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Realizing the Potential of Remote Sensing

Over the past decade, a renewed and expanding interest in practical applications of Earth observations from space and airborne platforms has coincided with and been fueled by changes in the data, in how they can be used, and in who produces them. There have been significant improvements in the availability of remote sensing data and in their spectral and spatial resolution. In addition, the data can be adapted for more varied uses because of the extension and advancement of complementary spatial data technologies, such as geographic information systems and the Global Positioning System, which can be used in conjunction with remote sensing data. During the same period, the institutional support for producing remote sensing data has also become more diversified. In the United States, satellite remote sensing was until recently dominated by federal agencies and their private sector contractors and was focused on reconnaissance, scientific and technological innovation, and operational weather monitoring and prediction. Although the private sector has long been actively involved in providing airborne images for a variety of applied needs, commercial companies have only recently begun to provide satellite remote sensing imagery. Increasingly, private sector firms are playing a more central role, even a leadership role, in providing satellite remote sensing data, either through public-private partnerships or through the establishment of commercial entities that serve both government and private sector Earth observation needs. Public sector organizations and private firms also provide technology for instrumentation flown on airborne platforms that enable the development of additional products and services. In addition, many private sector value-adding firms have been established to work with end users of the data.



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Transforming Remote Sensing Data into Information and Applications 1 Realizing the Potential of Remote Sensing Over the past decade, a renewed and expanding interest in practical applications of Earth observations from space and airborne platforms has coincided with and been fueled by changes in the data, in how they can be used, and in who produces them. There have been significant improvements in the availability of remote sensing data and in their spectral and spatial resolution. In addition, the data can be adapted for more varied uses because of the extension and advancement of complementary spatial data technologies, such as geographic information systems and the Global Positioning System, which can be used in conjunction with remote sensing data. During the same period, the institutional support for producing remote sensing data has also become more diversified. In the United States, satellite remote sensing was until recently dominated by federal agencies and their private sector contractors and was focused on reconnaissance, scientific and technological innovation, and operational weather monitoring and prediction. Although the private sector has long been actively involved in providing airborne images for a variety of applied needs, commercial companies have only recently begun to provide satellite remote sensing imagery. Increasingly, private sector firms are playing a more central role, even a leadership role, in providing satellite remote sensing data, either through public-private partnerships or through the establishment of commercial entities that serve both government and private sector Earth observation needs. Public sector organizations and private firms also provide technology for instrumentation flown on airborne platforms that enable the development of additional products and services. In addition, many private sector value-adding firms have been established to work with end users of the data.

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Transforming Remote Sensing Data into Information and Applications These changes, some technological, some institutional, and some financial, have implications for new and continuing uses of remote sensing data. Recognizing the importance of these changes and their significance for a variety of issues related to the use of remote sensing data, the Space Studies Board established the Steering Committee on Space Applications and Commercialization to hold a series of three workshops to explore three sets of related issues.1 Based on the first workshop, titled “Moving Remote Sensing From Research to Applications: Case Studies of the Knowledge Transfer Process” and held in May 2000, this report focuses on the process of technology and knowledge transfer in transforming remote sensing data into applications. BACKGROUND Remote sensing has long been recognized as a means of obtaining data and information to meet perceived needs. Systematic remote sensing began in the period between World Wars I and II with aerial photography used for military reconnaissance and photogrammetry. The Cold War emphasis on collecting intelligence to monitor the U.S.-Soviet arms race stimulated the rapid technological advancement of satellite remote sensing capabilities for military applications. During the same period progress was made in the development of remote sensing technologies applicable to civilian needs: Box 1.1 lists milestones over the past four decades.2 TIROS 1, the first meteorological satellite, was launched in 1960, and the Earth Resources Technology Satellite series, later renamed Landsat, began operating in 1972. With Landsat came a continuous source of satellite images that could be used routinely for a variety of civilian applications such as mineral and oil exploration, crop monitoring, and natural resource management. Early programs such as the Large Area Crop Inventory Experiment, a program to forecast the yield of specific crops, called attention to the possibilities for developing a variety of useful applications of remote sensing data, although the effort never achieved the ambitious goals set by its proponents.3 By the 1980s, as a result of budgetary problems and a declining interest in 1   The second workshop will address the conduct of scientific research in the new and evolving remote sensing environment, and the third will focus on public sector applications of remote sensing data. 2   Although the military sector has a long history of collecting remotely sensed data and transforming it into information for military uses, this report focuses on the development of civilian applications. Both in the allocation of budgetary resources and in the use of the technology, military developments evolved separately from civil remote sensing, and defense and military systems were designed to prevent access to the data rather than to encourage their widespread use. 3   Pamela E.Mack, Viewing the Earth: The Social Construction of the Landsat Satellite System. Cambridge, Mass.: MIT Press, 1990, pp. 146–158.

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Transforming Remote Sensing Data into Information and Applications civilian applications at NASA, which had taken the technical lead in civilian Earth observation, responsibility for civil operational sensors and remote sensing satellites had been transferred to the National Oceanic and Atmospheric Administration (NOAA).4 NASA concentrated its energies on developing sensors for gathering scientific data,5 and resources for Earth observation were directed increasingly to instruments intended primarily to meet scientific and environmental data needs. In the late 1980s, the agency committed itself to building the Earth Observing System (EOS), an environmental satellite system that was defined in terms of both NASA and interagency environmental observation needs. As NASA was realigning its activities to meet scientific and policy data needs, interest in the role of the private sector in Earth observation was growing. The French SPOT system (Système pour l’Observation de la Terre) was created through a public-private partnership with the specific goal of selling data and developing a self-sustaining commercial enterprise.6 SPOT Image was organized to operate the system and sell data; the French government provided support for the spacecraft system. During the same period, the U.S. government experimented with commercialization of the Landsat system, awarding a contract to the Earth Observation Satellite Company (EOSAT) in 1985 to operate the Landsat system and sell the data on the commercial market.7 This experiment, however, did not meet expectations.8 NASA moved back into the arena of remote sensing applications with the establishment of the Earth Observations Commercialization/Applications Program (EOCAP) in 1993 and a university-government-industry collaborative pro- 4   Presidential Directive 54 (PD 54) of November 1979 assigned NOAA responsibility for all civil land remote sensing satellite systems. 5   Office of Technology Assessment, U.S. Congress, The Future of Remote Sensing from Space: Civilian Satellite Systems and Applications, Washington, D.C., Government Printing Office, 1993, p. 49; Space Studies Board, National Research Council, Earth Observations from Space: History, Promise, and Reality, Washington, D.C., National Academy Press, 1995, p. 113. 6   Office of Technology Assessment, U.S. Congress, The Future of Remote Sensing from Space: Civilian Satellite Systems and Applications, Washington, D.C., Government Printing Office, 1993, p. 53. 7   Space Studies Board, National Research Council, Earth Observations from Space: History, Promise, and Reality, Washington, D.C., National Academy Press, 1995, p. 114; Office of Technology Assessment, U.S. Congress, The Future of Remote Sensing from Space: Civilian Satellite Systems and Applications, Washington, D.C., Government Printing Office, 1993, p. 49. 8   Prices increased significantly during the period of transition from a government to a private operator. The higher prices resulted in lower sales, and consequently the use of the data and the development of applications decreased. Landsat 6, which was to have been operated by EOSAT, failed to reach orbit, further curtailing EOSAT’s ability to seek a profit from Landsat data on the commercial market. The U.S. government did not obtain a commercial operator for Landsat 7 and transferred the program back to government control.

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Transforming Remote Sensing Data into Information and Applications BOX 1.1 Milestones in Civil Satellite Remote Sensing 1960 The first meteorological satellite, TIROS 1, takes first images to be used in weather forecasts. 1960 CORONA, a reconnaissance satellite, takes its first image. CORONA imagery was declassified in 1995. 1968 Apollo 8 returns the first pictures of Earth from deep space. 1972 NASA launches the first civilian Earth resource satellite, Earth Resources Technology Satellite (later named Landsat 1). 1975 The Large Area Crop Inventory Experiment becomes the first Landsat applications program. 1975 NASA launches Landsat 2 and 3. 1979 NOAA assumes control of the Landsat program from NASA pursuant to executive order. 1982 NASA launches Landsat 4. 1983 NOAA transfers the nation’s civil, operational remote sensing satellites to the private sector. 1984 Land Remote Sensing Commercialization Act establishes the process for the commercialization of land remote sensing satellites. 1985 NASA launches Landsat 5. 1985 NOAA transfers the Landsat program to the Earth Observation Satellite Company (EOSAT), a private operator. 1985 Nimbus-7 Total Ozone Mapper confirms ozone depletion. 1986 France launches the first commercially oriented Earth observation satellite, SPOT 1. 1986 The media uses Landsat 5 data to monitor the Chernobyl nuclear power plant disaster, marking the first widespread use of satellite imagery in the news media.

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Transforming Remote Sensing Data into Information and Applications 1991 NASA establishes the Earth Observing System (EOS) program in response to a U.S. Presidential initiative to provide in-depth scientific understanding about the functioning of the Earth as a system. 1991 Landsat 5 monitors burning oil wells and other environmental effects of the Gulf War. 1992 Land Remote Sensing Policy Act of 1992 transfers the Landsat program back to the government and provides for the continuation of the program with Landsat 7. 1993 Department of Commerce issues the first license to operate a private remote sensing system to EarthWatch for the Early Bird satellite. 1993 EOSAT’s launch of Landsat 6 fails. 1995 U.S. delegate to the United Nations shows satellite images of mass graves in Bosnia to the UN Security Council. 1995 Russian firm, Sovinformsputnik, sells 2-m imagery. 1995 Canada launches the first operational synthetic aperture radar satellite, Radarsat 1. 1996 NASA creates lead center for commercial remote sensing applications development. 1997 Congress and the Office of Management and Budget direct NASA to acquire Earth science data products from commercial sources. 1998 NASA’s Office of Earth Science creates the Applications Division. 1998 Department of Defense awards its first contract to procure high-resolution satellite images gathered by privately owned satellites. 1999 NASA launches Landsat 7. 1999 Space Imaging, Inc. launches the first commercial 1-m resolution satellite, IKONOS 2. 1999 NASA launches the first Earth Observing System (EOS) satellite, Terra. 2000 Department of Commerce issues first licenses to operate remote sensing systems to collect 0.5-m imagery.

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Transforming Remote Sensing Data into Information and Applications gram of affiliated research centers around the same time.9 NASA’s Stennis Space Center was given responsibility for developing commercial remote sensing applications and administering NASA’s Science Data Buy, a demonstration program encouraging NASA to purchase scientific research data from the private sector. Through EOCAP, NASA established partnerships with private companies and business alliances seeking to develop and market remote sensing applications products. According to NASA, its role is to share in the financial risks and provide technical guidance to industry during the development, validation, and dissemination of prototypes for commercially viable applications. The affiliated research centers program funds university efforts to develop and test new uses of remote sensing data and data analysis tools in partnership with both small and large private sector companies. Regardless of their outcome, NASA’s programs to encourage the development of viable commercial uses of remote sensing data exemplify the changes under way in the existing relationships among federal science agencies, the private sector in the form of the commercial remote sensing industry, and both scientific and applied users of remote sensing data. In 1998, NASA established the Applications Division to foster and expand the uses of Earth Science Enterprise (ESE) products in the public and private sectors. The formation of the Applications Division, parallel in structure to the ESE Research Division, signaled the significance accorded to remote sensing applications within NASA. Today scientific and operational remote sensing images produced by U.S. government agencies, aerial and high-resolution satellite images from the private sector, and remote sensing images from international sources contribute to the growing abundance of Earth observation data. In 1999 alone, there were three major launches of civil Earth observation satellites: Landsat 7, IKONOS, and Terra, one of which (IKONOS) was launched by a private sector firm, Space Imaging, Inc. Moreover, the expected launches of new satellites over the next several years with capabilities for gathering data of even higher spatial and spectral resolution in both the public and private sectors will add to the rich array of possibilities for additional applications. (One forecast projects some 15 commercial land imaging satellites to be launched during the period from 2001 to 2006.10) In addition to more data suppliers, there is now a more diverse infrastructure for producing applications, including a growing number of value-adding producers, university centers, and consultants. Advances in computing capabilities and the development and availability of geographic information technologies have given added impetus to the use of remote sensing data in new types of 9   For more information on affiliated research centers see <http://www.crsp.ssc.nasa.gov/scripts/arc/>, accessed on March 2, 2001. 10   Stoney, William E., “Summary of Land Imaging Satellites (with Better Than 30 Meters Resolution) Planned to Be Operational by 2006,” McLean, Va., Mitretek Systems, March 20, 2001.

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Transforming Remote Sensing Data into Information and Applications applications. Socioeconomic, epidemiological, and ecosystem databases can be integrated with remote sensing data in a geographic information system to improve understanding of complex spatial and environmental relationships. The Internet, in particular, the World Wide Web, provides a means for scientists and applications users to identify existing remote sensing data and imagery and to obtain them rapidly. The intersection of these various technological advances offers the potential for a new period in the application of remote sensing to public policy, governance, and commercial needs. For example, the use of remotely sensed imagery in the media made such events as the Chernobyl disaster, oil wells set afire during the Persian Gulf War, and atrocities in Bosnia and Kosovo visible to the general public in ways that were previously not possible.11 TURNING REMOTE SENSING DATA INTO INFORMATION Space-based remote sensing provides a new source of information that cannot be easily obtained in other ways and that promises both economic and social benefits. To fulfill this promise will require a better understanding of cost-effective ways to realize potential useful applications. Workshop discussions involving remote sensing applications users made it clear that the utility of the technology will come not from the data itself but rather from the information that can be derived from the data. These users emphasized that turning data into useful information is central to technology transfer and the development of successful applications. Workshop discussions suggested that to date new applications of remote sensing data have been developed largely by individuals or organizations that already possessed both the necessary technical expertise and an understanding of potential uses of the data. Participants pointed out that remote sensing data can initially appear complicated and possibly even irrelevant to potential end users who make policy and management decisions. Such users need easily understood information that can be used to address economic, social, environmental, and other policy questions. For this reason, research to enable interpretation of the data, and transformation of remote sensing data into usable information, are critical steps in the development of applications. To enjoy widespread use, remote sensing data must be made accessible to information consumers who may not have the technical expertise currently required to use such data. Past approaches to applications development have 11   There has also been a long history of civilian applications of classified imagery. For example, MEDEA, an environmental scientific advisory group, has shown the advantages of using intelligence data and imagery for civil environmental applications. See Pace, Scott, O’Connell, Kevin M., and Lachman, Beth E., Using Intelligence Data for Environmental Needs: Balancing National Interests, Santa Monica, Calif., RAND, 1997.

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Transforming Remote Sensing Data into Information and Applications BOX 1.2 Limitations of Common Approaches to Applications Development Models that motivated many of the previous government programs to develop successful applications of remote sensing may have inhibited their success. Despite government investment in demonstration programs, subsidies to data producers and data users, and applications partnerships between and within the public and private sectors aimed at developing economically viable applications of remote sensing, the full potential of the technology for routine or operational applications has not yet been realized. In particular, these previous models for applications development do not address several of the challenges noted in the workshop: (1) the knowledge and communications gap between technical experts and information consumers, (2) the lack of incentives for many end users to adopt remote sensing applications, and (3) the need for applications users to anticipate and meet the full spectrum of costs associated with the development and use of remote sensing applications. Demonstration research programs are often premised on the belief that successful applications in both the public and private sectors will emerge from research projects that have demonstrated new uses of remote sensing data. The federal role in this approach has been to identify areas of need or promise and to provide financial support for university-led research projects in these areas. However, another necessary step, moving from research results to operational demonstrations of utility that will persuade nontechnical end users to adopt remote sensing applications, is often not taken. This is the need addressed, for example, by the county extension agent (now known as a county extension educator) in agricultural technology transfer. A key component of the success of this process is the “spannable social distance” between the county agent and his clients and, as a result, the ability of the county agent to understand and speak directly to farmers’ needs and priorities.1 The county agent will meet with both farmers and seed industry representatives to determine the best way to present the leading hybrid varieties to other farmers. A demonstration plot of all varieties sold in the county will usually be planted along a well-traveled roadway so that other farmers can observe them throughout the growing season. Yield data are obtained and summary tables of this information are provided at the end of the growing season so that farmers can use this information in selecting seed for the following year. Subsidies are used in two ways. One, as illustrated by NASA’s Earth Observa- stopped short of realizing remote sensing’s full potential (Box 1.2). The demand for applications will be driven by requirements for information rather than by the technical capabilities of the end users. Unlike those who developed the first applications of remote sensing, many new applications users are likely to have little, if any, knowledge of remote sensing technology or how it is employed to derive information. They will be concerned instead with the accuracy and timeliness of the data and with its relevance for specific tasks and decisions. Potential users of remote sensing information want to be assured that its

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Transforming Remote Sensing Data into Information and Applications tions Commercialization/Applications Program (EOCAP), involves providing an incentive to the private sector to invest in remote sensing applications by creating a partnership in which the government serves as a financial partner. EOCAP projects have involved applications for agriculture, geology, urban land use, real estate management, and telecommunications. A second approach involves subsidizing the use of data for applications, perhaps by providing data at no cost through government data programs or through such vehicles as the experimental science data buy program that gives scientists access to free commercial data through a competitive proposal process.2 To the extent that scientific research leads to specific applications, workshop discussions suggested, the direct subsidization of scientific data acquisition through the public and private sectors may promote applications. However, this approach is not oriented to bridging the gap between data and information. More specifically, it does not address the issue of end user information needs. Finally, a partnership approach has been employed in the development of SPOT in France and Radarsat in Canada. The central government serves as the financial partner of a private sector firm in supporting the construction, launch, and operation of remote sensing satellites for both scientific and applied uses. The European Space Agency’s decision to have ERS-1 and Envisat synthetic aperture radar data distributed on a commercial basis is another example of the public-private partnership approach.3 In this case, governments subsidize the production of data but have not become involved in the process of converting data to information, and have not attempted to address the full range of applications costs (see Chapter 4) that were discussed in the workshop. Each of these three approaches emphasizes the role of government financial support in the development of new applications, but none addresses user needs or the institutional, workforce, legal, and other nontechnical issues that arise in the successful development of applications. 1   Although the county agent and the farmer share a common language, education, and background, the county agent has more education and training, is knowledgeable about research, and serves as a link between the farmer and the knowledge base in state universities and federal agencies. 2   The science data buy and its implications for Earth science research will be explored in some detail in a subsequent report by the steering committee. 3   See “ESA Hands Radar Satellite Responsibility to Industry,” Space News, Vol. 11, No. 11, October 30, 2000, pp. 1, 34. value will surpass the institutional investments involved in acquiring and using the information. In a commercial market, there must be a balance between the value of the information, as perceived by end users, and the revenue necessary to support the information delivery system. In the public sector, the value of the information must be weighed against alternative uses of the funds needed to support the work of transforming data into information. Achieving the needed balance depends on both the intrinsic information content of the raw data pro-

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Transforming Remote Sensing Data into Information and Applications duced by a remote sensing instrument and the way the data are processed to produce new information. In the case studies examined at the workshop, it was clear that a critical element in producing information of value is processing, which involves two steps: preprocessing and the conversion of data to information. Preprocessing turns raw data into accurately calibrated measures of precisely located physical variables such as reflectance, emittance, temperature, and backscatter. The knowledge base underlying this step is usually well developed, although research may be required for developing specific applications (as in the case, for example, of developing algorithms for using SeaWiFS data to monitor Gymnodinium breve, a species associated with harmful “red tides”; see Chapter 2, Box 2.2). However, the scientific knowledge base to support the conversion of data to information is far less developed. Transforming technical data into a form that is meaningful to nontechnical users-a process often including either the integration of remote sensing data with other types of data or scientific research to characterize the data (or both)-is highly dependent on the information requirements of applied users and on the skills of technical experts. For example, a digital elevation model that was extracted from remotely sensed light detection and ranging (lidar) data provided increased accuracy over conventional digital elevation models and thus proved valuable in helping to determine optimum routes for new Norfolk and Southern railroad lines.12 In another example, a private sector firm transformed satellite imagery into maps tailored for the specific needs of commercial and sports fishermen, showing where albacore rather than swordfish were likely to be present. The diversity of end users’ information needs that might be met by the same initial set of physical variables is depicted in Figure 1.1, which illustrates several simultaneous data-to-information conversion processes. BRIDGING THE KNOWLEDGE GAP Data must be transformed to information and knowledge if the goal of developing successful operational applications of remote sensing data is to be met.13 On one side of the gap are the scientists, engineers, and technologists who construct and operate instruments to measure parameters in the Earth system using spacecraft and aircraft. On the other side are actual and potential end users (the 12   Cowen, D.C., Jensen, J.R., Hendrix, C., Hodgson, M.E., and S.R.Schill, “A GIS-Assisted Rail Construction Econometric Model That Incorporates LIDAR Data,” Photogrammetric Engineering and Remote Sensing 66(11):1323–1328, 2000. 13   Such a transformation of data to information was demonstrated in the case studies presented at the workshop (see Chapter 2).

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Transforming Remote Sensing Data into Information and Applications FIGURE: 1.1 Processing data into information.

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Transforming Remote Sensing Data into Information and Applications information consumers) who have information requirements but know little about using remote sensing technology to satisfy them and, critically, have little if any financial, personal, or institutional motivation to consider such an approach.14 The presence within an organization of a highly motivated person or “champion” who can get an organization to recognize the potential benefits of using remote sensing data and applications can be critical to overcoming gaps in communication. Nevertheless, those who develop sensors, collect and analyze data, and develop products to address scientific or technical questions often have few opportunities to communicate with prospective users who lack essential technical expertise. This lack of communication constitutes a significant barrier to technology transfer. Bridging the knowledge gap will depend not only on improved communication among technologists and users (see Box 1.3), but also on research focused on converting data into information. A key barrier to transforming data and images into meaningful information is the limited understanding of how to convert measurements made from space into information of ecological, economic, social, infrastructure, environmental, or administrative value. As workshop presentations pointed out, improving this knowledge base requires the involvement of those who are knowledgeable about the physics of remote sensing and the technologies that support it. In addition, both social and natural scientists could provide and integrate complementary data for use in the transformation of raw remote sensing data into usable information, and researchers could also refine or extend the utility of an existing remote sensing application. However, the current model of conducting scientific research and publishing the results in peer-reviewed journals that emphasize original new work can discourage the pursuit of research on applications, given that many scientific disciplines and universities often judge the merit of a researcher or a project by publication alone. Moreover, funding organizations generally issue grants for original research rather than work on applications, creating another disincentive to turning research into applications. In workshop discussions, participants suggested the need for an alternative to peer-reviewed publication as the end product of basic research. In some fields, such as pharmacology and engineering, the end product of a research project is often an application. Mechanisms such as grants and NASA Research Announcements that encourage the development of applications research would benefit the 14   For example, in one case study discussed in the workshop, sanitation authorities resisted using remote sensing to improve their capabilities for monitoring coastal sewage discharge, possibly because of the potential for positive signals to complicate existing monitoring and compliance issues (see Chapter 2, Box 2.3). Other case studies and examples discussed in the workshop and planning meeting highlighted the importance of creating incentives for end users to adopt remote sensing applications.

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Transforming Remote Sensing Data into Information and Applications practical use of Earth science data. In addition, some new journals are publishing peer-reviewed research focusing on scientific research and its use in decision making and applications.15 But there is little support for research to explore the linkages between basic research and applied remote sensing and the opportunities those linkages offer for developing new applications. An exception is land grant colleges and universities, which encourage the practical application of research to local or state issues. MOVING FROM RESEARCH TO APPLICATIONS Today, new mechanisms are needed for transferring the results of federally funded research to applications that will benefit operations within and beyond federal agencies. Technology transfer, at the heart of which is the creation of useful knowledge and information, is a critical element in the development of new applications of remote sensing data that is not always well understood. Rather than being confined to cost considerations that tend to focus on the initial expense of acquiring imagery, and to privatization that involves the transfer or licensing of technology to private firms, the process of remote sensing technology and knowledge transfer is better discussed, as the steering committee learned, in a broader context that includes policy and institutional issues, new users’ requirements, education and training, and technical issues. Applications of remote sensing data and images for public, private, and not-for-profit uses, produced by public or private sector providers, may be developed from data originating in either the public or the private sector. Similarly, technology transfer can take place within or across government agencies, between the public and the private sectors, within the private sector, and between the private or government sectors and the not-for-profit sector. At issue is not where the data originate or who uses them, but rather how to develop useful, operational applications. Despite the growing number of users who have taken advantage of the opportunities to apply remote sensing data to practical problems-in, for example, coastal management, monitoring environmental change, mapping, natural resource management, and public health-an even larger set of users could potentially benefit from the data. As became evident in the workshop, however, extending the benefits of remote sensing to potential new users is a complex process of technology and knowledge transfer that goes far beyond the initial task of creating market-based incentives to purchase data. Remote sensing special- 15   See Ecological Applications, available online at <http://esapubs.org/esapubs/journals/applications_main.htm> accessed October 10, 2001.

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Transforming Remote Sensing Data into Information and Applications BOX 1.3 Technology and Knowledge Transfer The process of converting data into information is a form of technology and knowledge transfer. There has been a wealth of research on technology transfer over the past several decades, as well as a growing body of experience in technology transfer and research utilization programs,1 only a small slice of which was presented at the workshop. This research indicates an emerging consensus not only about what technology transfer is, but also about what it is not. It is not generally thought to be a unidirectional, linear process that begins with basic research discoveries, which are then moved into applied research and development, and finally ends with the production and dissemination of usable applications. Nor is it a simple process of disseminating advanced technological resources to potential users. Instead, as both ongoing research and the case studies presented at the workshop make clear, the process of technology transfer is interactive and can begin at any point-with a market or user need, with applied research, with a technology or technological product, or with basic research. What is critical to this process is what David Roessner2 calls a “spannable social distance” across each interface of components in the system.3 By this he means that the cultural and communicative distance between producers and users of a new technology must be small. Roessner’s emphasis on spannable social distance is based on his examination of the experience of the federal government in technology transfer and research utilization programs in the 1960s and 1970s.4 He concluded that both passive and reactive technology transfer mechanisms and programs were generally less effective than those that were active or required collaboration among producers and end users from the start.5 Moreover, although technology transfer was more likely to be successful when applications were developed by users with substantial technical capabilities, it also required strong, ongoing personal interactions between the suppliers of the technology and the new users of that technology. Bridging the gap illustrated in Figure 1.1 will require considerable interaction between technical experts and information consumers to convert data into information of value to the end user. This interaction may also require intermediaries that are close to the cultures of both the user and the technical expert. ists, for example, must obtain a fundamental understanding of the fit between remote sensing data and the needs of potential users. To do so may require overcoming such nontechnical barriers and bottlenecks as the lack of understanding by end users of the potential of the technology, the absence of a trained inhouse technical workforce, or restrictions on the use of data or software that can effectively slow down or impede the adoption of new applications. The lack of communication among remote sensing specialists, data users, and potential infor-

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Transforming Remote Sensing Data into Information and Applications 1   One recent study on the technology transfer process is Ruttan, Vernon W., Technology, Growth, and Development: An Induced Innovative Perspective, New York, Oxford University Press, 2001. For additional reading on the technology and knowledge transfer process see: David, Paul A., “Technology Diffusion, Public Policy, and Industrial Competitiveness” in Ralph Landau and Nathan Rosenberg, eds., The Positive Sum Strategy: Harnessing Technology for Economic Growth, Washington, D.C., National Academy Press, 1986; Cowan, Robin, David, Paul A., and Foray, Dominique, “The Explicit Economics of Knowledge Codification and Tacitness,” Industrial and Corporate Change: Special Issue, Vol. 9, Issue 2, June 1, 2000; David, Paul A., “Rethinking Technology Transfers: Incentives, Institutions and Knowledge-based Industrial Development,” in Charles Feinstein and Christopher Howe, eds., Chinese Technology Transfer in the 1900s: Current Experience, Historical Problems, and International Perspectives, Cheltenham, England, Edward Elgar, 1997; David, Paul A., and Dominique Foray, “Information Distribution and the Growth of Economically Valuable Knowledge: A Rationale for Technological Infrastructure Policies” in Morris Teubal, Dominique Foray, Moshe Justman, and Ehud Zuscovitch, eds., Technological Infrastructure Policy: An International Perspective, Dordrecht, Kluwer Academic Publishers, 1996. 2   J.David Roessner, a professor of public policy at Georgia Institute of Technology, spoke on the topic “Technology Transfer Process” at the May 2000 workshop on which this report is based. 3   For the original research on spannable social distance, see Rogers, Everette M., Eveland, J.D., and Bean, Alden S., Extending the Agricultural Extension Model, Institute for Communication Research, Stanford University, 1976. 4   Roessner, J.David. “Evaluating Government Innovation Programs: Lessons from the U.S. Experience,” Research Policy 18:343–359, 1989. 5   See Ballard, Steven, James, Thomas E., Adams, Timothy I., Devine, Michael D., Malysa, Lani L., and Meo, Mark, Innovation Through Technical and Scientific Information: Government and Industry Cooperation, Westport, Conn., Quorum Books, 1989; Doctors, S.I., The Role of Federal Agencies in Technology Transfer, Cambridge, Mass., MIT Press, 1969; Gruber, W.H., and Marquis, D.G., Factors in the Transfer of Technology, MIT Press, 1969; Havelock, R.G., Planning for Innovation, Ann Arbor, Mich., Center for Research on the Utilization of Scientific Knowledge, 1969; Hough, Granville, Technology Diffusion, Federal Programs and Procedures, Mt. Airy, Md., Lomond Books, 1975; and Rogers, Everette M., and Shoemaker, Floyd, Communication of Innovations, 2nd Edition, New York, Free Press, 1971. mation consumers is one of the greatest barriers to expanding the use of remote sensing data. Drawing on workshop discussions and material presented in the workshop’s case studies, the steering committee examined these barriers and bottlenecks and developed suggestions for ways to deal with them, taking as a starting point the requirements of end users in the coastal zone for successful operational applications. To that end, the steering committee collaborated with the NRC’s Ocean

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Transforming Remote Sensing Data into Information and Applications Studies Board, which provided a foundation of research and access to scientific expertise for developing the workshop and the report. The use of remote sensing in the coastal zone has been discussed in a number of Ocean Studies Board and other NRC reports.16 In identifying barriers and bottlenecks as well as successful approaches to overcoming them, the steering committee’s goal in this report is to advance the dialogue about how to succeed in the development of remote sensing applications. 16   As early as 1992, the Ocean Studies Board called for greater use of remote sensing data in ocean and coastal research and policy and called for new partnerships with both federal remote sensing data providers and industry data providers to accomplish this effort. Recommendations regarding the application of remote sensing data in NRC reports go beyond scientific need, however, and extend into policy, monitoring, and other operational responsibilities in the coastal zone. See: Ocean Studies Board, National Research Council, Oceanography in the Next Decade: Building New Partnerships, Washington, D.C., National Academy Press, 1992, p. 151. In addition, other National Research Council reports have called attention to the importance of remote sensing to coastal and ocean research and policy. See: Clean Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution (Ocean Studies Board, 2000); Review of NASA’s Earth Science Enterprise Research Strategy for 2000–2010 (Space Studies Board, Board on Atmospheric Sciences and Climate, Board on Earth Sciences and Resources, and Ocean Studies Board, 2000); Global Environmental Change: Research Pathways for the Next Decade (Board on Sustainable Development, 1999); From Monsoons to Microbes: Understanding the Ocean’s Role in Human Health (Ocean Studies Board, 1999); Global Ocean Science: Toward an Integrated Approach (Ocean Studies Board, 1999); and Restoring and Protecting Marine Habitat: The Role of Engineering and Technology (Marine Board, 1994), all published by National Academy Press, Washington, D.C.