DigitalGlobe satellites – WorldView-2,
WorldView-1, and Quickbird – but also involved the collaboration
of numerous other organizations to process the imagery and create
geospatial content (UNITAR, 2014).
In a manner similar to Jody Berland’s description of weather
forecasting, epidemic surveillance and prediction involve a ‘‘technical convergence and economic interdependency of a specific
technological assemblage of satellite communication transmission,
GPS monitoring, television, digital information processing, digital
graphics, security systems, and the management of urban space”
(Berland, 2009, p. 246). The term ‘satellite imagery’ thus underplays the degree to which satellite technologies are contingent
on an assemblage of different organizations with ‘‘different social
goals and ways of understanding the hardware itself” (Mack,
1990, p. 4). It also elides the different phases of the image production process: from the acquisition of data to their processing, spectral analysis and interpretation, and finally the development of
specific information products (Lillesand et al., 2004, p. 3). This
interdependence of state agencies, NGOs, and other organizations
and corporations working as service providers, constitutes a ‘‘contracting nexus” that Crampton, Roberts, and Poorthuis identify as a
‘‘new political economy of geographical intelligence” (Crampton
et al., 2014; see also Parks and Schwoch, 2012).
Until recently, geopolitics has tended to be understood as a fundamentally ‘‘flat discourse”. As Weizman has observed: ‘‘It largely
ignores the vertical dimension and tends to look across rather than
to cut through the landscape. This was the cartographic imagination inherited from the military and political spatialities of the
modern state” (Weizman, 2002). Over recent years, however, there
has been a fresh emphasis on the vertical dimension of geopolitics;
on how aerial and orbital perspectives are reshaping notions of territory, security, and conflict (Adey et al., 2011, 2013; Elden, 2013;
Graham, 2004; Williams, 2013). Aerial warfare in World War I
4
See ‘How technology is helping fight Ebola’, GCN (October 22, 2014). Retrieved
from: https://gcn.com/articles/2014/10/22/ebola-technology.aspx.
25
‘‘prefigured a symptomatic shift in target-location”, while the
development of spy-satellites and drones after World War II
enabled a ‘‘strategy of global vision” (Virilio, 1989, p. 1) that
challenged existing cartographic techniques. In short, twentiethcentury aerial and orbital technological innovations have
increasingly moved geopolitics onto a vertical axis, and as a result
have called for a new multi-dimensional representation of space
(Weizman, 2002).
The contemporary dependence on satellite imagery for mapping might be viewed as an extension of the state’s historical reliance on mapping to manage risks and threats (Crampton, 2003).
However, the involvement of multiple non-state actors in the production and distribution of such imagery could be said to reflect ‘‘a
shift in the institutional locus of disciplinary power” and a diffusion of surveillance that challenges a ‘‘state-centric view of world
politics” (Litfin, 2012, p. 67).
As Parks notes, ‘‘It is especially when technologies converge that
we notice and understand their definitions” (Parks, 2005, p. 9).
Today epidemiology and public health are being reconfigured
through the uses of high-resolution satellite imagery and globalpositioning (GP) maps that are also central to military strategy
and underpin commercial entertainment. Media broadcasting,
mobile phones, air travel, as well as national security, all rely on
the same constellation of satellite technologies. ‘‘When technologies converge”, Parks observes, ‘‘they develop in discursive, economic, and institutional interdependence with one another.
Convergence, then, is a relational model of understanding how
technologies inflect, inform, and interact with one another in processes of their emergence” (Parks, 2005, p. 77).
This inter-reliance of public and private sectors has triggered
heated debates about the potential for conflicts of interest, particularly in the context of security policy, which ‘‘is in the midst of a
fundamental shift in tone and quality as a result of remote sensing
satellite technology” (Livingston and Robinson, 2003; see also
O’Connell et al., 2001). Satellite imagery constitutes an important
component of the military ‘‘surveillant assemblage” (Haggerty
and Ericson, 2000) that has been succinctly defined as ‘‘a heterogeneous set of intelligence gathering and command systems whose
unity depended upon their smooth and transparent interoperability” (Harris, 2006, p. 103). The purchase by the Pentagon in 2001 of
the rights to images of Afghanistan taken by the IKONOS satellite
owned and operated by DigitalGlobe, is one example of the devolution of security technology. This use of commercial highresolution satellites is widely understood to carry political and
operational security challenges for national policy-makers
(Livingston and Robinson, 2003).
From the late 1980s, disease emergence has been increasingly
construed as a problem of global security. As the preface to the
influential 1992 report Emerging Infections: Microbial Threats to
Health in the United States declared: ‘‘There is nowhere in the world
from which we are remote and no one from whom we are disconnected. Consequently, some infectious diseases that now affect
people in other parts of the world represent potential threats to
the United States because of global interdependence, modern
transportation, trade, and changing social and cultural patterns”
(Lederberg et al., 1992, p. v). Public health security became the
framework for dealing with new biological threats produced by
this global connectedness (Lakoff and Collier, 2008, p. 7). In his critique of Western humanitarian and peace interventionism, Duffield argues that development has functioned primarily as a
mechanism for maintaining and policing the divide between development and underdevelopment (Duffield, 2007). In this paper we
suggest, similarly, that the mobilization of geosurveillance technologies for health and humanitarianism is further merging development and security agendas (Duffield, 2001). Rather than relying
on biodefense – on safeguarding national borders – the emphasis
26
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
Figs. 1 and 2. Ó UNOSAT/UNITAR. Atlas of Ebola Care Facilities (ECF) in Guinea, Liberia & Sierra Leone. The satellite image shown above left pinpoints the location of an ECF in
Macenta, Guinea, close to the Liberian border. The image on the right shows Lakka Hospital, an ECF near the coast of Sierra Leone. The operational status of the facilities at the
time of image capture was not reported (UNITAR, 2014).
has shifted to ‘‘biosecurity interventions”: to detecting and managing disease outbreaks ‘‘should such events occur across international borders” (WHO quoted in Lakoff and Collier, 2008, p. 8).
The targeting of disease ‘hotspots’ in developing countries resembles a form of precision warfare. Indeed, the same remotesensing technologies are being used in public health and military
campaigns waged sometimes in the same places (Peckham, 2016).
Although there is now a substantive body of scientific work
applying satellite data to specific cases of disease surveillance
and management, this has tended to be largely descriptive. There
has been negligible analysis to date of how these data might relate
to practices of power and to a vertical geopolitics, as recent studies
of warfare have suggested. Equally, little investigation has been
made of the institutional contexts that determine the data’s use.
Given the dependency on satellites in telecommunications and
direct broadcasting, remote sensing and GP, it is surprising that
so little interest has been shown in how ‘‘orbital space is structured
to make such practices possible” (Parks, 2013, p. 62).
The use of remote-sensing technologies during the Ebola crisis
became an important subsidiary story in the news media with
widespread coverage of how Western space technologies were
being arrayed in the ‘fight’ against disease. The emphasis on satellites and real-time communication and information systems contrasted to conventional disaster images of gowned healthcare
personnel, makeshift health centers, isolation facilities, and bodybagged victims. Implicitly, state-of-the-art space technology was
pitted against the backwardness of a region where ‘primitive’ burial rituals were widely held responsible for spreading infection
(Nielsen et al., 2015). High-resolution satellite imagery laid bare
the region’s lack of infrastructure. It underscored a glaring discrepancy between the apparently seamless connectivity and ease of
operation embodied in satellites, on the one hand, and the communication impediments presented to response teams on the ground
by a vast landmass with poor transportation links, an absence of
healthcare facilities, partial access to electricity, and dense forest,
on the other. As we shall see, satellite data served to
reaffirm prevalent non-African views of the continent as a disease
‘hotspot’ – a ‘‘[site] of scrutiny, destruction, and extraction” (Parks,
2012, p. 198).
2. The rise of tele-epidemiology
A recent study of the drone has attempted to trace its ‘‘technical
and tactical genealogy” in order to understand the technology’s
‘‘fundamental characteristics” that stem from this genealogy
(Chamayou, 2013, p. 16). A similar attempt might be undertaken
to track the technical and tactical genealogy of remote-sensing
technologies that have been recruited for epidemic intelligence,
surveillance, and reconnaissance. By the early 1970s, satellites
had gained a new prominence as scientific tools. A RAND report
commissioned by the US Army Air Forces and published in 1946
presented ‘‘an engineering analysis of the possibilities of designing
a man-made satellite”. While undoubtedly of ‘‘great military
value”, the report noted that a ‘‘satellite vehicle with appropriate
instrumentation can be expected to be one of the most potent scientific tools of the twentieth century” (RAND, 1946). It was not
until October 1957, however, that the first artificial space satellite,
Sputnik 1, was launched by the Soviet Union. The size of a beach
ball, it took some 98 minutes to orbit the earth and triggered a
space race.5 The CORONA reconnaissance satellite was successfully
launched by the United States in August 1960 (Ruffner, 1995, pp.
xiii–xvi).
The term ‘remote sensing’ was apparently coined in
1958 (Warner et al., 2009, p. x), the year that the US National
5
See http://history.nasa.gov/sputnik/.
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
Aeronautics and Space Administration (NASA) was created by President Eisenhower. It came to designate ‘‘the science – and art – of
identifying, observing and measuring an object without coming
into direct contact with it”.6 The idea that satellites might be useful
in the fight against disease had been broached in the 1960s. In 1965,
the director of the USGS, William Pecora, ‘‘proposed the idea of a
civilian remote-sensing satellite program to gather facts about the
natural resources of the earth” (Loveland, 2012, p. 14). In July
1972, NASA launched its first Earth Resources Technology Satellite
(ERTS-1) – renamed Landsat-1 in 1975 – with the aim of collecting
environmental data about temperature, rainfall, humidity, and vegetation (Mack, 1990). These are limiting factors that affect the activity
of pathogens and their natural reservoirs, as well as the behavior of
disease vectors, such as mosquitoes. As NASA administrator James C.
Fisher remarked in 1974: ‘‘If I had to pick one spacecraft, one space
age development, to help save the world, I would pick ERTS and the
operational satellites which I believe will be evolved from it later in
this decade” (Wilford, 1974). In 1985, NASA launched a Global Monitoring of Human Health (GMHH) program, focused on vector-borne
diseases, including malaria and Lyme disease. This led to the establishment a decade later of the Center for Health Applications of Aerospace Related Technologies (CHAART), explicitly ‘‘to provide
education, training, and outreach to investigators from the human
health community” (Wood et al., 2000, pp. 336–337).
Since the mid-1990s, when CHAART was founded, ‘‘an increasing number of health studies have used remotely sensed data for
monitoring, surveillance, or risk mapping, particularly of vectorborne diseases” (Beck et al., 2000, p. 217). Research has suggested
that many emerging and reemerging infectious diseases are connected to climatic and environmental change. Rising sea levels,
floods, and forest fires, for example, are viewed as drivers of infection. Environmental biosurveillance by satellites has thus provided
a basis for epidemic early warning systems (Ford et al., 2009;
Nichols et al., 2014; Pinzon et al., 2004). Socioecological drivers
of infectious disease are also being analyzed through satellite imagery – urbanization, changes in land use, poverty, migration, and
human encroachment into forest habitats (Bharti et al., 2011;
Jean et al., 2016).
Epidemiologists have employed satellite data to map, control,
and predict the spread of water-borne and vector-borne infections,
including malaria in sub-Saharan Africa (Dambach et al., 2009;
Ebhuoma and Gebreslasie, 2016; Kabaria et al., 2016; Rogers
et al., 2002; Sewe et al., 2016; Weiss et al., 2014). Google Earth,
which integrates satellite imagery with aerial photography and
images generated by global information systems (GIS), has been
mobilized to track the spread of polio in the Democratic Republic
of Congo (DRC) (Kamadjeu, 2009). Satellite-based assessments
have been made of hydro-climatic conditions related to epidemic
cholera (Jutla et al., 2015), and satellites have also been used to
study predictor variables in outbreaks of Rift Valley fever in Kenya
(Linthicum et al., 1999) and Senegal (Vignolles et al., 2010), as well
as meningococcal meningitis across the so-called ‘African Meningitis Belt’ (Thomson et al., 2006).
Tele-epidemiology has thus become an increasingly important
dimension of global health, particularly since the mid-1990s, when
commercial satellite imagery became more readily available
(Kalluri et al., 2007). In 1994, President Clinton had allowed private
companies to sell high-resolution satellite imagery ‘‘to domestic
and foreign customers” and sanctioned the export of turnkey
remote sensing systems. The aim of this policy was explicitly ‘‘to
find new commercial applications for defense technologies and
enhance US global competitiveness in the international remote
6
See http://earthobservatory.nasa.gov/Features/RemoteSensing/.
27
sensing marketplace”.7 At the Third United Nations Conference on
the Exploration and Peaceful Uses of Outer Space (UNISPACE III) held
in Austria in 1999, infectious disease mitigation and prevention were
identified as important areas and the conference called for the integration of space technologies into ‘‘medical research, surveillance
and control programmes on a global scale” (Dinas et al., 2015;
UNISPACE III, 1999, p. 21).
In the twenty-first century, tele-epidemiology is an evolving
field that combines ‘‘epidemiology and space technology applied
to human and animal health” (Brazeau et al., 2014), with an
emphasis on the connections between disease and climatic and
environmental variations (Hay, 2000; Marechal et al., 2008). NASA,
along with international organizations, including the WHO – in
partnership with commercial operations – have been instrumental
in the development of tele-epidemiology. The European Space
Agency (ESA) sponsored an Earth observation for epidemiology
project, EPIDEMIO, between 2004 and 2006. This used Earth observation and land-based data to monitor the environmental conditions that drive infections (Gemperli et al., 2004). EPIDEMIO also
supported on-the-ground epidemic response efforts, providing
data from the SPOT-5 and IKONOS satellites for epidemiological
urban mapping during an outbreak of Marburg virus disease
(MVD) in Angola (ESA, 2005). The SAFE (Satellites for Epidemiology) pilot project, also funded by ESA, focused on the use of satellite communication services during biological crises (Chronaki
et al., 2007). The ESA noted that ‘‘the SAFE pilot project is a good
illustration of the added value of satellites – with the service provided by space answering the needs on the ground” (Wagstaff,
2008, p. 88). As Beck, Lobitz, and Wood noted at the beginning of
the millennium: ‘‘Increased computing power and spatial modeling capabilities of geographic information systems could extend
remote sensing into operational disease surveillance and control”
(Beck et al., 2000, p. 217).
Over a decade since this pronouncement was made, advances in
GIS are making high-resolution global data increasingly available,
accessible, and affordable (Hay et al., 2006). The ability to incorporate ancillary geo-coded data ‘layers’ has improved the accuracy of
satellite image analysis, while the Internet has facilitated the storage and dissemination of these data. ‘‘Satellite systems”, write Purkis and Klemas, ‘‘have become the defining technology in our
ability to quantify global change” (Purkis and Klemas, 2011, p. 5).
These systems are now being applied ever more widely to model
the prevalence of infectious diseases (Weiss et al., 2014). Remote
sensing is being used, not only to establish outbreak patterns and
track vector movements, but also to assist with diagnostics and
treatment, and to support humanitarian relief work (Asrar et al.,
2015).
3. Satellites and the 2014–2015 Ebola epidemic in West Africa
EVD is a severe, often fatal illness affecting humans.8 The
virus, which belongs to the Filoviridae family of filoviruses, is
transmitted to people from wild animals and subsequently spreads
through human-to-human contact. The disease first appeared in
two concurrent outbreaks in 1976: in Nzara and Maridi in
south-western Sudan, and in the village of Yambuku, 682 miles
northeast of Kinshasa in the DRC (formerly Zaire) (IC, 1978;
Pattyn et al., 1977; WHO, 1978). The disease takes its name from
the River Ebola, a tributary of the Congo River, that runs through
the northern DRC (Piot, 2013, pp. 56–57).
7
PDD-NSC 23 ‘US policy on foreign access to remote sensing space capabilities’
(March 10, 1994). On the profound implications of this market liberalization for
satellite imagery, see Dehqanzada and Florini (2000). On the implications of Clinton’s
policy, see Baker (1997).
8
Ebola virus disease (EVD) was formerly known as Ebola hemorrhagic fever.
28
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
The recent Ebola outbreak in West Africa is the largest since
1976. The last epidemic in Uganda between 2000 and 2001 saw
425 presumptive cases with 224 deaths (Lamunu et al., 2004).
The 2014–2015 outbreak by comparison saw 28,652 suspected,
probable, and confirmed cases with 11,325 deaths.9 The first confirmed cases of the disease occurred in March 2014 (Baize et al.,
2014; Bausch and Schwarz, 2014). On 8 August 2014, the WHO
announced that the Ebola epidemic in West Africa was a ‘‘public
health emergency of international concern” (PHEIC) under the International Health Regulations (Briand et al., 2014; Gostin et al., 2014;
WHO, 2014). The most severely affected countries were Guinea,
Liberia, and Sierra Leone – but Ebola cases were also reported in
Senegal, Nigeria, and Mali (ECDC, 2014).
The scale of the Ebola outbreak in West Africa prompted a global response that reflected international concerns over the disease’s pandemic potential. Cases in the United States, Spain, and
the United Kingdom generated widespread media coverage and a
degree of global panic.10 While the ground response in West Africa
was highly visible in the media, remote-sensing technologies were
also employed to track the disease. Satellites were engaged to monitor isolated rural communities, providing mapping data that supported on-the-ground logistics and contact tracing (CERN, 2014).
According to the ESA, one of the problems faced by health agencies
in mapping past epidemics is outdated ground information. Access
to current visual data is critical in planning personnel deployment
and identifying likely infection routes. In addition, potential Ebola
outbreak sites cover large areas, so real-time ground data help to
focus research by highlighting regions of concern that warrant further study (ESA, 2003b).
At the street level, satellite mapping was used to help Médecins
Sans Frontières (MSF) response teams navigate their way to and
around the worst affected towns and villages.11 MSF had signed a
framework agreement in late 2013 to collaborate with CartONG, a
French NGO specializing in humanitarian mapping. For the first time,
a dedicated GIS officer was deployed on the ground in Guéckédou
prefecture, in the Nzérékoré region of Guinea (Lüge, 2014, p. 10).
The GIS officer produced weekly updates on confirmed, probable,
and suspected cases of Ebola, along with deaths. This was regularly
uploaded to a satellite map, allowing for timely interventions. As
one commentator remarked: ‘‘That map translated the scientific into
the operational” (Lüge, 2014, p. 19). Past relief operations had typically relied on schematic hand drawn maps and basic Google Earth
images. However, these did not provide the requisite level of detail
and accurate local information to guide ground operatives in hazardous environments, where rapid response to reported cases is
often crucial.12 CartONG purchased Pleiades and SPOT 6 regional
satellite images from Airbus Defence and Space (other images were
provided free) to produce reliable base maps that could be overlaid
with critical operational information. To identify villages, streets,
and buildings the images were further processed by the Humanitarian OpenStreetMap Team (HOT), a volunteer group within Mapbox,
and the results posted online, including a map of Guéckédou that
was uploaded to the UN’s Office for the Coordination of Humanitarian Affairs’ website, ReliefWeb (ADS, 2016). Processed mapping
images were retained by MSF to build a database that would build
capacity for existing and future operations in the region. Operatives
9
See http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/.
See, for example, ‘Panic: the dangerous epidemic sweeping an Ebola-fearing US’,
Guardian (October 20, 2014). Retrieved from: http://www.theguardian.com/world/
2014/oct/20/panic-epidemic-ebola-us.
11
MSF utilized an existing anti-malaria program, run by MSF Switzerland (MSF-CH),
as a ready-made base from which to operate during the Ebola crisis. Hence, the Ebola
response was initially mediated by logistical factors and preexisting knowledge of the
region, with satellite data superimposed as a strategic tool (Lüge, 2014, p. 9).
12
According to an MSF report, ‘‘Google has no commercial incentive to improve its
maps in these [developing] countries” (Lüge, 2014, p. 17).
10
noted that the information furnished by the GIS officer had a ‘‘significant positive impact” on ground operations, by providing ‘‘a better
understanding of the emergency” and enabling a faster and more
targeted response to the outbreak (Lüge, 2014, p. 5).
The lack of telecommunications infrastructure in remote locations was overcome using mobile broadband equipment powered
by satellites. Eutelsat, for example, deployed a satellite, which
linked to terminals provided by the nonprofit organization
NetHope ‘‘in areas with little-to-no-existing communications
capacity with the intention of helping aid workers curb the spread
of Ebola”.13 GPS enabled medical teams to record their routes and
pinpoint foci of infection, which could then be evaluated in combination with other incoming data. Satellites provided analytical support
for mobile diagnostic laboratories. Real-time results are crucial to
prevent the spread of the disease in local populations and ensure
prompt handling and treatment of infected individuals and their
contacts. This approach enables those that are fearful of entering
military style Ebola hospitals and containment facilities to be tested
in their homes, as well as preventing those who are ill from undertaking perilous journeys to distant central camps (Tucker, 2014).
Moreover, there were a number of sociocultural obstacles to overcome, with doctors facing hostile communities, thus necessitating
good local communication networks to ensure their own safety
and removal from potentially dangerous situations (Wheeler, 2015).
To combat the problem of misinformation and scaremongering,
satellites were employed to disseminate public health education
across West Africa. ‘Fight Ebola’, a dedicated Ebola education channel, was launched by leading satellite operator SES and broadcast
by satellite to affected countries. Practical, culturally appropriate
public health messages delivered by well-known personalities
were designed to impart accurate and timely information en masse
to ease ground operations (Wheeler, 2015; SES, 2014).
Satellites were also central to long-term research on the disease’s emergence. The establishment of a satellite-mediated preemptive system to spot the environmental indicators that might
predispose a region to Ebola emergence has been the goal of a
number of research studies, both prior to and following the
2014–2015 epidemic. However, the compulsion to identify Ebola
‘hotspots’ has tended to deflect attention away from the broader
geographical contexts of disease risk. Much of the remotesensing research conducted before 2014 targeted Central Africa,
due to the region’s prehistory of Ebola outbreaks there since
1976 (Tucker et al., 2002). Yet enviroclimatic remote-sensing data
collated by Pinzon et al. (2004) had suggested that West Africa also
harbored suitable environmental conditions for Ebola emergence.
Thus, prior to the 2014 outbreak much of the ecological modeling
and geo-epidemiology work on the ground had failed to focus on
West Africa as a potential site of Ebola emergence.
Although many aspects of the zoonotic origins and transmission
pathways of Ebola remain unknown (Saéz et al., 2015), strides have
been made in identifying possible hosts (Peterson et al., 2007). Evidence has linked the potential source of human outbreaks to several bats species and their habitats can be mapped using spatial
epidemiology (Leendertz et al., 2016; Leroy et al., 2009, 2005).
Recent satellite-assisted studies conducted by Pigott et al. (2014,
2016) have demonstrated the ‘‘potential zoonotic transmission
niche” of Ebola to be more widely distributed through Central
and West Africa than previously thought, with populations of suspected reservoir bat species widespread in both regions. Some
22 million people in Central and West Africa may live in spillover
risk areas (Pigott et al., 2014, 2016), but predicting outbreaks
remains a challenge, as many of the variables that contribute to
13
See http://www.eutelsat.com/home/news/press-releases/Archives/2014/presslist-container/eutelsat-provides-equipment-and.html.
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
spillover events are tenuous. Consequently, there is a danger that
‘hotspotting’ from satellite data, as a predictive research approach,
may miss new sites of potential disease emergence. As the work of
Pigott et al. suggests, future geo-epidemiological research might
endeavor to integrate horizontal data collection with vertical
hotspotting. Harnessing the combined capacity of satellite mapping and remote-sensing data might enable researchers to connect
potential Ebola eco-niches with cross-territorial corridors of transmission (2014, 2016). Thus, while satellite imaging cannot replace
horizontal geo-epidemiological work, it can add a depth of perspective (Pigott et al., 2016). Perhaps the utility of predictive satellite data as a means of forecasting infectious disease emergence is
in revealing ecological ‘‘fault lines” where disease might arise as a
result of inherent vulnerabilities (Barton, 2016). Rather than focusing on hotspots, predictive remote-sensing research might track
these fault lines, where particular socioecological conditions converge and internal stressors – or ‘‘trigger events” as Pinzon et al.
(2004) describe them – may drive niche disease emergence.
4. Distant zoom: the Ebola enigma
SENTINEL-2A satellites are polar orbiting satellites launched by
the ESA in June 2015.14 The satellites were designed for multispectral high-resolution missions, including supporting ‘‘land management, agriculture and forestry, disaster control, humanitarian
relief operations, risk mapping, and security concerns” (Fig. 3). More
specifically, the satellites have been used to provide imagery that
may assist in ‘‘[pinpointing] potential fruit bat habitats” (ESA,
2014; Copernicus, 2014a) in order to ‘‘[solve] the Ebola enigma”
(ESA, 2003b). The aim of this high-resolution satellite imagery is
therefore predictive: to help scientists ascertain where an outbreak
might occur and to take action to prevent such an occurrence. As
DigitalGlobe – the company involved in processing the data and
the leading supplier of satellite imagery to the US intelligence community – insists, the purpose is to ‘‘make informed decisions
quickly” and to provide ‘‘actionable analytics”. The satellite’s name
is in fact apposite, since the technology works as a ‘sentinel’ device
that forewarns of future threats (Lakoff and Keck, 2013).
The image reproduced below from an ESA brochure, depicts a
view of the village of Kwendin in Nimba County, northeastern
Liberia (Fig. 4). This is an area deemed to be at high risk from an
epidemic of Ebola. Color has been added to the image to facilitate
interpretation. Buildings are identified in red15 beside a road with
two small oil palm plantations ringed in yellow surrounded by forest. According to an ESA gloss:
Liberia is experiencing cases of Ebola with numerous deaths.
Epidemiologists seek to identify isolated rural settlements surrounded by dense tropical forests and oil palm cultivations.
These are likely to attract fruit bats, which are one of the main
vectors of the Ebola virus (ESA, 2014).
The color-coded boundaries around the village houses and the
two plantations provide an interpretative framework for reading
the image as a whole (Wood, 1992, p. 124). In effect, these graphic
superimpositions identify locales of high risk. In so doing, they act
as filters that make certain features of the landscape legible, while
obscuring other dimensions. The image shows the current state of
the landscape but gives no indication of the historical pattern of
land-use: How long have Kwendin villagers been cultivating land
in the vicinity of the forest? Does the image provide evidence of
rapid ecological degradation? As Wallace et al. note in their discus-
29
sion of Ebola in Guinea, ‘‘Contrary to prelapsarian fantasies of
hunting/gathering, forest farmers have been cultivating oil palm
in one form or another for hundreds of years” (Wallace et al.,
2016, pp. 2–3).16 ‘‘While satellite data can reveal much about the
earth’s surface,” observes Litfin, ‘‘social meanings (and hence policy
implications) are not rendered transparent so easily” (Litfin, 2012, p.
81).
On the one hand, the image of Kwendin offers a strategic view
of a potential target – a site that has been construed as a likely
Ebola ‘hotspot’ on the basis that it shares ‘‘particular environmental characteristics associated with infected sites where either dead
animals are found or local people have acquired Ebola antibodies”
(ESA, 2003a). On the other hand, the image presents us with an
agroecological perspective wherein Ebola’s emergence is conceptualized in terms of the interdynamics of human and animal populations. A confluence of environmental conditions points to an
infectious disease’s presence in a particular location (Franklin,
2009). Socioecological and environmental stressors accumulate
until a tipping point is reached (Miller et al., 2010). Changes in
land-use and human encroachment into the rainforest – represented here by the ringed plantations – provide the preconditions
for ‘‘viral chatter” (Wolfe, 2011) and lethal spillovers (Daszak,
2000; Quammen, 2012). The ESA image depicts Kwendin as a front
line: a community on the edge of the forest where cultivated and
uncultivated lands are difficult to distinguish. Although the framing of the scattered houses suggests that Kwendin is cut off and
remote, the snaking dirt road on the left hand side of the image
intimates mobility and suggests an ominous pathway for disease
to disperse.
Satellite imagery, such as this, is intended as a resource to help
identify places that may be vulnerable to zoonotic diseases. Knowledge is imagined implicitly as ‘‘exposure of what is hidden”
(Herscher, 2014, p. 472). ‘‘All maps,” notes Koch, ‘‘argue the existence of something in a place” (2015, p. 66). As ESA articulates it
in the agency’s Copernicus promotional literature, ‘‘infectious diseases may not be able to hide for long”. Although the satellite is ‘‘an
entry point or gateway to closer views”, the high-resolution imagery it enables is ‘‘a site/sight that must be read” (Parks, 2009, p.
538; see also Parks, 2005, 2006). Furthermore, the identification
of Kwendin as a potential hotspot implies its opposite: the existence of a non-diseased environment. However, what would a
healthy baseline image look like? What ecological conditions
would characterize it? Pigott et al. note ‘‘the heterogeneities in
spillover risk that exist within Africa”, intimating that there is great
variety in risk-associated landscapes (2016).
A key criticism of the handling of the 2014 outbreak was the
missed opportunity to contain the disease before it spread to Conakry, Guinea’s capital (Koch, 2016). High levels of population
mobility in West Africa, including unregulated cross-border traffic,
are believed to have facilitated the rapid dissemination of the virus
across the region (IOM, 2016). One of the limitations of satellite
technology in a disease crisis scenario is its inability to spot the
early signs of an outbreak. It may act as an early warning system
and it may be used to manage an epidemic, but the critical phase
in between that might determine whether a disease such as Ebola
will remain contained, or spread, is invisible from space.
Although the image of Kwendin provides an environmental perspective on Ebola, with the disease’s emergence linked to specific
environmental features, it is also suggestive of a military viewpoint. As the cultural critic Rey Chow has noted, ‘‘in the age of
bombing, the world has also been transformed into – is essentially
conceived and grasped as – a target. To conceive of the world as a
14
See https://sentinel.esa.int/web/sentinel/missions/sentinel-2.
For interpretation of color in Fig. 4, the reader is referred to the web version of
this article.
15
16
See the analysis of satellite images showing similar land-use near Guéckédou in
Guinea in Wallace et al. (2016, p. 5).
30
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
Fig. 3. Ó Copernicus/ESA. The ESA SENTINEL constellation of satellites are each charged with a different mission. Sentinel 6 is due for launch in 2020.
Fig. 4. Ó ESA/G-ECO-MON/GeoVille. Image: DigitalGlobe. Kwendin Village.
target is to conceive of it as an object to be destroyed” (Chow, 2006,
p. 31).17 As Harris observes, satellite ‘‘imagery production is
attached to concrete and purposive action” (Harris, 2006, p. 101) –
in this case the identification of an Ebola site as a precondition for
the virus’s eventual elimination. Assuming, of course, that it exists
there. The WHO concluded a 1997 report on disease mapping and
17
See also Parks’s commentary on this (2012, pp. 196–197).
risk assessment by conceding that ‘‘problems remain with interpretation and with evaluation of the implications” (WHO, 1997).
‘‘Microscopes are not the only tools available to study disease”,
ESA declares in its publicity material. ‘‘A new ESA project employs
satellites to predict and help combat epidemic outbreaks, as well
as join the hunt for the origin of the deadly Ebola virus” (ESA,
2003a). This claim by space agencies and corporations that disease
can be ‘pinpointed’ from space is commonplace. As Kleiner
asserted in 1995: ‘‘Satellite (sensor) images can pinpoint the
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
breeding grounds of the mosquitoes that cause malaria, pick out
the tsetse fly’s favourite haunts and perhaps even identify places
where there is a risk of cholera” (Kleiner, 1995, p. 9). Despite the
implication in ESA’s promotional material that its satellites have
the capability to spot Ebola, the microbial disease agents in question are, of course, indiscernible; strands of ribonucleic acid
(RNA) encased in protein that require an electron microscope to
see. Neither, for that matter, can we see Kwendin’s population of
2000. Instead, we are offered a view that is ‘‘close up at a distance”
(Kurgan, 2013). The pathogenic threat, like the invisible inhabitants whose presence is discernible only second hand via their
imprint on the land, must be read through contextual information
and the superimposition of analytics, such as the color markers to
indicate houses and plantations. To borrow Kleiner’s expression,
what we are shown are ‘‘haunts” from which we may extrapolate
hidden presences. Satellites see traces of disease, not the disease
itself.
One of the most important benefits of an orbital perspective is
that it ‘‘[projects] power without projecting vulnerability” (quoted
in Chamayou, 2013, p. 12). In other words, satellites remove the
risks associated with on-the-ground public health work and the
dangers of contagion. To paraphrase Chamayou, in the coming
years it is likely that we will see the gradual ‘‘dronization” (2013,
p. 14) – Baudrillard’s ‘‘satellisation” (1994, p. 35) – of an increasing
portion of the global public health armamentarium.
Some vector-borne diseases, such as Rift Valley fever and malaria, have been linked to abnormally high rainfall and humidity, conditions that favor mosquito populations (Bosch, 2004). In the case
of Ebola, however, the environmental conditions driving disease
emergence and progression remain little understood (Bosch,
2004: Saéz et al., 2015). It is not therefore that satellite data are
more suitable to studying some diseases rather than others, but
that given the lack of any clear epidemiological model for Ebola,
remote-sensing technologies are necessarily of limited use at present (Pinzon and Tucker, 2007). In this sense, looking at a potential
site of Ebola from space is not dissimilar to viewing a climate
change image. The problem, as Schneider and Nocke argue, is that
we cannot see the problem since climate change exists as a phenomenon detectable across big data (Schneider and Nocke, 2014).
In other words, such satellite imagery invites the viewer to make
leaps of the imagination; it represents what Kurgan calls ‘‘the
opacity of transparency” (Kurgan, 2013, p. 24).
The image of Kwendin, like other views that pervaded the
media coverage of Ebola in 2014–2015, serves to reinforce stereotypes of Africa as a place of dark secrets – of latent threats – which
call forth a corresponding effort of exposure and enlightenment
(Fair and Parks, 2001; Pieterse, 1992). This is an ‘‘image-Africa”;
a discursive terrain constituted by an ‘‘accretion of images and figments and blanks” (Landau, 2002, p. 2). The image presents us with
a parameterized viewpoint. In so doing, it directs our gaze away
from socioecological complexity to targeted objects, delineated as
color-coded spaces. This hotspotting effect de-emphasizes contextual circumstances, although the potential remains to view the
image in terms of a broader relational dynamics. At the same time,
in disclosing potential vulnerabilities to emerging disease, Kwendin’s invisible inhabitants are posited both as victims of a hostile
tropical environment and as precipitators of future spillover
events.
There is a parallel between the latency of the disease – which
the image invites us to imagine lurking among the vegetation –
and the satellite image itself as an approximation that emerges
out of data. As Parks remarks of satellite imagery, ‘‘[because] it is
digital, its ontological status differs from that of the electronic
image. The satellite image is encoded with time coordinates that
index the moment of its acquisition, but since most satellite image
data is simply archived in huge supercomputers, its tense is one of
31
latency. Satellites are constantly and quietly scanning the earth, but
much of what they register is never seen or known” (Parks, 2005, p.
91). The god’s eye vantage made possible by satellite technology is
thus contingent: data must be paid for, selected, and processed
before anything can be seen. Moreover, the captured data cannot
verify the operational status of each site. Images need to be corroborated with ‘ground-truthing’ (Pickles, 1994). The scope of
decision-making enabled by these static images alone is therefore
necessarily limited.
5. Mapping Ebola: the digital divide
In their promotional material on the SENTINEL-2 satellite and
its role in the Ebola crisis, ESA note how the satellite provides
two scales of vision. While it enables the monitoring of ‘‘land cover
parameters such as oil palm cultivations, water bodies and general
vegetation cover”, it also offers ‘‘wide area coverage to map the
vast areas affected in West Africa” (ESA, 2014). During the 2014–
2015 Ebola outbreak, satellite imagery provided the basis for producing more comprehensive maps. Maps provided ‘‘graphic and
indexical images” of the emerging disease (Berland, 2009, p.
246). They also supported on-the-ground health-workers who
were required to negotiate difficult terrain, and they helped in
the monitoring of population movements (Figs. 5 and 6).
ESA satellite imagery and maps disclosed the region’s infrastructural deficiencies and the environmental fallout that results
from unregulated development. A satellite image of Freetown,
the capital of Sierra Leone, captured by an ESA satellite in December 2015, revealed how the city’s ‘‘growing population” and ‘‘unauthorized housing development” had resulted in the destruction of
hectares of mangrove vegetation.18 In a region with negligible
‘backbone assets’, satellite-based maps with their superimposed
grids suggest a counter-balancing ordering process. As Berland
observes of weather forecast maps, they imply ‘‘technological mastery of space” (Berland, 2009, p. 93). In the case of West Africa,
satellite-based maps produced during the Ebola outbreak transformed sovereign territories ‘‘into a navigable digital [domain]”
(Parks, 2012, p. 197), but did not reveal the sociocultural contexts
in which the disease was produced and circulated.
In Fig. 6, data are foisted onto the satellite basemap. This grid is
provisional and virtual; the ‘‘local infrastructure and facilities”
shown on the map are not material presences on the ground, but
reflect an improvised, hyper-spatial solution to an enduring structural problem – the absence of discernible urban planning. Data
sets are temporary superimpositions on the landscape designed
‘‘to ensure maximum operational efficiency” (Copernicus, 2014b)
in much the same ways as makeshift hospitals, health centers, or
refugee camps. In short, the map is a rhetorical device that seeks
to rationalize territory in order to facilitate interventions and
decision-making processes. A satellite image becomes a map when
it is overlaid with descriptive topographical information. Like
graphically constructed maps, these images require interpretation.
As Wood notes, map-making is a highly mediated activity and ‘‘the
interest served is masked” (Wood, 1992, pp. 70–94). This ambiguous aspect of the layered satellite-generated map reminds us of the
extent to which the modalities of humanitarianism and war, with
their emphasis on emergency response, overlap (Fassin and
Pandolfi, 2010). Moreover, while the orbital perspective implies a
vertical direction, the concept of data ‘layers’ suggests depth. Yet
the maps produced during the Ebola crisis, such as Fig. 6, cover
over the satellite-generated image. They reproduce a military cartographic approach that is structured along a horizontal axis and
gazes across, rather than ‘‘[cuts] through the landscape”
18
http://www.esa.int/spaceinimages/Images/2016/01/Sierra_Leone_River_Estuary.
32
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
Fig. 5. Ó DigitalGlobe provided under ESA GSC-DH DWC license (Copernicus, 2014a). WorldView 2 satellite image. The Copernicus Emergency Management Service was
activated in March 2014 (EMSR076) to assist epidemiologists investigating a link between oil palm cultivation and resident colonies of fruit bats, a suspected vector of the
Ebola virus. Residential areas marked on the map above (brown squares) within the green shaded zone of oil palms were identified as potential sites where it was predicted
Ebola patients might be more likely to be found. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
(Weizman, 2002). Ebola maps were understood by NGO agencies
expressly as a development of earlier colonial mapping practices.19
Such allusions to nineteenth-century cartography are telling,
since maps ‘‘formed an integral part of political discourse about
the colonization of Africa”. Cartography involved the formal
demarcation of boundaries that defined colonial possessions. Information furnished by maps on the location of natural resources,
roads and villages, ‘‘facilitated troop movements, settlement, and
commercial activities”. Graphic devices, including color-coding,
blank spaces, and the inscription of boundary lines legitimated
imperial territorial expansion (Bassett, 1994, pp. 316–317).
As we noted earlier, during the Ebola epidemic HOT launched
an online crowd-sourced app and mobilized cartographers to identify routes and dwellings (Koch, 2015). OSM provided web-based
editable maps that enabled contributors to freely view, edit, and
use the geographical data. While much was made during the epidemic of the ‘‘free and open data that can readily be integrated
with ground information” (ESA, 2014), in many rural areas of the
countries affected there is only partial access to the Internet. There
is thus a conspicuous asymmetry – a ‘digital divide’ (Fuchs and
Horak, 2008) – between the technological capacities that enable
the mapping and the situation on the ground, where there is likely
to be minimal connectivity and the majority of the population lack
electricity. In Liberia, for example, a country emerging from a
destructive civil war (1999–2003), over 90% of the country’s estimated 4.7 million population has no access to power, except for
private generators – ‘‘one of the lowest access rates in the world”.20
As an International Monetary Fund report noted in 2008: ‘‘Most
Liberians use palm oil, kerosene and candles for light” (IMF, 2008,
p. 29). At the same time, open-data maps, like the high-resolution
overhead imagery of disease ‘hotspots’, circulate freely on the Internet for the benefit of distant viewers (Perkins and Dodge, 2009).
Thus, while satellite technologies have certainly underpinned the
development of on-the-ground communication devices and
20
See https://www.usaid.gov/powerafrica/liberia.
Android’s Open Data Kit and Form Hub Technology, however, played a significant
role in the response to the recent Ebola outbreak in Nigeria (Tom-Aba et al., 2015).
21
19
Loyd, ‘Ebola mapping in Guinea: Humanitarian OpenStreetMap Team.’
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
33
Fig. 6. Ó CNES 2014, distribution Airbus Defence and Space Services/SPOT Images acquired on 01/12/2014 and 26/11/2014 (Copernicus, 2014b). Pléiades satellite image. A
second Copernicus EMS activation (EMSR110) in November 2014 used layered OpenStreetMap data to provide planning support to a Belgian medical mission heading to
Nzérékoré, Guinea, to assist Ebola patients. The map provided details of local infrastructure and facilities, including roads and residential areas, to ensure maximum
operational efficiency for the humanitarian aid team on the ground.
georeferenced platforms that depend on the GPS for their functionality, their use among local communities in West Africa is limited.21
The limitations of participatory, volunteered geographic information (VGI) map-making in the case of Ebola rehearse ongoing
debates about the use of ‘mashups’ in crisis mapping (Liu and
Palen, 2010). On the one hand, it has been argued that new
geotechnologies are providing possibilities for a more openended form of knowledge-production that enables individuals to
contribute to databases and engage in collaborative mapping
(Goodchild, 2007). On the other hand, as Litfin concludes: ‘‘New
networks of surveillance may decenter the state, but they do not
render it obsolete.” States are still vested with the authority to
issue licenses for commercial satellites, to determine the legal
operational framework, and to formulate policies for the agencies
they contract (Litfin, 2012, p. 85).
The asymmetry between distant technology-enabled data
extraction and affected communities who play a minimal role in
the mapping of their own locales is particularly striking in the
satellite image of Kwendin discussed above. Until recently, when
a biomass-powered microgrid was constructed by USAID to supply
248 households, Kwendin had no access to electricity.22 In 2012–
2103, the Kwendin Health Center and Vocational Training Center lost
their government funding (Sayegh, 2014). Kwendin’s ‘off-the-grid’
status and the unregulated activity suggested by haphazard land
use stand in stark contrast to the connectivity and commercial regulation of orbital space implied by the smooth operation of the overhead satellite. Indeed, satellite data in the form of high-resolution
imagery direct our gaze downward to examine how the spaces
below are organized (or not). In so doing, our attention is deflected
from looking upwards and considering how orbital ‘‘space is organized, who controls it and how it has been contested” (Parks,
2013, p. 62). ‘‘Assertions of ‘openness’”, write Perkins and Dodge,
‘‘have become co-opted by consumption capitalism, which depends
upon secrets for its rhetorical power and, paradoxically, is itself
21
Android’s Open Data Kit and Form Hub Technology, however, played a significant
role in the response to the recent Ebola outbreak in Nigeria (Tom-Aba et al., 2015).
22
See http://www.winrock.org/wp-content/uploads/2016/02/Subproject-briefs_070813-ACota.pdf.
34
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
implicated in hiding information” (Perkins and Dodge, 2009, p.559).
And as Harris remarks, ‘‘satellite imagery can not only ‘open up’ the
world (making it transparent), but can also ‘close down’ geographical
space under a regime of surveillance” (Harris, 2006, p.101). Given the
lack of Internet connectivity in many of the areas affected by Ebola,
the notion of crowd-sourcing was largely gestural. The majority of
the community had no online presence. Assertions of ‘openness’
and ‘free access’ were therefore directed at a global (Western)
constituency.
6. Conclusion: the geospatial future of global health
The Ebola outbreak in 2014–2015 ‘‘revealed serious shortcomings in national and international capacity to detect, monitor,
and respond to infectious disease outbreaks as they occur”
(Woolhouse et al., 2015). The epidemic also highlighted the important role that remote sensing is likely to play in managing disease
episodes in the future, since it offers ‘‘new opportunities to obtain
geospatial data about neighborhoods that may circumvent the limitations of traditional data sources” (Schootman et al., 2016). As
Schootman et al. have noted with reference to a range of geospatial
technologies including unmanned aerial vehicles, Google, and
location-based social media platforms: ‘‘By harnessing these technologies, public health research can not only monitor populations
and the environment, but intervene using novel strategies to
improve the public health” (Schootman et al., 2016).
Today satellite data-gathering and digital image-processing are
becoming central to the concept of ‘‘planetary health” surveillance,
‘‘based on the understanding that human health and human civilisation depend on flourishing natural systems and the wise stewardship of those natural systems” (Whitmee et al., 2015, p.
1974). International health agencies are increasingly focused on
preparedness with a growing emphasis on an integrated ‘one
health’ approach predicated on ‘‘an injunction to join up areas of
expertise and practice” (Craddock and Hinchliffe, 2015, p. 1) and
a recognition of the ‘‘historical scarcity of transdisciplinary
research and funding” (Whitmee et al., 2015, p. 1973). During
the 2014–2105 Ebola outbreak, satellites were usefully deployed
to assist in hazardous ground operations, and to identify potential
sites at risk. Yet the outbreak also revealed limitations, in particular a need for caution in using the technology to predict and define
the borders of Ebola hotspots. The parameterized view may work
to promote a targeted perspective predicated on a disease threat,
rather than to further understanding of disease ecologies. Furthermore, the temporary nature of such remote interventions in a crisis
may serve to undermine the case for permanent health infrastructure, with critical consequences for countries where infectious disease risks and social challenges converge.
Epidemiology and global health, we have argued, have progressively ‘‘come to collaborate on the production of geopolitical
knowledge and the accumulation of geopolitical power through
the deployment of satellite imagery” (Herscher, 2014, p. 486).
Orbital and aerial perspectives are increasingly defining how pandemics are studied and understood. As Herscher has observed, ‘‘the
imaginative geography” delineated by satellite imagery is producing a new form of ‘‘surveillant” culture (2014). In so arguing, we do
not seek to promote a contrarian view that minimizes the important role that satellite and other remote-sensing technologies are
undoubtedly playing in epidemiology and public health, particularly in sub-Saharan Africa that bears a disproportionate burden
of disease. Instead, our aim has been to foreground the cultural
and political dimensions of this ‘‘satellisation” of health.
Despite the use made of satellite data in epidemiology there has
been no sustained discussion in the public health or medical literature of the broader issues that this integration raises. Neither has
attention been paid to space technologies within the anthropological and cultural scholarship on Ebola.23 As Parks noted some time
ago in her analysis of satellites and televisual culture, despite the
pervasiveness of satellite data, the satellite itself remains ‘‘a structuring absence, a technology on the perimeter of everyday visibilities
and cultural theory” (Parks, 2005, p. 7). In short, we have sought to
draw attention to the broader social and political issues at stake in
their use and to suggest that tracing the tactical genealogy of satellite surveillance may help us to understand how high-tech public
health tools are merging with other discursive modalities. It is perplexing, given the progressive reliance of epidemiology on satellite
imagery, that there has been so little discussion of the broader implications of its deployment in public health.
There is now a substantive literature on the military use of
remote-sensing technologies and the ways they are shaping how
conflict is experienced and understood as an ‘‘everywhere war”
(Gregory, 2011a, 2011b; Williams, 2013). Cultural geographers
and epidemiologists have likewise considered the televisualization of disease from space, analyzing how global political
and economic processes have helped to create an econiche for
Ebola to take hold in West Africa. As Wallace et al. argue, local
landscapes and ecosystems have been transformed through the
promotion of monoculture oil palm, backed by global capital flows.
Disease emergence, they conclude, is linked to an agroeconomic
transition that is predicated on a neoliberal model of free trade,
private ownership, and the deregulation of markets (Wallace
et al., 2015, 2016).24 Satellite technologies are thus interconnected
to other forms of ‘verticality’ aside from the geopolitical, including
cost-cutting ‘vertical’ financing, which seeks to target specific diseases rather than invest in upgrading inadequate health systems.
Despite such work, however, anthropology and the social sciences,
while attentive to processes on the ground, have often been reluctant to look up and consider views of Ebola from space – a surprising
omission, given recent calls for the social sciences to ‘‘[elucidate] the
effects uneven power relations, discrepant risks, and variable access
to resources have on vulnerabilities and responses to disease outbreaks” (Craddock and Hinchliffe, 2015, p. 2; see also Bardosh, 2016).
The mobilization of space technologies and the entanglement of
different interests – national, international, and corporate – raise a
number of critical questions: Who are the stakeholders in this
technology? Who are the end-users? And who stands to benefit
from satellite-derived data? As we have seen, satellite technologies
depend upon complex interrelationships between different actors
with often divergent interests: commercial companies, international agencies, government institutions – including the military
– NGOs, and academic researchers. This assemblage is part of a
‘‘contracting nexus” that reflects a ‘‘new political economy of geographical intelligence” (Crampton et al., 2014). In his discussion of
NASA’s coordinated polar-orbiting and low inclination satellites
launched as part of an Earth Observation System (EOS), Lambright
notes how space technology programs are ‘‘susceptible to the pulls
and hauls of politics” and depend on ‘‘coalitions” of interests for
their development and implementation (Lambright, 1994, pp. 64,
57–64).
There is a significant disparity between so-called ‘end-users’
and the beneficiaries of this technology – in other words, afflicted
communities. Many satellite image-providers and organizations
involved in creating geospatial content are driven by explicit commercial imperatives. Their websites feature slick presentations of
their ‘products and services’. DigitalGlobe maintains that its
23
An insightful recent work, Representing Ebola: Culture, Law, and Public Discourse
about the 2013–2015 West African Ebola Outbreak, which deals in some detail with the
media coverage of the outbreak, does not mention remote sensing and there is no
index entry for satellite (Hasian, 2016).
24
See also https://neoliberalebola.wordpress.com/.
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
mission is to ‘‘put the world’s smartest images into everyone’s
hands, giving them confidence to make decisions that matter”.25
The reference maps of Guinea produced during the Ebola outbreak
under the ESA-EU Copernicus initiative identify their ‘‘core users”
as ‘‘Humanitarian Aid Operators” (Copernicus, 2014a). Despite such
claims, the ‘end-users’, whether NGO organizations or government
agencies, belong to the ‘‘contracting nexus” that reflects, as we noted
at the beginning of this paper, an ‘‘institutional interdependence”
(Parks, 2005, p. 77).
MSF points out that ‘‘good maps are valuable to all stakeholders” and accordingly a web-based ‘Map Centre’ was launched in
July 2014. However, security relating to processed satellite maps
is an emerging issue in the context of global health. While the base
image may not be contentious, the image overlaid with identifying
data may well be sensitive and give rise to accusations of espionage, particularly in conflict zones or politically sensitive regions
(Lüge, 2014, p. 37). In response, MSF’s Map Centre features layered
password-protected access that effectively takes the application
out of the public domain. MSF’s mapping initiative underscores a
tension within humanitarian responses between recognition of
the increasing importance of VGI surveillance and the need to
securitize data, especially given the reliance on external service
providers. During the Ebola crisis, satellite generated GIS maps
were also used as open negotiating tools to build relations with
local government officials and other NGOs on the ground. The distribution of data functioned as a bargaining chip between MSF and
other stakeholders, pointing to the complexity of establishing trust
on the ground while also operating in a secure vertical space. In its
post-epidemic recommendations, MSF notes that ‘‘goodwill can be
generated by sharing maps” (Lüge, 2014, pp. 21, 37).
It could also be argued that much of the satellite data obtained
under the guise of global public health does not in fact directly
benefit the communities or environments under scrutiny. Organizations, such as UNOSAT, have been established to address this
asymmetry, but they too are clients of commercial companies,
such as DigitalGlobe. Given the often opaque contractual relationships that underpin the space industry, conflicts of interests inevitably arise. After all, satellites are not dedicated to global health
issues but are servicing multiple clients’ requests from diverse sectors. As DigitalGlobe asserts, the company is ‘‘the trusted partner of
dozens of industries worldwide – from environmental monitoring
and mapmaking to defense and public safety”.26 Satellite companies may be conducting commercial natural resource exploration –
for example mining, ‘‘planning a pipeline, or routing a railroad”,
while participating in climate change monitoring, or humanitarian
flood relief projects.27 Given such conflicts, it is not perhaps surprising that local rumors circulated in West Africa that the outbreak was
in fact ‘‘a bioweapon designed by the United States military to
depopulate the planet” (Feuer, 2014).
As we have argued in this paper, the digitalization of the globe
that satellites have enabled has been driven in large part by a military worldview premised on the notion of strategic intervention
and an accumulation of ‘overhead assets’. Particularly post-9/11,
the nature of warfare has been shaped by ‘‘the slippery spaces
within which and through which it is conducted” (Gregory,
2011a, p. 239). As Gregory has suggested, this is an emergent, ‘‘everywhere war” that calls for constant surveillance, since the
demarcations of the battlespace are ambiguous. Similarly, we
might speak of an ‘‘everywhere war” being waged from space
against disease where the places and spaces of emergence are scattered and the emphasis is on vulnerable ‘‘global borderlands”
(Gregory, 2011a). The availability of aerial photography and satel-
26
27
See http://www.digitalglobe.com/about/our-company.
See http://www.satimagingcorp.com/about/.
35
lite monitoring has also shaped an expanding televisual news
entertainment culture. The ways in which public health innovations have become entangled with military security and corporate
expansion remain a critical area for further research. As Harris has
remarked, satellite imagery is a rich site for exploring ‘‘how power
and national sovereignty turn on the visual” (Harris, 2006, p. 101).
Today a top-down, vertical approach remains in tension with
intersecting horizontal influences. Thus, global health approaches
make use of satellite technologies to identify hotspots of disease,
while geo-epidemiological studies rely on horizontal data sets to
make predictions about where such diseases are most likely to
spread. Alternative vertical and horizontal economic models are
proposed, while targeted humanitarian responses coexist with participatory and voluntaristic map-mapping initiatives.28 These tensions, we have suggested, are manifest not only in the different
uses to which satellite images are put, but also in the different interpretative frames within which they are read. While satellite images
may be used to target hotspots, constraining vision to contemplation
of a latent disease site, the complexity and detail of the satellite view
itself, especially when combined with on the ground inputs, may
open up new opportunities for visualizing a complex human geography of vulnerability.
There are important consequences that stem from global
health’s progressive use of remote sensing. Biosurveillance for epidemics might be seen as an extension of earlier colonial and imperial endeavors to map foreign territories for resource extraction
and as part of pacification campaigns. Epidemic surveillance also
overlaps with bioprospecting, particularly given the use of remote
sensing for ‘‘resource management” (Belward and Valenzuela,
1991). At the same time, satellite imagery ignores the deeper
socioecological dynamics that drive infection. Instead, it offers up
surface views as objects for interpretation through the superimposition of data ‘layers’. Perhaps, as Elden (2013) suggests, it is more
appropriate to consider the vertical dimension as volumetric, to
better situate satellite involvement in the new spatial structuring
of epidemics and the ecologies that underlie them. Views of the
Earth from space, however, ignore history (Parks, 2009) and override local specificities (Whiteford and Manderson, 2000). How do
communities experiencing public health crises on the ground
understand remote-sensing interventions? Will the progressive
removal of public health operations to space be interpreted as
abandonment, or will it be welcomed by communities that are
weary of foreign interference in the name of health?
There is a need to view epidemic satellite imagery within
geopolitical contexts. An ‘‘aesthetic of abstraction and remoteness”, observe Perkins and Dodge, ‘‘connotes the [satellite] image
as a document of truth, and hides the political work the image is
employed to achieve” (Perkins and Dodge, 2009, p. 547). As Robbins has suggested, remote-sensing technologies produce characterizations of the environment that are often discrepant with
local views. ‘‘Satellite imagery”, he concludes, ‘‘is not an impartial
tool for the settlement of debates about land cover but is instead
the result of prior debates about the character of nature. Moreover,
such imagery acts as a force in the transformation of the environment; by fixing certain interpretations of the environment and
forcing certain forms of management, technology changes on the
land through a process of reverse adaptation” (Robbins, 2001, p.
161). What is required, we suggest, is a pushback against aerial
and orbital perspectives; a critique of how, by espousing remotesensing technologies, global health may be unwittingly looking
the wrong way.
28
Ooms et al. argue against the polarization of ‘vertical’ and ‘horizontal’ models,
suggesting the benefits of a ‘diagonal’ financing model (2008).
36
R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38
Acknowledgments
The research for this paper was supported by a grant from the
Research Grants Council of Hong Kong to Robert Peckham (HKU
Project Code 17607415: ‘Techno-Imperialism and the Origins of
Global Health’). We have benefitted greatly from the congenial
atmosphere of the Centre for the Humanities and Medicine
(CHM) at The University of Hong Kong; our appreciation, in particular, to the regular participants of CHM’s Science, Technology, and
Medicine Research Seminar for their encouragement and helpful
feedback. Finally, we thank the four anonymous reviewers for their
helpful comments on an earlier draft of this paper.
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