Russia’s Remote Sensing Industry

Remote sensing is a segment of the space sector that has been developed not just with the intelligence and military purposes to support other business sectors (Broniatowski et al. 2008). The earth observation market constitutes a significant component of the space economy, with revenues estimated at $ 2.3 billion, out of $ 122.58 billion for all the commercial space services and products (Ricard et al. 2015). In 2014, remote sensing accounted for about 13 percent of all operational satellites globally. Forecasts suggest that the industry is expected to grow threefold in the next decade, to reach about $ 6 billion by 2022 (Clark et al. 2014). Frolov (2011) notes that the remote sensing industry is concentrated among a few countries, which can be attributed to the costs of satellites ‚Äď this further compels global cooperation between the emerging space powers. Many authors state that Russia plays a significant role in space industry (Harvey 2007). However, its share in the global remote sensing market is small, accounting for 0.2 percent of the global market share (OECD 2011). This literature review has three objectives: to explore the impact of the remote sensing industry on Russia‚Äôs and global economy; its effect on Russia‚Äôs relationship with other countries; and the current and future state of the industry in Russia.

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History of Remote Sensing

The concept of remote sensing emerged during the 1960s to refer to aerial photography (Asadi, Vuppala & Reddy 2007). Since then, the techniques for aerial photography have changed from using planes to satellites in an attempt to cover more land space and facilitate regular monitoring. Initially, remote sensing was developed for military applications during the Cold War with the purpose of spying on enemies. Currently, the application of remote sensing is diverse and has been commercialized in addition to military uses. Corporations and nations are now capable of launching satellites that can be used to take images of Earth (Payson & Davidian 2015). From a commercial standpoint, the progress in remote sensing technologies offers numerous opportunities for various economic sectors such as mining, construction, planning, agriculture, conservation, fishing and forestry (Campbell & Wynne 2011). In addition, advancements in remote sensing technologies have enabled taking of more detailed Earth images at relatively lower costs. 

Impact of the Remote Sensing Industry on Russia’s and Global Economy

When compared to other economic industries, the performance of space sector is considered relatively successful after the recent economic crisis (Frolov 2011). There is an agreement among various authors that mapping the space industry is still a complex process. As a result, economic data relating to the space sector are largely unknown for various countries, especially in emerging segments in the overall space economy such as remote sensing (Venturini, Verbano & Matsumoto 2013; Zhao 2005). In Russia, a literature search revealed only one study that has been conducted to investigate the impact of the remote sensing industry on the economy in forest management. The limited literature on Russia’s remote sensing sector can be attributed to the fact that the industry is emerging and still in its infancy stages. Moreover, the lack of scholarly interest in the Russian remote sensing sector can be attributed to the fact that Russia is an insignificant player in the global remote sensing industry (Frolov & Ganichev 2014;  Venturini & Verbano 2014). Therefore, in order to understand the likely effects of the remote sensing on Russia’s economy, studies of the sector in other countries will be analysed.

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Numerous approaches have been used by scholars to explore the economic impacts of the remote sensing. The first is the macroeconomic approach, which emphasizes on the determining the impact on the entire economy of a country by gauging Gross Domestic Product (GDP) contributions, changes in income levels, employment, and other economy-wide measures (Campbell & Wynne 2011; Lautenbacher 2006). The second method is the microeconomic approach, which emphasizes the impact of a sector in the consumer welfare via the price mechanism (Sandau, Roeser & Valenzuela 2014). The most common methodological approach adopted by the authors when exploring the economic impacts of the remote sensing industry entails using descriptive case studies. 

In Russia, remote sensing applications have been used in forest management, which resulted in significant cost savings (Malysheva et al. 2000). The forest areas in Russia covers about 23 percent of the world’s closed forests; however, a considerable portion of this forests are neither frequently monitored nor managed, which is because of the lack of developed infrastructure for the remote regions in the northern Russia. It makes monitoring and managing forests an expensive affair when using on-ground methods. Malysheva et al. (2000) argue that despite the promise of remote sensing applications in Russia, their application in forest management is suboptimal, but nonetheless acknowledged the significant cost-savings from the use of remote sensing in forestry management in Russia. 

Case studies in other regions have also highlighted the crucial role that remote sensing plays in the economy. Petroni, Venturini and Santini (2010) outlined the specific sectors directly impacted by the remote sensing industry, which include agriculture, energy, aviation/transport, tourism and recreation. For instance, in Australia, ACIL Tasman (2010) reported the productivity impact of remote sensing in various sectors including the agricultural, forestry, fisheries, petroleum and mining, transport and storage, communications, tourism, biosecurity, and maritime safety sectors. Based on their survey, ACIL Tasman (2010) estimated productivity improvements of 15 percent in the Australian economy attributed to remote sensing. Overall, the authors explored the economic value of remote sensing based on three perspectives, which include direct GDP contribution, impact on productivity, and other benefits to society from using remote sensing. ACIL Tasman (2010) concluded that the direct GDP contribution of GDP in Australia is $ 1.4 billion, impact on productivity is $ 1.9 billion, and other benefits estimated to be $ 1 billion. Therefore, remote sensing stimulates the economy through GDP, productivity, and benefits to society.

In addition, remote sensing stimulates the economy through productivity gains and cost efficiencies. Venturini and Verbano (2014) pointed out that weather forecast, which depends on the considerable meteorological satellite coverage, is currently a routine service for governments, business organisations, and citizens. In terms of the effect on the economy, estimates by Sheehan (2007) indicated that in the US, the benefits associated with investments in weather warnings and forecasts are estimated to be $ 31.5 billion annually. Cost efficiencies from remote sensing technologies can be attributed to the cost savings associated with using the technology (Leloglu & Kocaoglan 2008). In this respect, remote sensing service providers have the capability of offering a more detailed view of the Earth at relatively lower costs. According to Campbell and Wynne (2011), remote sensing applications are cost efficient because of their relatively larger geographical scope of coverage when compared to using non-space sensing technologies. Productivity gains associated with remote sensing have been documented in the agricultural sector. Asadi, Vuppala and Reddy (2007) studied a project implemented by the Indian Ministry of Rural Development involving the use of remote sensing technology in mapping out groundwater in ten states. The project reported a success rate of bore holes and was estimated to be 90 percent; as a result, the project was expanded to cover the whole of India. 

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Impact of the Remote Sensing Industry on Russia’s Relationship with Other Countries

The high costs associated with the development of remote sensing capabilities poses the need for international collaboration among various emerging space powers (Peter & Stoffl 2009). According to Ehrenfreund & Peter (2009); Logsdon (2008); Schaffer (2008), the remote sensing sector requires international collaboration. For example, Ehrenfreund and Peter (2009) describe the case of the United States collaborating with other 76 nations together with global organisations for remote sensing activities that focused mainly on weather. Smaller countries acknowledged the value of this partnership and utilized the collaboration to their advantage. Ehrenfreund and Peter (2009) profiled such countries and noted that they are mainly emerging space powers lacking a substantial share of the global remote sensing market. Moreover, Peter and Stoffl (2009) reported that these countries are incapable of bearing the costs of implementing full-fledged Earth observation programs regardless of its economic value.

Another case of international collaboration described by Zhao (2005) is that between China and Brazil, dubbed the CBERS program, which was established in the late 1980s when both countries were considering the possibility of implementing national remote sensing systems. In 2014, the CEBRS sent a satellite to space to help in monitoring agriculture, forestry, and land (Zhao 2005). There is no agreement concerning the motives of the program. According to Zhao (2005), this program was aimed to increase the influence of China in the Latin America. For others, this program is a joint effort that had the objective of accomplishing a tack jointly that could not be achieved by either of the parties alone (Qiao et al. 2009; Haibin 2010). Regardless of the motives, there is no doubt that the program is successful in Earth observation activities, and has the capability of improving the domestic remote sensing sectors in the countries (Zhao 2005). 

Russia has also adopted a similar approach of international collaboration in order to develop its remote sensing sector (Moore 2014). In particular, Russia collaborates with Iran to jointly develop an Earth observation system for Iran. Such collaboration is part of a larger strategy by Russia to widen cooperation areas with Iran besides industry, trade and economy (Moore 2014). In addition, in 2014, Russia entered into an agreement with China for a joint development of remote sensing satellites in space, which are primarily used for civilian and scientific monitoring services as well as military purposes (Payson & Davidian 2015). Moreover, Russia has signed partnership agreements with Germany to work jointly on remote sensing and space robotics with the aim of increasing the number of its remote sensing satellites in space to 20 as 2025 from the current seven. Russia also cooperates with India in joint remote sensing; this partnership has the aim of offering cheap remote sensing services in order to increase Russia’s competitive position in the global remote sensing industry (Payson & Davidian 2015). Apart from collaboration, Russia has allowed other countries to use Russian-built remote sensing satellites. These countries include Belarus, Egypt and South Africa. Therefore, it is evident that Russia relies on international collaboration to develop its remote sensing sector.

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Current and Future of the Remote Sensing Industry in Russia

The commercialisation of remote sensing in Russia commenced during the early 1990s. At the time, Russia embarked on the sale of imagery captured by its military satellite (Payson & Davidian 2015). Nonetheless, with the European and American private enterprises into the remote sensing sector, Russia has not been able to keep pace with this growth with respect to market integration and enhancing technological capabilities as is the case with major commercial players in the sector (Makarov & Payson 2009). The dismal performance of the Russia’s remote sensing sector can be attributed to a number of factors including barriers to operate in the private sector; lack of the needed skills (Frolov 2011); lack of government support (Frolov & Ganichev 2014); and lack of local demand for Earth observation services (Makarov & Payson 2009).

The economic projections for the remote sensing industry show the continued growth of the sector. The remote sensing sector is considered the most promising growth area. Regardless of the budget deficit and fiscal restraint measures, Euroconsult (2011) projects that governments will continue to drive the remote sensing sector through the next decade. The increasing demand for imagery data will also fuel the growth of the sector. According to Euroconsult (2011), the ongoing expansion in remote sensing missions will affect the entire value chain of the sector, ranging from the manufacturing segment of the industry to the supply of data for the ever increasing end-users. Moreover, geographical expansion is poised to play a significant role in the future growth with the emergence of new government initiatives coupled with the proliferation of commercial data distribution networks globally (Peter & Stoffl 2009). In addition, it is projected that governments will make up a significant fraction of the customer base for remote sensing services, which can be attributed to increasing defence requirements (Euroconsult 2011). Nevertheless, a diversification of the client base has been projected, especially from the private sector in the oil and gas sector. Competition is expected to increase due to the proliferation of both government and private enterprises into the remote sensing sector (Euroconsult 2011). Another future trend is the sustained increase of government funding into the remote sensing sector, particularly in defence, monitoring of natural resources, and environmental monitoring.

The literature review reveals crucial insights regarding the state of the Russian remote sensing sector. The first significant finding is that Russia is a small player in the global remote sensing sector in terms of market share. Although there are no specific studies exploring the economic impact of remote sensing for Russia, descriptive case studies can be used to understand the likely effects the industry has on the economy of the country. These effects include contribution to GDP and productivity. However, it is essential to acknowledge the complexity associated with modelling the economic impact of this sector. It is also clear from the literature review that the remote sensing sector fosters international collaboration between Russia and other countries, especially Iran, China, and India. The strength of the studies in the literature review is that they have performed detailed case studies; however, they have failed to quantify the effects of the remote sensing industry on Russia’s economy and foreign relations. What is less clear is the specific effects of remote sensing on the Russian economy. There are no studies that have been conducted to investigate how remote sensing affects various sectors of the Russian economy, which poses the need for conducting a detailed descriptive case study on the effects of sector on Russia’s economy.

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