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1 Introduction The growing interest in using remote sensing data and information in public sector management and decision making is being fed by the perceived utility of remote sensing data and information for a variety of state and local government purposes, by the increasing availability and usability of remote sensing-derived data in geographic information systems (GIS) and decision support systems, and by improvements in the spatial and spectral resolution of the data (see Box 1.1 for definitions of key terms). Since the early days of aerial photography in the 1930s and 1940s, local governments have been among the most active users of information obtained from remote sensing. State and local agencies have long depended on remote sensing technology for interpreting the aerial photographs they use to map and monitor changes in, for instance, land use, civil (nonmilitary) infrastructure, and transportation. The advent of civil satellite remote sensing raised expectations that state, county, and local governments would rapidly develop further applications of this new source of information, but those early expectations were not fulfilled. Although many state and local governments have used airborne remote sensing data to obtain information for both management and policy purposes, the use of satellite data in the nonfederal public sector is still limited. In some jurisdictions and for some purposes, airborne remote sensing continues to be preferred over the use of satellite data because of the former’s high spatial resolution and stereoscopic features. High-resolution images are necessary for many urban uses, and the resolution of the early civil satellite data was too low. By the end of the 1990s, however, new sources—federal and commercial—of high-resolution and multispectral remote sensing data from satellites led
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BOX 1.1 Definitions of Key Terms Understanding the advantages and potential uses of remote sensing begins with an understanding of key terms, some of which are defined here as they apply to the more common aspects of remote sensing. Hyperspectral data may be collected in hundreds of wavelengths and therefore offer the richest detail on the physical or biophysical properties of the objects being viewed. Light detection and ranging (lidar) measures the time it takes for a pulse of laser energy to travel round-trip from the laser source to a target and back to a sensor on the same satellite (or airplane) as the laser source. The pulse’s travel times are useful for measuring the elevation of a hard surface such as a building or the ground. Newer systems can collect data that distinguish reflections from multiple sources such as trees and the ground surface below them and can thus provide information on the structure of a forest. Multispectral data include information detected in several electromagnetic wavelengths and thus provide more detail on the observed objects, as opposed to black and white (or panchromatic) data, which do not provide any spectral information. Orthophotography refers to aerial photographs that are referenced to precise x, y coordinates on the ground. Referencing removes from the photographs the distortions caused by the terrain, Earth’s curvature, and camera angle. Orthophotography creates images that have the characteristics of a map: One can measure distances, areas, and angles accurately. These features make orthophotography useful for urban planning, environmental assessment, and other applications. Photogrammetry is the art, science, and technology of obtaining reliable information about physical objects and the environment through processes of recording, measuring, and interpreting photographic images, generally taken from an aircraft. Remote sensing is a means of obtaining data and images from sensors or cameras located at a distance rather than from direct human observation. Remote sensing data can be collected in several ways. Aerial images are obtained by photographing Earth’s surface from an airplane. Sensors on satellites generally provide digital rather than photographic images; they measure the electromagnetic radiation reflected or emitted from vegetation and terrain, which is then converted into the necessary information. Spatial resolution refers to the smallest feature discernable in an image. For example, a single picture element (pixel) in an image collected from the Landsat satellite measures 30 meters on a side, while some commercial satellites collect images that can distinguish features as small as 0.5 meter. While one could not distinguish an automobile using data with 30-meter resolution one could do so using data with 0.5-meter resolution.
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Spectral resolution refers to a sensor’s ability to collect data at specific electromagnetic wavelength ranges. Higher resolution provides more information about the physical characteristics of the object observed or more details about the biophysical properties of land cover and plants. Temporal resolution refers to the frequency with which a satellite revisits the same location. More frequent observations provide a better record of change, such as plants greening up in the spring, and increase the chance of observing a short-term event. For example, the Landsat 7 satellite has a temporal resolution of 16 days. many to conclude that state and local government would now become a significant, possibly the most significant, user of the data. Another type of remote sensing is ground-based and consists of sensors on Earth’s surface such as air-pollution sensors, ground-penetrating radar, and sonar, which are used to obtain information about Earth. Ground-based remote sensing is not, however, covered in this report, which explores the use of new as well as older types of satellite and airborne remote sensing data and information. This report explores how state, local, and regional governments apply remote sensing data and information applications, the problems they have met with in these applications, and how these problems are being addressed.1 The report is intended as both an introduction to remote sensing applications and a guide for managers and decision makers in state and local government who are responsible for supervising, establishing, managing, or budgeting for public sector data and information, including geospatial data operations. It is also intended for technically sophisticated geospatial professionals in state and local government who are interested in remote sensing applications and technology and for decision makers in the federal and commercial sectors who are engaged in the production, regulation, or dissemination of civil remote sensing data, to help them understand the opportunities offered by satellite remote sensing data in the nonfederal public sector as well as the constraints such data pose. The nonfederal public sector in the United States is a unique and often difficult setting in which to introduce new applications of satellite remote sensing data. Although potentially a large user market in the aggregate, it is highly decentralized, consisting of tens of thousands of independent and quasi-independent jurisdictions, each with complex budgetary, procurement, and decision- 1 Another NRC report, People and Pixels: Linking Remote Sensing and Social Science, Washington, D.C., National Academy Press, 1998, discusses the use of remote sensing data by social scientists, farmers, local governments, and urban and natural resource managers.
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making processes that influence the acquisition of remote sensing imagery. These public sector jurisdictions operate under significant budget constraints, and the budgets can change from year to year. Because managers in these jurisdictions are directly accountable to the voting public and their elected representatives and often must also meet the requirements of other levels of government, such as states and federal agencies, they operate in a complex political environment. Unlike the federal government, which uses remote sensing data and information for research, analysis, and public policy, state and local governments are engaged primarily in fulfilling highly specific operational responsibilities related to public sector management and governance. They obtain the data and information required for those responsibilities by traditional information-gathering procedures that may be legally constrained and labor-intensive. In such a setting, introducing new, high-technology data sources like satellite remote sensing can be difficult and expensive from technological, administrative, and budgetary perspectives. As a result, public sector managers may believe that adopting remote sensing data from satellites creates more problems than it solves. To assess the potential value of satellite remote sensing data to their operations, managers in state and local government need some understanding of technical distinctions and of the capabilities of remote sensing and its applications. They also need to understand the institutional and budgetary ramifications of adopting satellite remote sensing applications in a public sector setting. This report, which is based on information supplied in public sector case studies, attempts to meet the need for both types of information. At the same time, the steering committee recognizes that public sector decision makers who are not technical experts will and should turn to specialists for an assessment of technical issues. For this reason, and because the technology frequently changes, technical information in this report is kept to a minimum. Table 1.1 briefly lists types of remote sensing data that may be useful in state and local government operations. The steering committee hopes in this way to introduce nontechnical decision makers to the vocabulary of remote sensing and its capabilities. The focus of the report, however, is the utility of remote sensing applications and the institutional, budgetary, and policy issues that arise when remote sensing data and information are used to meet state and local government information needs. Many of the examples and case studies presented describe land remote sensing applications because of the broad relevance and importance of land data to state and local governments. The issues raised in the case studies are not specific to any single data type or application; moreover, specific uses of remote sensing data may introduce issues other than those discussed in this report. Although the emphasis is on civil remote sensing, the report recognizes that since September 11, the lines between civil and national security data in state and local government have blurred. This report grew out of the workshop “Facilitating Public Sector Uses of
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TABLE 1.1 Selected Types of Remote Sensing Data Data Type Attributes Availability Case Studies Supplying Examples High-resolution optical —High detail within small area —Useful for infrastructure, urban applications —Provides high-resolution views of objects at 1-2 m —Private U.S. and non-U.S. remote sensing companies —Private aerial photography firms —Baltimore, Md. —Richland County, S.C. —Washington State Multispectral optical, medium resolution —Shows multiple geophysical features —Allows for classification of vegetation, land use —Provides medium-resolution views of objects at 10-30 m —Beneficial for viewing large land areas —U.S. and non-U.S. government agencies and private firms —Baltimore, Md. —Portland (Ore.) Metro —Boulder County, Colo. —Missouri —Richland County, S.C. Hyperspectral —Provides maximum information on objects viewed —Allows for high-level classification, identification, and distinguishing of objects —U.S. and non-U.S. remote sensing companies —These data may be useful for identifying roofing materials and for enhanced accuracy of land classification in urban areas Lidar (light detection and ranging) —Provides detailed, bare-Earth elevation data and data on the height of vegetation and structures —Data collection unaffected by time of day or night, cloud cover —U.S. and non-U.S. private contractors and firms —Red River Valley, N.D./Minn. —North Carolina —Richland County, S.C. Radar —Data collection unaffected by clouds or time of day or night —Highly useful in studies of snow, ice —U.S. government (NASA) —Non-U.S. remote sensing companies and government agencies —Private aerial remote sensing firms
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Remote Sensing Data,” held in Boulder, Colorado, in January 2002. Organized by the Space Studies Board’s Steering Committee on Space Applications and Commercialization, the workshop brought together representatives of federal agencies and the nonfederal public sector, technical remote sensing experts, university scientists and applications specialists, and representatives of the commercial sector for 2 days of panels, discussions, and presentations. The focus of the workshop was the ways in which remote sensing has been and can be used in state and local government, the role of the federal government in fostering public sector uses of remote sensing, barriers and bottlenecks to the expansion of remote sensing use and how to overcome them, and mechanisms to facilitate the adoption of remote sensing. The information exchanged at the workshop and the very lively discussions it engendered, together with the experience of the steering committee, form the basis of this report. Many of the issues previously considered by the steering committee also proved relevant to the issues that concern state and local decision makers. In its first report, Transforming Remote Sensing Data into Information and Applications,2 the steering committee examined institutional issues related to the adoption of remote sensing applications in new settings and to bridging the gap between raw remote sensing data and the information needed by decision makers. That report focused on remote sensing applications in the coastal zone, but the issues it examined have far wider relevance. Moreover, because many state and local governments have jurisdictional responsibility for some coastal issues, the coastal applications discussed in that report may be of interest to them (see Appendix A for the executive summary of the report). The steering committee’s second report, Toward New Partnerships in Remote Sensing: Government, the Private Sector, and Earth Science Research,3 examined public–private partnerships for providing satellite remote sensing data for scientific research. Again, some of the issues discussed in the second report, though not directed at state and local government needs, can be instructive in thinking about remote sensing in the nonfederal public sector. HISTORY The technology of land remote sensing has advanced rapidly. Beginning in the 19th century with the photographic reproduction of landscapes obtained through a variety of devices that enabled overhead photography, the field expanded rapidly in the 1930s and 1940s with the development of airborne photog 2 Space Studies Board and Ocean Studies Board, NRC, Transforming Remote Sensing Data into Information and Applications, National Academy Press, Washington, D.C., 2001. 3 Space Studies Board, NRC, Toward New Partnerships in Remote Sensing: Government, the Private Sector, and Earth Science Research, National Academy Press, Washington, D.C., 2002.
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raphy. The commercial firms that obtained these photographic images were generally small and operated on a local rather than a national scale. With the launch of the first civilian land remote sensing satellite in 1972 and the beginning of global-scale remote sensing, there was an expectation that state, county, and local governments would rapidly create applications for this new source of information, but for a number of reasons public sector applications were slow to develop. There were limitations on what could be accomplished with satellite data in urban areas because the resolution of the satellite imagery was lower than that of the airborne imagery upon which many cities had depended for so long. Few people who had technical experience with remote sensing data worked in the public sector, which in any case had established nontechnical means of obtaining the necessary information. In short, for many jurisdictions, there was no compelling reason to incur the added institutional and budgetary expense of introducing a new technology into their operations—a technology perceived as having limited practical applications. There have since been changes in both the institutional and the technical capabilities of state and local governments. Management of spatial (geographical) data on terrains, land ownership, land use, and soils collected by state and local governments has become far more sophisticated in recent years. GIS software has become more flexible, powerful, and easy to use. Layers of digital data can be combined to form new information products. Many state and local governments now employ staff with geographic information science expertise and use GIS databases routinely. Global positioning system (GPS) technologies also contribute to the geospatial resources available to the public sector. GIS and GPS technologies are particularly useful in urban applications and management. One of the advantages of these technologies is that they can easily be used in conjunction with remote sensing. Because remote sensing data can be georeferenced, they can be combined with topographic, land use, or tax data in a GIS database to provide information not previously available. State and local governments have never before had such a broad array of land remote sensing data available to them. Table 1.1 lists some of the types of remote sensing data from which these governments can draw. The data can be obtained from an array of sources, such as the federal government, foreign governments, commercial satellite remote sensing companies, and aerial photography firms. ORGANIZATION OF THE REPORT Chapter 2 discusses how state, local, county, and regional governments are using remote sensing data; it examines cases in which remote sensing was used to solve real problems. Chapter 3 looks at how these governments addressed the problems that arose in connection with the introduction of remote sensing appli-
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cations. Chapter 4 discusses the mutual benefits when federal and nonfederal agencies cooperate in remote sensing and examines the role of the private sector in meeting the remote sensing data and information needs of the nonfederal public sector. Chapter 5 contains the findings and recommendations of the steering committee. Appendix A contains the Executive Summary of the steering committee’s first report, which addresses barriers to developing remote sensing applications and proposes steps to address those obstacles.
Representative terms from entire chapter: