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

http://dx.doi.org/10.1016/j.geoforum.2017.01.0010016-7185/� 2017 Elsevier Ltd. All rights reserved.

⇑ Corresponding author.E-mail address: rpeckham@hku.hk (R. Peckham).

1 The Ebola outbreak has been traced to a two-year-old boy, who died in December2013 in Meliandou, a village in southeastern Guinea (Maron, 2014).

2 ‘‘Authorized Users” for the main part comprise national space agencies but alsoinclude 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.

3 Charlie Loyd, ‘Ebola mapping in Guinea: Humanitarian OpenStreetMa(March 25, 2014). Retrieved from: http://www.mapbox.com/blog/osm-ebping/.

Robert Peckham ⇑, Ria SinhaCentre for the Humanities and Medicine, The University of Hong Kong, Hong Kong

a r t i c l e i n f o a b s t r a c t

Article history:Received 16 September 2016Received in revised form 15 December 2016Accepted 3 January 2017

Keywords:SatellitesEpidemic intelligenceEbolaWest AfricaDigital divideVertical geopolitics

Satellite technologies are increasingly being deployed to manage infectious disease outbreaks. Althoughthere is a substantive literature concerned with the geopolitics of space and the ethical issues raised bythe use of remote sensing in warfare and counterinsurgency, little study has been made of the critical roleplayed 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-deriveddata, to investigate how overhead orbital and close-up viewpoints enabled by satellites are shaping atti-tudes to disease and determining responses to infectious threats. We argue that high-resolution satelliteimagery is acting as a spur to a new spatio-temporal targeting of disease that parallels the ever more ver-tical dimension of contemporary warfare. At the same time, this new visualization of disease is promotinga broader ecological perspective on pathogen emergence. How can these divergent perspectives be rec-onciled? In addressing this question, we analyze the different uses to which satellite imagery has beenput in tracking and mapping Ebola ‘hotspots’ across Guinea, Liberia, and Sierra Leone. We also considerthe institutional contexts that have enabled the acquisition of this imagery. Given the rapid integration ofspace technologies in epidemiology and health logistics, there is now a need to examine how and withwhat consequences remote-sensing and communication technologies may be reconfiguring the practicesand scope of global health.

� 2017 Elsevier Ltd. All rights reserved.

1. Introduction: technological convergence

Between December 2013 and December 2015, West Africaexperienced the largest epidemic of Ebola virus disease (EVD) inhistory, with more than 28,000 suspected cases across Guinea,Liberia, and Sierra Leone, and over 11,000 deaths.1 On 9 October2014, the International Charter for Space and Major Disasters – anagreement between ‘‘Authorized Users” to provide free space data‘‘to those affected by natural or man-made disasters” – was activatedby the US Geological Survey (USGS) on behalf of the US NationalGeospatial-Intelligence Agency (NGA) to monitor the Ebola outbreakin Sierra Leone (UK Space Agency, 2014). This marked the first timethe Charter’s space assets had been deployed to assist in containingan epidemic (CERN, 2014).2

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 sawa significant number of remote-sensing initiatives that involvedpartnerships between multiple national and international agenciesand commercial companies. The outbreak instigated a rush forhigh-resolution satellite imagery that would furnish the basis formore comprehensive mapping. As Mapbox – a company involvedin a humanitarian mapping project during the Ebola outbreak –notes on its website: ‘‘This is a region where the best availablemaps are often antiques from the colonial era, two generationsago.”3

Space data also acted as a spur to discussions across disciplinesabout the practical application of innovative technologies in themanagement of infectious disease. An international conference,‘Technology for Ebola’, sponsored by Microsoft, was held in Cairoin December 2014 under the motto ‘‘The tech industry canempower Africa in its fight against Ebola”. As one commentatornoted during the crisis: ‘‘The Ebola scare may turn out to be one

p Team’ola-map-

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of health care technology’s important trial runs, given the sheernumber of apps, mapping tools, collaboration platforms and evenrobots that have been recruited for duty.”4

In this paper, we focus on the Ebola outbreak in West Africa toexamine how epidemiological knowledge and communication sys-tems are becoming increasingly entwined. What are the implica-tions of this intertwinement for global health? In addressing thisquestion, we draw upon – and seek to contribute to – a growing lit-erature 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 explor-ing the role of media technologies, such as satellites, in reconfigur-ing visual practices and shaping how the ‘global’ is understood.Satellite images of earth are the upshot of complex interdependen-cies between state and non-state agencies, and are practicallyenabled by state and multinational financing. Rather than viewingsuch imagery as neutral data – the way that those promoting andselling the technology encourage us to do – the focus has shiftedonto the geopolitical contexts that determine how data is pro-duced, interpreted, and disseminated.

Epidemic image data generated by remote-sensing technolo-gies, we argue in this paper, are the outcome of a complex techno-logical and institutional matrix that extends from opticalinstruments to computer processing. During the Ebola crisis, theUN’s Operational Satellite Applications Programme (UNOSAT), adivision of the UN’s Institute for Training and Research (UNITAR),produced an Atlas of Ebola Care Facilities in Guinea, Liberia & SierraLeone to support emergency humanitarian assistance activities onthe ground (Figs. 1 and 2). The atlas relied on high-resolution ima-gery from three DigitalGlobe satellites – WorldView-2,WorldView-1, and Quickbird – but also involved the collaborationof numerous other organizations to process the imagery and creategeospatial content (UNITAR, 2014).

In a manner similar to Jody Berland’s description of weatherforecasting, epidemic surveillance and prediction involve a ‘‘tech-nical convergence and economic interdependency of a specifictechnological assemblage of satellite communication transmission,GPS monitoring, television, digital information processing, digitalgraphics, security systems, and the management of urban space”(Berland, 2009, p. 246). The term ‘satellite imagery’ thus under-plays the degree to which satellite technologies are contingenton an assemblage of different organizations with ‘‘different socialgoals and ways of understanding the hardware itself” (Mack,1990, p. 4). It also elides the different phases of the image produc-tion process: from the acquisition of data to their processing, spec-tral analysis and interpretation, and finally the development ofspecific information products (Lillesand et al., 2004, p. 3). Thisinterdependence of state agencies, NGOs, and other organizationsand corporations working as service providers, constitutes a ‘‘con-tracting nexus” that Crampton, Roberts, and Poorthuis identify as a‘‘new political economy of geographical intelligence” (Cramptonet al., 2014; see also Parks and Schwoch, 2012).

Until recently, geopolitics has tended to be understood as a fun-damentally ‘‘flat discourse”. As Weizman has observed: ‘‘It largelyignores the vertical dimension and tends to look across rather thanto cut through the landscape. This was the cartographic imagina-tion inherited from the military and political spatialities of themodern state” (Weizman, 2002). Over recent years, however, therehas been a fresh emphasis on the vertical dimension of geopolitics;on how aerial and orbital perspectives are reshaping notions of ter-ritory, 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). Retrievedfrom: https://gcn.com/articles/2014/10/22/ebola-technology.aspx.

‘‘prefigured a symptomatic shift in target-location”, while thedevelopment of spy-satellites and drones after World War IIenabled a ‘‘strategy of global vision” (Virilio, 1989, p. 1) thatchallenged existing cartographic techniques. In short, twentieth-century aerial and orbital technological innovations haveincreasingly moved geopolitics onto a vertical axis, and as a resulthave called for a new multi-dimensional representation of space(Weizman, 2002).

The contemporary dependence on satellite imagery for map-ping might be viewed as an extension of the state’s historical reli-ance on mapping to manage risks and threats (Crampton, 2003).However, the involvement of multiple non-state actors in the pro-duction and distribution of such imagery could be said to reflect ‘‘ashift in the institutional locus of disciplinary power” and a diffu-sion of surveillance that challenges a ‘‘state-centric view of worldpolitics” (Litfin, 2012, p. 67).

As Parks notes, ‘‘It is especially when technologies converge thatwe notice and understand their definitions” (Parks, 2005, p. 9).Today epidemiology and public health are being reconfiguredthrough the uses of high-resolution satellite imagery and global-positioning (GP) maps that are also central to military strategyand underpin commercial entertainment. Media broadcasting,mobile phones, air travel, as well as national security, all rely onthe same constellation of satellite technologies. ‘‘When technolo-gies converge”, Parks observes, ‘‘they develop in discursive, eco-nomic, and institutional interdependence with one another.Convergence, then, is a relational model of understanding howtechnologies inflect, inform, and interact with one another in pro-cesses of their emergence” (Parks, 2005, p. 77).

This inter-reliance of public and private sectors has triggeredheated debates about the potential for conflicts of interest, partic-ularly in the context of security policy, which ‘‘is in the midst of afundamental shift in tone and quality as a result of remote sensingsatellite technology” (Livingston and Robinson, 2003; see alsoO’Connell et al., 2001). Satellite imagery constitutes an importantcomponent of the military ‘‘surveillant assemblage” (Haggertyand Ericson, 2000) that has been succinctly defined as ‘‘a heteroge-neous set of intelligence gathering and command systems whoseunity depended upon their smooth and transparent interoperabil-ity” (Harris, 2006, p. 103). The purchase by the Pentagon in 2001 ofthe rights to images of Afghanistan taken by the IKONOS satelliteowned and operated by DigitalGlobe, is one example of the devo-lution of security technology. This use of commercial high-resolution satellites is widely understood to carry political andoperational security challenges for national policy-makers(Livingston and Robinson, 2003).

From the late 1980s, disease emergence has been increasinglyconstrued as a problem of global security. As the preface to theinfluential 1992 report Emerging Infections: Microbial Threats toHealth in the United States declared: ‘‘There is nowhere in the worldfrom which we are remote and no one from whom we are discon-nected. Consequently, some infectious diseases that now affectpeople in other parts of the world represent potential threats tothe United States because of global interdependence, moderntransportation, trade, and changing social and cultural patterns”(Lederberg et al., 1992, p. v). Public health security became theframework for dealing with new biological threats produced bythis global connectedness (Lakoff and Collier, 2008, p. 7). In his cri-tique of Western humanitarian and peace interventionism, Duf-field argues that development has functioned primarily as amechanism for maintaining and policing the divide between devel-opment and underdevelopment (Duffield, 2007). In this paper wesuggest, similarly, that the mobilization of geosurveillance tech-nologies for health and humanitarianism is further merging devel-opment and security agendas (Duffield, 2001). Rather than relyingon biodefense – on safeguarding national borders – the emphasis

Figs. 1 and 2. � 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 inMacenta, 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 thetime of image capture was not reported (UNITAR, 2014).

5 See http://history.nasa.gov/sputnik/.

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has shifted to ‘‘biosecurity interventions”: to detecting and manag-ing disease outbreaks ‘‘should such events occur across interna-tional borders” (WHO quoted in Lakoff and Collier, 2008, p. 8).The targeting of disease ‘hotspots’ in developing countries resem-bles a form of precision warfare. Indeed, the same remote-sensing technologies are being used in public health and militarycampaigns waged sometimes in the same places (Peckham, 2016).

Although there is now a substantive body of scientific workapplying satellite data to specific cases of disease surveillanceand management, this has tended to be largely descriptive. Therehas been negligible analysis to date of how these data might relateto practices of power and to a vertical geopolitics, as recent studiesof warfare have suggested. Equally, little investigation has beenmade of the institutional contexts that determine the data’s use.Given the dependency on satellites in telecommunications anddirect broadcasting, remote sensing and GP, it is surprising thatso little interest has been shown in how ‘‘orbital space is structuredto make such practices possible” (Parks, 2013, p. 62).

The use of remote-sensing technologies during the Ebola crisisbecame an important subsidiary story in the news media withwidespread coverage of how Western space technologies werebeing arrayed in the ‘fight’ against disease. The emphasis on satel-lites and real-time communication and information systems con-trasted to conventional disaster images of gowned healthcarepersonnel, makeshift health centers, isolation facilities, and body-bagged victims. Implicitly, state-of-the-art space technology waspitted against the backwardness of a region where ‘primitive’ bur-ial rituals were widely held responsible for spreading infection(Nielsen et al., 2015). High-resolution satellite imagery laid barethe region’s lack of infrastructure. It underscored a glaring discrep-ancy between the apparently seamless connectivity and ease ofoperation embodied in satellites, on the one hand, and the commu-nication impediments presented to response teams on the ground

by a vast landmass with poor transportation links, an absence ofhealthcare facilities, partial access to electricity, and dense forest,on the other. As we shall see, satellite data served toreaffirm 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 ‘‘technicaland 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 undertakento track the technical and tactical genealogy of remote-sensingtechnologies that have been recruited for epidemic intelligence,surveillance, and reconnaissance. By the early 1970s, satelliteshad gained a new prominence as scientific tools. A RAND reportcommissioned by the US Army Air Forces and published in 1946presented ‘‘an engineering analysis of the possibilities of designinga man-made satellite”. While undoubtedly of ‘‘great militaryvalue”, the report noted that a ‘‘satellite vehicle with appropriateinstrumentation can be expected to be one of the most potent sci-entific tools of the twentieth century” (RAND, 1946). It was notuntil October 1957, however, that the first artificial space satellite,Sputnik 1, was launched by the Soviet Union. The size of a beachball, it took some 98 minutes to orbit the earth and triggered aspace race.5 The CORONA reconnaissance satellite was successfullylaunched by the United States in August 1960 (Ruffner, 1995, pp.xiii–xvi).

The term ‘remote sensing’ was apparently coined in1958 (Warner et al., 2009, p. x), the year that the US National

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Aeronautics and Space Administration (NASA) was created by Pres-ident Eisenhower. It came to designate ‘‘the science – and art – ofidentifying, observing and measuring an object without cominginto direct contact with it”.6 The idea that satellites might be usefulin the fight against disease had been broached in the 1960s. In 1965,the director of the USGS, William Pecora, ‘‘proposed the idea of acivilian remote-sensing satellite program to gather facts about thenatural resources of the earth” (Loveland, 2012, p. 14). In July1972, NASA launched its first Earth Resources Technology Satellite(ERTS-1) – renamed Landsat-1 in 1975 – with the aim of collectingenvironmental data about temperature, rainfall, humidity, and vege-tation (Mack, 1990). These are limiting factors that affect the activityof pathogens and their natural reservoirs, as well as the behavior ofdisease vectors, such as mosquitoes. As NASA administrator James C.Fisher remarked in 1974: ‘‘If I had to pick one spacecraft, one spaceage development, to help save the world, I would pick ERTS and theoperational satellites which I believe will be evolved from it later inthis decade” (Wilford, 1974). In 1985, NASA launched a Global Mon-itoring of Human Health (GMHH) program, focused on vector-bornediseases, including malaria and Lyme disease. This led to the estab-lishment a decade later of the Center for Health Applications of Aero-space Related Technologies (CHAART), explicitly ‘‘to provideeducation, training, and outreach to investigators from the humanhealth community” (Wood et al., 2000, pp. 336–337).

Since the mid-1990s, when CHAART was founded, ‘‘an increas-ing number of health studies have used remotely sensed data formonitoring, surveillance, or risk mapping, particularly of vector-borne diseases” (Beck et al., 2000, p. 217). Research has suggestedthat many emerging and reemerging infectious diseases are con-nected to climatic and environmental change. Rising sea levels,floods, and forest fires, for example, are viewed as drivers of infec-tion. Environmental biosurveillance by satellites has thus provideda basis for epidemic early warning systems (Ford et al., 2009;Nichols et al., 2014; Pinzon et al., 2004). Socioecological driversof infectious disease are also being analyzed through satellite ima-gery – urbanization, changes in land use, poverty, migration, andhuman 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; Rogerset al., 2002; Sewe et al., 2016; Weiss et al., 2014). Google Earth,which integrates satellite imagery with aerial photography andimages generated by global information systems (GIS), has beenmobilized to track the spread of polio in the Democratic Republicof Congo (DRC) (Kamadjeu, 2009). Satellite-based assessmentshave been made of hydro-climatic conditions related to epidemiccholera (Jutla et al., 2015), and satellites have also been used tostudy predictor variables in outbreaks of Rift Valley fever in Kenya(Linthicum et al., 1999) and Senegal (Vignolles et al., 2010), as wellas meningococcal meningitis across the so-called ‘African Meningi-tis Belt’ (Thomson et al., 2006).

Tele-epidemiology has thus become an increasingly importantdimension of global health, particularly since the mid-1990s, whencommercial satellite imagery became more readily available(Kalluri et al., 2007). In 1994, President Clinton had allowed privatecompanies to sell high-resolution satellite imagery ‘‘to domesticand foreign customers” and sanctioned the export of turnkeyremote sensing systems. The aim of this policy was explicitly ‘‘tofind new commercial applications for defense technologies andenhance US global competitiveness in the international remote

6 See http://earthobservatory.nasa.gov/Features/RemoteSensing/.

sensing marketplace”.7 At the Third United Nations Conference onthe Exploration and Peaceful Uses of Outer Space (UNISPACE III) heldin Austria in 1999, infectious disease mitigation and prevention wereidentified as important areas and the conference called for the inte-gration of space technologies into ‘‘medical research, surveillanceand control programmes on a global scale” (Dinas et al., 2015;UNISPACE III, 1999, p. 21).

In the twenty-first century, tele-epidemiology is an evolvingfield that combines ‘‘epidemiology and space technology appliedto human and animal health” (Brazeau et al., 2014), with anemphasis on the connections between disease and climatic andenvironmental variations (Hay, 2000; Marechal et al., 2008). NASA,along with international organizations, including the WHO – inpartnership with commercial operations – have been instrumentalin the development of tele-epidemiology. The European SpaceAgency (ESA) sponsored an Earth observation for epidemiologyproject, EPIDEMIO, between 2004 and 2006. This used Earth obser-vation and land-based data to monitor the environmental condi-tions that drive infections (Gemperli et al., 2004). EPIDEMIO alsosupported on-the-ground epidemic response efforts, providingdata from the SPOT-5 and IKONOS satellites for epidemiologicalurban mapping during an outbreak of Marburg virus disease(MVD) in Angola (ESA, 2005). The SAFE (Satellites for Epidemiol-ogy) pilot project, also funded by ESA, focused on the use of satel-lite communication services during biological crises (Chronakiet al., 2007). The ESA noted that ‘‘the SAFE pilot project is a goodillustration of the added value of satellites – with the service pro-vided by space answering the needs on the ground” (Wagstaff,2008, p. 88). As Beck, Lobitz, and Wood noted at the beginning ofthe millennium: ‘‘Increased computing power and spatial model-ing capabilities of geographic information systems could extendremote sensing into operational disease surveillance and control”(Beck et al., 2000, p. 217).

Over a decade since this pronouncement was made, advances inGIS are making high-resolution global data increasingly available,accessible, and affordable (Hay et al., 2006). The ability to incorpo-rate ancillary geo-coded data ‘layers’ has improved the accuracy ofsatellite image analysis, while the Internet has facilitated the stor-age and dissemination of these data. ‘‘Satellite systems”, write Pur-kis and Klemas, ‘‘have become the defining technology in ourability to quantify global change” (Purkis and Klemas, 2011, p. 5).These systems are now being applied ever more widely to modelthe prevalence of infectious diseases (Weiss et al., 2014). Remotesensing is being used, not only to establish outbreak patterns andtrack vector movements, but also to assist with diagnostics andtreatment, 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 Thevirus, which belongs to the Filoviridae family of filoviruses, istransmitted to people from wild animals and subsequently spreadsthrough human-to-human contact. The disease first appeared intwo concurrent outbreaks in 1976: in Nzara and Maridi insouth-western Sudan, and in the village of Yambuku, 682 milesnortheast of Kinshasa in the DRC (formerly Zaire) (IC, 1978;Pattyn et al., 1977; WHO, 1978). The disease takes its name fromthe River Ebola, a tributary of the Congo River, that runs throughthe northern DRC (Piot, 2013, pp. 56–57).

PDD-NSC 23 ‘US policy on foreign access to remote sensing space capabilities’(March 10, 1994). On the profound implications of this market liberalization forsatellite imagery, see Dehqanzada and Florini (2000). On the implications of Clinton’spolicy, see Baker (1997).

8 Ebola virus disease (EVD) was formerly known as Ebola hemorrhagic fever.

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The recent Ebola outbreak in West Africa is the largest since1976. The last epidemic in Uganda between 2000 and 2001 saw425 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 con-firmed cases of the disease occurred in March 2014 (Baize et al.,2014; Bausch and Schwarz, 2014). On 8 August 2014, the WHOannounced that the Ebola epidemic in West Africa was a ‘‘publichealth emergency of international concern” (PHEIC) under the Inter-national 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 inSenegal, Nigeria, and Mali (ECDC, 2014).

The scale of the Ebola outbreak in West Africa prompted a glo-bal response that reflected international concerns over the dis-ease’s pandemic potential. Cases in the United States, Spain, andthe United Kingdom generated widespread media coverage and adegree of global panic.10 While the ground response in West Africawas highly visible in the media, remote-sensing technologies werealso employed to track the disease. Satellites were engaged to mon-itor isolated rural communities, providing mapping data that sup-ported on-the-ground logistics and contact tracing (CERN, 2014).According to the ESA, one of the problems faced by health agenciesin mapping past epidemics is outdated ground information. Accessto current visual data is critical in planning personnel deploymentand identifying likely infection routes. In addition, potential Ebolaoutbreak sites cover large areas, so real-time ground data help tofocus research by highlighting regions of concern that warrant fur-ther study (ESA, 2003b).

At the street level, satellite mapping was used to help MédecinsSans Frontières (MSF) response teams navigate their way to andaround the worst affected towns and villages.11 MSF had signed aframework agreement in late 2013 to collaborate with CartONG, aFrench NGO specializing in humanitarian mapping. For the first time,a dedicated GIS officer was deployed on the ground in Guéckédouprefecture, 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 regularlyuploaded to a satellite map, allowing for timely interventions. Asone commentator remarked: ‘‘That map translated the scientific intothe operational” (Lüge, 2014, p. 19). Past relief operations had typi-cally relied on schematic hand drawn maps and basic Google Earthimages. However, these did not provide the requisite level of detailand accurate local information to guide ground operatives in haz-ardous environments, where rapid response to reported cases isoften crucial.12 CartONG purchased Pleiades and SPOT 6 regionalsatellite images from Airbus Defence and Space (other images wereprovided free) to produce reliable base maps that could be overlaidwith critical operational information. To identify villages, streets,and buildings the images were further processed by the Humanitar-ian OpenStreetMap Team (HOT), a volunteer group within Mapbox,and the results posted online, including a map of Guéckédou thatwas uploaded to the UN’s Office for the Coordination of Humanitar-ian Affairs’ website, ReliefWeb (ADS, 2016). Processed mappingimages were retained by MSF to build a database that would buildcapacity for existing and future operations in the region. Operatives

9 See http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/.10 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 Ebolaresponse was initially mediated by logistical factors and preexisting knowledge of theregion, 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 itsmaps in these [developing] countries” (Lüge, 2014, p. 17).

noted that the information furnished by the GIS officer had a ‘‘signif-icant positive impact” on ground operations, by providing ‘‘a betterunderstanding of the emergency” and enabling a faster and moretargeted response to the outbreak (Lüge, 2014, p. 5).

The lack of telecommunications infrastructure in remote loca-tions was overcome using mobile broadband equipment poweredby satellites. Eutelsat, for example, deployed a satellite, whichlinked to terminals provided by the nonprofit organizationNetHope ‘‘in areas with little-to-no-existing communicationscapacity with the intention of helping aid workers curb the spreadof Ebola”.13 GPS enabled medical teams to record their routes andpinpoint foci of infection, which could then be evaluated in combina-tion with other incoming data. Satellites provided analytical supportfor mobile diagnostic laboratories. Real-time results are crucial toprevent the spread of the disease in local populations and ensureprompt handling and treatment of infected individuals and theircontacts. This approach enables those that are fearful of enteringmilitary style Ebola hospitals and containment facilities to be testedin their homes, as well as preventing those who are ill from under-taking perilous journeys to distant central camps (Tucker, 2014).Moreover, there were a number of sociocultural obstacles to over-come, with doctors facing hostile communities, thus necessitatinggood local communication networks to ensure their own safetyand removal from potentially dangerous situations (Wheeler, 2015).

To combat the problem of misinformation and scaremongering,satellites were employed to disseminate public health educationacross West Africa. ‘Fight Ebola’, a dedicated Ebola education chan-nel, was launched by leading satellite operator SES and broadcastby satellite to affected countries. Practical, culturally appropriatepublic health messages delivered by well-known personalitieswere designed to impart accurate and timely information en masseto ease ground operations (Wheeler, 2015; SES, 2014).

Satellites were also central to long-term research on the dis-ease’s emergence. The establishment of a satellite-mediated pre-emptive system to spot the environmental indicators that mightpredispose a region to Ebola emergence has been the goal of anumber of research studies, both prior to and following the2014–2015 epidemic. However, the compulsion to identify Ebola‘hotspots’ has tended to deflect attention away from the broadergeographical contexts of disease risk. Much of the remote-sensing research conducted before 2014 targeted Central Africa,due to the region’s prehistory of Ebola outbreaks there since1976 (Tucker et al., 2002). Yet enviroclimatic remote-sensing datacollated by Pinzon et al. (2004) had suggested that West Africa alsoharbored suitable environmental conditions for Ebola emergence.Thus, prior to the 2014 outbreak much of the ecological modelingand geo-epidemiology work on the ground had failed to focus onWest Africa as a potential site of Ebola emergence.

Although many aspects of the zoonotic origins and transmissionpathways of Ebola remain unknown (Saéz et al., 2015), strides havebeen made in identifying possible hosts (Peterson et al., 2007). Evi-dence has linked the potential source of human outbreaks to sev-eral bats species and their habitats can be mapped using spatialepidemiology (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 transmissionniche” of Ebola to be more widely distributed through Centraland West Africa than previously thought, with populations of sus-pected reservoir bat species widespread in both regions. Some22 million people in Central and West Africa may live in spilloverrisk areas (Pigott et al., 2014, 2016), but predicting outbreaksremains a challenge, as many of the variables that contribute to

3 See http://www.eutelsat.com/home/news/press-releases/Archives/2014/press-st-container/eutelsat-provides-equipment-and.html.

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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 ofPigott et al. suggests, future geo-epidemiological research mightendeavor to integrate horizontal data collection with verticalhotspotting. Harnessing the combined capacity of satellite map-ping and remote-sensing data might enable researchers to connectpotential Ebola eco-niches with cross-territorial corridors of trans-mission (2014, 2016). Thus, while satellite imaging cannot replacehorizontal geo-epidemiological work, it can add a depth of per-spective (Pigott et al., 2016). Perhaps the utility of predictive satel-lite data as a means of forecasting infectious disease emergence isin revealing ecological ‘‘fault lines” where disease might arise as aresult of inherent vulnerabilities (Barton, 2016). Rather than focus-ing on hotspots, predictive remote-sensing research might trackthese fault lines, where particular socioecological conditions con-verge 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 bythe ESA in June 2015.14 The satellites were designed for multi-spectral high-resolution missions, including supporting ‘‘land man-agement, agriculture and forestry, disaster control, humanitarianrelief operations, risk mapping, and security concerns” (Fig. 3). Morespecifically, the satellites have been used to provide imagery thatmay 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 istherefore predictive: to help scientists ascertain where an outbreakmight occur and to take action to prevent such an occurrence. AsDigitalGlobe – the company involved in processing the data andthe leading supplier of satellite imagery to the US intelligence com-munity – insists, the purpose is to ‘‘make informed decisionsquickly” and to provide ‘‘actionable analytics”. The satellite’s nameis in fact apposite, since the technology works as a ‘sentinel’ devicethat forewarns of future threats (Lakoff and Keck, 2013).

The image reproduced below from an ESA brochure, depicts aview of the village of Kwendin in Nimba County, northeasternLiberia (Fig. 4). This is an area deemed to be at high risk from anepidemic of Ebola. Color has been added to the image to facilitateinterpretation. Buildings are identified in red15 beside a road withtwo small oil palm plantations ringed in yellow surrounded by for-est. According to an ESA gloss:

Liberia is experiencing cases of Ebola with numerous deaths.Epidemiologists seek to identify isolated rural settlements sur-rounded by dense tropical forests and oil palm cultivations.These are likely to attract fruit bats, which are one of the mainvectors of the Ebola virus (ESA, 2014).

The color-coded boundaries around the village houses and thetwo plantations provide an interpretative framework for readingthe image as a whole (Wood, 1992, p. 124). In effect, these graphicsuperimpositions identify locales of high risk. In so doing, they actas filters that make certain features of the landscape legible, whileobscuring other dimensions. The image shows the current state ofthe landscape but gives no indication of the historical pattern ofland-use: How long have Kwendin villagers been cultivating landin the vicinity of the forest? Does the image provide evidence ofrapid ecological degradation? As Wallace et al. note in their discus-

14 See https://sentinel.esa.int/web/sentinel/missions/sentinel-2.15 For interpretation of color in Fig. 4, the reader is referred to the web version othis article.

16 See the analysis of satellite images showing similar land-use near Guéckédou inGuinea in Wallace et al. (2016, p. 5).

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sion of Ebola in Guinea, ‘‘Contrary to prelapsarian fantasies ofhunting/gathering, forest farmers have been cultivating oil palmin one form or another for hundreds of years” (Wallace et al.,2016, pp. 2–3).16 ‘‘While satellite data can reveal much about theearth’s surface,” observes Litfin, ‘‘social meanings (and hence policyimplications) are not rendered transparent so easily” (Litfin, 2012, p.81).

On the one hand, the image of Kwendin offers a strategic viewof a potential target – a site that has been construed as a likelyEbola ‘hotspot’ on the basis that it shares ‘‘particular environmen-tal characteristics associated with infected sites where either deadanimals are found or local people have acquired Ebola antibodies”(ESA, 2003a). On the other hand, the image presents us with anagroecological perspective wherein Ebola’s emergence is conceptu-alized in terms of the interdynamics of human and animal popula-tions. A confluence of environmental conditions points to aninfectious disease’s presence in a particular location (Franklin,2009). Socioecological and environmental stressors accumulateuntil a tipping point is reached (Miller et al., 2010). Changes inland-use and human encroachment into the rainforest – repre-sented here by the ringed plantations – provide the preconditionsfor ‘‘viral chatter” (Wolfe, 2011) and lethal spillovers (Daszak,2000; Quammen, 2012). The ESA image depicts Kwendin as a frontline: a community on the edge of the forest where cultivated anduncultivated lands are difficult to distinguish. Although the fram-ing of the scattered houses suggests that Kwendin is cut off andremote, the snaking dirt road on the left hand side of the imageintimates mobility and suggests an ominous pathway for diseaseto disperse.

Satellite imagery, such as this, is intended as a resource to helpidentify places that may be vulnerable to zoonotic diseases. Knowl-edge is imagined implicitly as ‘‘exposure of what is hidden”(Herscher, 2014, p. 472). ‘‘All maps,” notes Koch, ‘‘argue the exis-tence of something in a place” (2015, p. 66). As ESA articulates itin the agency’s Copernicus promotional literature, ‘‘infectious dis-eases may not be able to hide for long”. Although the satellite is ‘‘anentry point or gateway to closer views”, the high-resolution ima-gery it enables is ‘‘a site/sight that must be read” (Parks, 2009, p.538; see also Parks, 2005, 2006). Furthermore, the identificationof Kwendin as a potential hotspot implies its opposite: the exis-tence of a non-diseased environment. However, what would ahealthy baseline image look like? What ecological conditionswould characterize it? Pigott et al. note ‘‘the heterogeneities inspillover risk that exist within Africa”, intimating that there is greatvariety in risk-associated landscapes (2016).

A key criticism of the handling of the 2014 outbreak was themissed opportunity to contain the disease before it spread to Con-akry, Guinea’s capital (Koch, 2016). High levels of populationmobility in West Africa, including unregulated cross-border traffic,are believed to have facilitated the rapid dissemination of the virusacross the region (IOM, 2016). One of the limitations of satellitetechnology in a disease crisis scenario is its inability to spot theearly signs of an outbreak. It may act as an early warning systemand it may be used to manage an epidemic, but the critical phasein between that might determine whether a disease such as Ebolawill remain contained, or spread, is invisible from space.

Although the image of Kwendin provides an environmental per-spective on Ebola, with the disease’s emergence linked to specificenvironmental features, it is also suggestive of a military view-point. As the cultural critic Rey Chow has noted, ‘‘in the age ofbombing, the world has also been transformed into – is essentiallyconceived and grasped as – a target. To conceive of the world as a

Fig. 3. � 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. � ESA/G-ECO-MON/GeoVille. Image: DigitalGlobe. Kwendin Village.

30 R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38

target is to conceive of it as an object to be destroyed” (Chow, 2006,p. 31).17 As Harris observes, satellite ‘‘imagery production isattached to concrete and purposive action” (Harris, 2006, p. 101) –in this case the identification of an Ebola site as a precondition forthe virus’s eventual elimination. Assuming, of course, that it existsthere. 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 interpre-tation 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 employssatellites to predict and help combat epidemic outbreaks, as wellas join the hunt for the origin of the deadly Ebola virus” (ESA,2003a). This claim by space agencies and corporations that diseasecan be ‘pinpointed’ from space is commonplace. As Kleinerasserted in 1995: ‘‘Satellite (sensor) images can pinpoint the

18 http://www.esa.int/spaceinimages/Images/2016/01/Sierra_Leone_River_Estuary.

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breeding grounds of the mosquitoes that cause malaria, pick outthe tsetse fly’s favourite haunts and perhaps even identify placeswhere there is a risk of cholera” (Kleiner, 1995, p. 9). Despite theimplication in ESA’s promotional material that its satellites havethe capability to spot Ebola, the microbial disease agents in ques-tion are, of course, indiscernible; strands of ribonucleic acid(RNA) encased in protein that require an electron microscope tosee. Neither, for that matter, can we see Kwendin’s population of2000. Instead, we are offered a view that is ‘‘close up at a distance”(Kurgan, 2013). The pathogenic threat, like the invisible inhabi-tants whose presence is discernible only second hand via theirimprint on the land, must be read through contextual informationand the superimposition of analytics, such as the color markers toindicate houses and plantations. To borrow Kleiner’s expression,what we are shown are ‘‘haunts” from which we may extrapolatehidden presences. Satellites see traces of disease, not the diseaseitself.

One of the most important benefits of an orbital perspective isthat it ‘‘[projects] power without projecting vulnerability” (quotedin Chamayou, 2013, p. 12). In other words, satellites remove therisks associated with on-the-ground public health work and thedangers of contagion. To paraphrase Chamayou, in the comingyears it is likely that we will see the gradual ‘‘dronization” (2013,p. 14) – Baudrillard’s ‘‘satellisation” (1994, p. 35) – of an increasingportion of the global public health armamentarium.

Some vector-borne diseases, such as Rift Valley fever andmalar-ia, have been linked to abnormally high rainfall and humidity, con-ditions that favor mosquito populations (Bosch, 2004). In the caseof Ebola, however, the environmental conditions driving diseaseemergence and progression remain little understood (Bosch,2004: Saéz et al., 2015). It is not therefore that satellite data aremore suitable to studying some diseases rather than others, butthat given the lack of any clear epidemiological model for Ebola,remote-sensing technologies are necessarily of limited use at pre-sent (Pinzon and Tucker, 2007). In this sense, looking at a potentialsite of Ebola from space is not dissimilar to viewing a climatechange image. The problem, as Schneider and Nocke argue, is thatwe cannot see the problem since climate change exists as a phe-nomenon detectable across big data (Schneider and Nocke, 2014).In other words, such satellite imagery invites the viewer to makeleaps of the imagination; it represents what Kurgan calls ‘‘theopacity of transparency” (Kurgan, 2013, p. 24).

The image of Kwendin, like other views that pervaded themedia coverage of Ebola in 2014–2015, serves to reinforce stereo-types of Africa as a place of dark secrets – of latent threats – whichcall 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 fig-ments and blanks” (Landau, 2002, p. 2). The image presents us witha parameterized viewpoint. In so doing, it directs our gaze awayfrom socioecological complexity to targeted objects, delineated ascolor-coded spaces. This hotspotting effect de-emphasizes contex-tual circumstances, although the potential remains to view theimage in terms of a broader relational dynamics. At the same time,in disclosing potential vulnerabilities to emerging disease, Kwen-din’s invisible inhabitants are posited both as victims of a hostiletropical environment and as precipitators of future spilloverevents.

There is a parallel between the latency of the disease – whichthe image invites us to imagine lurking among the vegetation –and the satellite image itself as an approximation that emergesout of data. As Parks remarks of satellite imagery, ‘‘[because] it isdigital, its ontological status differs from that of the electronicimage. The satellite image is encoded with time coordinates thatindex the moment of its acquisition, but since most satellite imagedata is simply archived in huge supercomputers, its tense is one of

latency. Satellites are constantly and quietly scanning the earth, butmuch of what they register is never seen or known” (Parks, 2005, p.91). The god’s eye vantage made possible by satellite technology isthus contingent: data must be paid for, selected, and processedbefore anything can be seen. Moreover, the captured data cannotverify the operational status of each site. Images need to be corrob-orated with ‘ground-truthing’ (Pickles, 1994). The scope ofdecision-making enabled by these static images alone is thereforenecessarily limited.

5. Mapping Ebola: the digital divide

In their promotional material on the SENTINEL-2 satellite andits role in the Ebola crisis, ESA note how the satellite providestwo scales of vision. While it enables the monitoring of ‘‘land coverparameters such as oil palm cultivations, water bodies and generalvegetation cover”, it also offers ‘‘wide area coverage to map thevast areas affected in West Africa” (ESA, 2014). During the 2014–2015 Ebola outbreak, satellite imagery provided the basis for pro-ducing more comprehensive maps. Maps provided ‘‘graphic andindexical images” of the emerging disease (Berland, 2009, p.246). They also supported on-the-ground health-workers whowere required to negotiate difficult terrain, and they helped inthe monitoring of population movements (Figs. 5 and 6).

ESA satellite imagery and maps disclosed the region’s infras-tructural deficiencies and the environmental fallout that resultsfrom unregulated development. A satellite image of Freetown,the capital of Sierra Leone, captured by an ESA satellite in Decem-ber 2015, revealed how the city’s ‘‘growing population” and ‘‘unau-thorized housing development” had resulted in the destruction ofhectares of mangrove vegetation.18 In a region with negligible‘backbone assets’, satellite-based maps with their superimposedgrids suggest a counter-balancing ordering process. As Berlandobserves of weather forecast maps, they imply ‘‘technological mas-tery of space” (Berland, 2009, p. 93). In the case of West Africa,satellite-based maps produced during the Ebola outbreak trans-formed sovereign territories ‘‘into a navigable digital [domain]”(Parks, 2012, p. 197), but did not reveal the sociocultural contextsin which the disease was produced and circulated.

In Fig. 6, data are foisted onto the satellite basemap. This grid isprovisional and virtual; the ‘‘local infrastructure and facilities”shown on the map are not material presences on the ground, butreflect an improvised, hyper-spatial solution to an enduring struc-tural problem – the absence of discernible urban planning. Datasets are temporary superimpositions on the landscape designed‘‘to ensure maximum operational efficiency” (Copernicus, 2014b)in much the same ways as makeshift hospitals, health centers, orrefugee camps. In short, the map is a rhetorical device that seeksto rationalize territory in order to facilitate interventions anddecision-making processes. A satellite image becomes a map whenit is overlaid with descriptive topographical information. Likegraphically constructed maps, these images require interpretation.As Wood notes, map-making is a highly mediated activity and ‘‘theinterest served is masked” (Wood, 1992, pp. 70–94). This ambigu-ous aspect of the layered satellite-generated map reminds us of theextent to which the modalities of humanitarianism and war, withtheir emphasis on emergency response, overlap (Fassin andPandolfi, 2010). Moreover, while the orbital perspective implies avertical direction, the concept of data ‘layers’ suggests depth. Yetthe maps produced during the Ebola crisis, such as Fig. 6, coverover the satellite-generated image. They reproduce a military car-tographic approach that is structured along a horizontal axis andgazes across, rather than ‘‘[cuts] through the landscape”

Fig. 5. � DigitalGlobe provided under ESA GSC-DH DWC license (Copernicus, 2014a). WorldView 2 satellite image. The Copernicus Emergency Management Service wasactivated in March 2014 (EMSR076) to assist epidemiologists investigating a link between oil palm cultivation and resident colonies of fruit bats, a suspected vector of theEbola 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 predictedEbola 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.)

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(Weizman, 2002). Ebola maps were understood by NGO agenciesexpressly 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 aboutthe colonization of Africa”. Cartography involved the formaldemarcation of boundaries that defined colonial possessions. Infor-mation furnished by maps on the location of natural resources,roads and villages, ‘‘facilitated troop movements, settlement, andcommercial activities”. Graphic devices, including color-coding,blank spaces, and the inscription of boundary lines legitimatedimperial territorial expansion (Bassett, 1994, pp. 316–317).

As we noted earlier, during the Ebola epidemic HOT launchedan online crowd-sourced app and mobilized cartographers to iden-tify routes and dwellings (Koch, 2015). OSM provided web-basededitable maps that enabled contributors to freely view, edit, anduse the geographical data. While much was made during the epi-demic of the ‘‘free and open data that can readily be integratedwith ground information” (ESA, 2014), in many rural areas of the

19 Loyd, ‘Ebola mapping in Guinea: Humanitarian OpenStreetMap Team.’

countries affected there is only partial access to the Internet. Thereis thus a conspicuous asymmetry – a ‘digital divide’ (Fuchs andHorak, 2008) – between the technological capacities that enablethe mapping and the situation on the ground, where there is likelyto be minimal connectivity and the majority of the population lackelectricity. In Liberia, for example, a country emerging from adestructive civil war (1999–2003), over 90% of the country’s esti-mated 4.7 million population has no access to power, except forprivate generators – ‘‘one of the lowest access rates in the world”.20

As an International Monetary Fund report noted in 2008: ‘‘MostLiberians use palm oil, kerosene and candles for light” (IMF, 2008,p. 29). At the same time, open-data maps, like the high-resolutionoverhead imagery of disease ‘hotspots’, circulate freely on the Inter-net for the benefit of distant viewers (Perkins and Dodge, 2009).Thus, while satellite technologies have certainly underpinned thedevelopment of on-the-ground communication devices and

See https://www.usaid.gov/powerafrica/liberia.1 Android’s Open Data Kit and Form Hub Technology, however, played a significantle in the response to the recent Ebola outbreak in Nigeria (Tom-Aba et al., 2015).

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ro

Fig. 6. � CNES 2014, distribution Airbus Defence and Space Services/SPOT Images acquired on 01/12/2014 and 26/11/2014 (Copernicus, 2014b). Pléiades satellite image. Asecond Copernicus EMS activation (EMSR110) in November 2014 used layered OpenStreetMap data to provide planning support to a Belgian medical mission heading toNzérékoré, Guinea, to assist Ebola patients. The map provided details of local infrastructure and facilities, including roads and residential areas, to ensure maximumoperational efficiency for the humanitarian aid team on the ground.

R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38 33

georeferenced platforms that depend on the GPS for their function-ality, their use among local communities in West Africa is limited.21

The limitations of participatory, volunteered geographic infor-mation (VGI) map-making in the case of Ebola rehearse ongoingdebates about the use of ‘mashups’ in crisis mapping (Liu andPalen, 2010). On the one hand, it has been argued that newgeotechnologies are providing possibilities for a more open-ended form of knowledge-production that enables individuals tocontribute to databases and engage in collaborative mapping(Goodchild, 2007). On the other hand, as Litfin concludes: ‘‘Newnetworks of surveillance may decenter the state, but they do notrender it obsolete.” States are still vested with the authority toissue licenses for commercial satellites, to determine the legaloperational framework, and to formulate policies for the agenciesthey contract (Litfin, 2012, p. 85).

The asymmetry between distant technology-enabled dataextraction and affected communities who play a minimal role in

21 Android’s Open Data Kit and Form Hub Technology, however, played a significanrole 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.

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the mapping of their own locales is particularly striking in thesatellite image of Kwendin discussed above. Until recently, whena biomass-powered microgrid was constructed by USAID to supply248 households, Kwendin had no access to electricity.22 In 2012–2103, the Kwendin Health Center and Vocational Training Center losttheir government funding (Sayegh, 2014). Kwendin’s ‘off-the-grid’status and the unregulated activity suggested by haphazard landuse stand in stark contrast to the connectivity and commercial reg-ulation of orbital space implied by the smooth operation of the over-head satellite. Indeed, satellite data in the form of high-resolutionimagery direct our gaze downward to examine how the spacesbelow are organized (or not). In so doing, our attention is deflectedfrom looking upwards and considering how orbital ‘‘space is orga-nized, 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 dependsupon secrets for its rhetorical power and, paradoxically, is itself

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’ theworld (making it transparent), but can also ‘close down’ geographicalspace under a regime of surveillance” (Harris, 2006, p.101). Given thelack of Internet connectivity in many of the areas affected by Ebola,the notion of crowd-sourcing was largely gestural. The majority ofthe community had no online presence. Assertions of ‘openness’and ‘free access’ were therefore directed at a global (Western)constituency.

3 An insightful recent work, Representing Ebola: Culture, Law, and Public Discoursebout the 2013–2015 West African Ebola Outbreak, which deals in some detail with theedia coverage of the outbreak, does not mention remote sensing and there is nodex entry for satellite (Hasian, 2016).4 See also https://neoliberalebola.wordpress.com/.

6. Conclusion: the geospatial future of global health

The Ebola outbreak in 2014–2015 ‘‘revealed serious shortcom-ings 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 impor-tant role that remote sensing is likely to play in managing diseaseepisodes in the future, since it offers ‘‘new opportunities to obtaingeospatial data about neighborhoods that may circumvent the lim-itations of traditional data sources” (Schootman et al., 2016). AsSchootman et al. have noted with reference to a range of geospatialtechnologies including unmanned aerial vehicles, Google, andlocation-based social media platforms: ‘‘By harnessing these tech-nologies, public health research can not only monitor populationsand the environment, but intervene using novel strategies toimprove the public health” (Schootman et al., 2016).

Today satellite data-gathering and digital image-processing arebecoming central to the concept of ‘‘planetary health” surveillance,‘‘based on the understanding that human health and human civil-isation depend on flourishing natural systems and the wise stew-ardship of those natural systems” (Whitmee et al., 2015, p.1974). International health agencies are increasingly focused onpreparedness with a growing emphasis on an integrated ‘onehealth’ approach predicated on ‘‘an injunction to join up areas ofexpertise and practice” (Craddock and Hinchliffe, 2015, p. 1) anda recognition of the ‘‘historical scarcity of transdisciplinaryresearch and funding” (Whitmee et al., 2015, p. 1973). Duringthe 2014–2105 Ebola outbreak, satellites were usefully deployedto assist in hazardous ground operations, and to identify potentialsites at risk. Yet the outbreak also revealed limitations, in particu-lar a need for caution in using the technology to predict and definethe borders of Ebola hotspots. The parameterized view may workto promote a targeted perspective predicated on a disease threat,rather than to further understanding of disease ecologies. Further-more, the temporary nature of such remote interventions in a crisismay serve to undermine the case for permanent health infrastruc-ture, with critical consequences for countries where infectious dis-ease risks and social challenges converge.

Epidemiology and global health, we have argued, have progres-sively ‘‘come to collaborate on the production of geopoliticalknowledge and the accumulation of geopolitical power throughthe deployment of satellite imagery” (Herscher, 2014, p. 486).Orbital and aerial perspectives are increasingly defining how pan-demics are studied and understood. As Herscher has observed, ‘‘theimaginative geography” delineated by satellite imagery is produc-ing a new form of ‘‘surveillant” culture (2014). In so arguing, we donot seek to promote a contrarian view that minimizes the impor-tant role that satellite and other remote-sensing technologies areundoubtedly playing in epidemiology and public health, particu-larly in sub-Saharan Africa that bears a disproportionate burdenof disease. Instead, our aim has been to foreground the culturaland political dimensions of this ‘‘satellisation” of health.

Despite the use made of satellite data in epidemiology there hasbeen no sustained discussion in the public health or medical liter-ature of the broader issues that this integration raises. Neither has

attention been paid to space technologies within the anthropolog-ical and cultural scholarship on Ebola.23 As Parks noted some timeago in her analysis of satellites and televisual culture, despite thepervasiveness of satellite data, the satellite itself remains ‘‘a struc-turing absence, a technology on the perimeter of everyday visibilitiesand cultural theory” (Parks, 2005, p. 7). In short, we have sought todraw attention to the broader social and political issues at stake intheir use and to suggest that tracing the tactical genealogy of satel-lite surveillance may help us to understand how high-tech publichealth tools are merging with other discursive modalities. It is per-plexing, given the progressive reliance of epidemiology on satelliteimagery, that there has been so little discussion of the broader impli-cations of its deployment in public health.

There is now a substantive literature on the military use ofremote-sensing technologies and the ways they are shaping howconflict is experienced and understood as an ‘‘everywhere war”(Gregory, 2011a, 2011b; Williams, 2013). Cultural geographersand epidemiologists have likewise considered the tele-visualization of disease from space, analyzing how global politicaland economic processes have helped to create an econiche forEbola to take hold in West Africa. As Wallace et al. argue, locallandscapes and ecosystems have been transformed through thepromotion of monoculture oil palm, backed by global capital flows.Disease emergence, they conclude, is linked to an agroeconomictransition that is predicated on a neoliberal model of free trade,private ownership, and the deregulation of markets (Wallaceet al., 2015, 2016).24 Satellite technologies are thus interconnectedto other forms of ‘verticality’ aside from the geopolitical, includingcost-cutting ‘vertical’ financing, which seeks to target specific dis-eases 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 reluc-tant to look up and consider views of Ebola from space – a surprisingomission, given recent calls for the social sciences to ‘‘[elucidate] theeffects uneven power relations, discrepant risks, and variable accessto resources have on vulnerabilities and responses to disease out-breaks” (Craddock and Hinchliffe, 2015, p. 2; see also Bardosh, 2016).

The mobilization of space technologies and the entanglement ofdifferent interests – national, international, and corporate – raise anumber of critical questions: Who are the stakeholders in thistechnology? Who are the end-users? And who stands to benefitfrom satellite-derived data? As we have seen, satellite technologiesdepend upon complex interrelationships between different actorswith often divergent interests: commercial companies, interna-tional 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 geo-graphical intelligence” (Crampton et al., 2014). In his discussion ofNASA’s coordinated polar-orbiting and low inclination satelliteslaunched as part of an Earth Observation System (EOS), Lambrightnotes how space technology programs are ‘‘susceptible to the pullsand hauls of politics” and depend on ‘‘coalitions” of interests fortheir 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, afflictedcommunities. Many satellite image-providers and organizationsinvolved in creating geospatial content are driven by explicit com-mercial imperatives. Their websites feature slick presentations oftheir ‘products and services’. DigitalGlobe maintains that its

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mission is to ‘‘put the world’s smartest images into everyone’shands, giving them confidence to make decisions that matter”.25

The reference maps of Guinea produced during the Ebola outbreakunder the ESA-EU Copernicus initiative identify their ‘‘core users”as ‘‘Humanitarian Aid Operators” (Copernicus, 2014a). Despite suchclaims, the ‘end-users’, whether NGO organizations or governmentagencies, belong to the ‘‘contracting nexus” that reflects, as we notedat the beginning of this paper, an ‘‘institutional interdependence”(Parks, 2005, p. 77).

MSF points out that ‘‘good maps are valuable to all stakehold-ers” and accordingly a web-based ‘Map Centre’ was launched inJuly 2014. However, security relating to processed satellite mapsis an emerging issue in the context of global health. While the baseimage may not be contentious, the image overlaid with identifyingdata may well be sensitive and give rise to accusations of espi-onage, particularly in conflict zones or politically sensitive regions(Lüge, 2014, p. 37). In response, MSF’s Map Centre features layeredpassword-protected access that effectively takes the applicationout of the public domain. MSF’s mapping initiative underscores atension within humanitarian responses between recognition ofthe increasing importance of VGI surveillance and the need tosecuritize data, especially given the reliance on external serviceproviders. During the Ebola crisis, satellite generated GIS mapswere also used as open negotiating tools to build relations withlocal government officials and other NGOs on the ground. The dis-tribution of data functioned as a bargaining chip between MSF andother stakeholders, pointing to the complexity of establishing truston the ground while also operating in a secure vertical space. In itspost-epidemic recommendations, MSF notes that ‘‘goodwill can begenerated by sharing maps” (Lüge, 2014, pp. 21, 37).

It could also be argued that much of the satellite data obtainedunder the guise of global public health does not in fact directlybenefit the communities or environments under scrutiny. Organi-zations, such as UNOSAT, have been established to address thisasymmetry, but they too are clients of commercial companies,such as DigitalGlobe. Given the often opaque contractual relation-ships that underpin the space industry, conflicts of interests inevi-tably arise. After all, satellites are not dedicated to global healthissues but are servicing multiple clients’ requests from diverse sec-tors. As DigitalGlobe asserts, the company is ‘‘the trusted partner ofdozens of industries worldwide – from environmental monitoringand mapmaking to defense and public safety”.26 Satellite compa-nies may be conducting commercial natural resource exploration –for example mining, ‘‘planning a pipeline, or routing a railroad”,while participating in climate change monitoring, or humanitarianflood relief projects.27 Given such conflicts, it is not perhaps surpris-ing that local rumors circulated in West Africa that the outbreak wasin fact ‘‘a bioweapon designed by the United States military todepopulate the planet” (Feuer, 2014).

As we have argued in this paper, the digitalization of the globethat satellites have enabled has been driven in large part by a mil-itary worldview premised on the notion of strategic interventionand an accumulation of ‘overhead assets’. Particularly post-9/11,the nature of warfare has been shaped by ‘‘the slippery spaceswithin which and through which it is conducted” (Gregory,2011a, p. 239). As Gregory has suggested, this is an emergent, ‘‘ev-erywhere war” that calls for constant surveillance, since thedemarcations of the battlespace are ambiguous. Similarly, wemight speak of an ‘‘everywhere war” being waged from spaceagainst disease where the places and spaces of emergence are scat-tered and the emphasis is on vulnerable ‘‘global borderlands”(Gregory, 2011a). The availability of aerial photography and satel-

26 See http://www.digitalglobe.com/about/our-company.27 See http://www.satimagingcorp.com/about/.

28 Ooms et al. argue against the polarization of ‘vertical’ and ‘horizontal’ models,suggesting the benefits of a ‘diagonal’ financing model (2008).

lite monitoring has also shaped an expanding televisual newsentertainment culture. The ways in which public health innova-tions have become entangled with military security and corporateexpansion remain a critical area for further research. As Harris hasremarked, satellite imagery is a rich site for exploring ‘‘how powerand national sovereignty turn on the visual” (Harris, 2006, p. 101).

Today a top-down, vertical approach remains in tension withintersecting horizontal influences. Thus, global health approachesmake use of satellite technologies to identify hotspots of disease,while geo-epidemiological studies rely on horizontal data sets tomake predictions about where such diseases are most likely tospread. Alternative vertical and horizontal economic models areproposed, while targeted humanitarian responses coexist with par-ticipatory and voluntaristic map-mapping initiatives.28 These ten-sions, we have suggested, are manifest not only in the differentuses to which satellite images are put, but also in the different inter-pretative frames within which they are read. While satellite imagesmay be used to target hotspots, constraining vision to contemplationof a latent disease site, the complexity and detail of the satellite viewitself, especially when combined with on the ground inputs, mayopen up new opportunities for visualizing a complex human geogra-phy of vulnerability.

There are important consequences that stem from globalhealth’s progressive use of remote sensing. Biosurveillance for epi-demics might be seen as an extension of earlier colonial and impe-rial endeavors to map foreign territories for resource extractionand as part of pacification campaigns. Epidemic surveillance alsooverlaps with bioprospecting, particularly given the use of remotesensing for ‘‘resource management” (Belward and Valenzuela,1991). At the same time, satellite imagery ignores the deepersocioecological dynamics that drive infection. Instead, it offers upsurface views as objects for interpretation through the superimpo-sition of data ‘layers’. Perhaps, as Elden (2013) suggests, it is moreappropriate to consider the vertical dimension as volumetric, tobetter situate satellite involvement in the new spatial structuringof epidemics and the ecologies that underlie them. Views of theEarth from space, however, ignore history (Parks, 2009) and over-ride local specificities (Whiteford and Manderson, 2000). How docommunities experiencing public health crises on the groundunderstand remote-sensing interventions? Will the progressiveremoval of public health operations to space be interpreted asabandonment, or will it be welcomed by communities that areweary of foreign interference in the name of health?

There is a need to view epidemic satellite imagery withingeopolitical contexts. An ‘‘aesthetic of abstraction and remote-ness”, observe Perkins and Dodge, ‘‘connotes the [satellite] imageas a document of truth, and hides the political work the image isemployed to achieve” (Perkins and Dodge, 2009, p. 547). As Rob-bins has suggested, remote-sensing technologies produce charac-terizations of the environment that are often discrepant withlocal views. ‘‘Satellite imagery”, he concludes, ‘‘is not an impartialtool for the settlement of debates about land cover but is insteadthe result of prior debates about the character of nature. Moreover,such imagery acts as a force in the transformation of the environ-ment; by fixing certain interpretations of the environment andforcing certain forms of management, technology changes on theland through a process of reverse adaptation” (Robbins, 2001, p.161). What is required, we suggest, is a pushback against aerialand orbital perspectives; a critique of how, by espousing remote-sensing technologies, global health may be unwittingly lookingthe wrong way.

36 R. Peckham, R. Sinha / Geoforum 80 (2017) 24–38

Acknowledgments

The research for this paper was supported by a grant from theResearch Grants Council of Hong Kong to Robert Peckham (HKUProject Code 17607415: ‘Techno-Imperialism and the Origins ofGlobal Health’). We have benefitted greatly from the congenialatmosphere of the Centre for the Humanities and Medicine(CHM) at The University of Hong Kong; our appreciation, in partic-ular, to the regular participants of CHM’s Science, Technology, andMedicine Research Seminar for their encouragement and helpfulfeedback. Finally, we thank the four anonymous reviewers for theirhelpful comments on an earlier draft of this paper.

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