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EARTH'S RESOURCES INTRODUCTION The Earth's Resources Panel considered the traditional areas included in the study of the earth's renewable and nonrenewable resources: agriculture, forestry, rangeland, geology, water resources, and land use. Remote sensing involves such functions as locating features on the earth and mapping them, measuring geological phenomena, studying water quality and quantity, and making studies of land use patterns. The primary benefit of satellite data to the earth's resources community is that they provide a current synoptic view from space that makes it possible to detect patterns and to recognize features not readily seen in conventional data. A notable geological example is the detection, in Landsat images, of previously unrecognized extensions of the San Andreas fault in California. Activities related to research on or management of renewable or nonrenewable resources may be grouped into three phases: inventory/survey, monitoring, and predictive modeling. In the inventory/survey phase, the quantity and quality of the resource of interest within a specific area are determinedâfor example, forest coverage in a particular geographic area. Monitoring involves detecting changes in the resource of interest, such as determining forest coverage increase or decrease from year-to-year. Predictive modeling yields an analysis of trends within a given area that, when coupled with environmental, socioeconomic, and political information, would facilitate or improve management decisions. For example, data and information from inventory/survey and monitoring activities would be used to drive mathematical models so that a decision to cut a timber stand in order to permit a residential development could be based on a rational analysis.
The degree to which a space station or space platform contributes to more effective or more efficient production of remotely sensed data will determine its utility for earth resources applications. The Panel reviews each of the earth resources areas, then comments on what is needed to improve the utility of remotely sensed data to the earth resources community and discusses the role of man in space. PRESENT STATUS Since the launch of the first Landsat in July l972, many investigations have shown the usefulness of remote sensing for earth's resources exploration management. In some cases, operational activities have been established using satellite data. For instance, there have been demonstrated benefits from locating and mapping of vegetative cover (crops and forests), and from observations of geologic phenomena, water quantity and quality, and land use patterns. Unfortunately, because of problems with data processing, handling, and distributionâand more recently because the continuity of Landsat data is unpredictableâfew of these applications can be considered operational in terms of meeting users' needs. Although processing and distribution have improved over the past ten years, at present the elapsed time between data acquisition and receipt of data by the potential user is still too long for many important applications. In some cases, the amount of data correction that must be done by the user before information can be extracted from the data is substantial. Agriculture, Forestry, and Rangeland Agriculture, forestry, and rangeland activities cover a variety of renewable resources that are heavily dependent on human activity. In general, these resources are managed on a cyclical basis in which harvest, regeneration, and intermediate cultural activity play dominant roles. Also, the management of agriculture, forest, and rangeland is severely affected by vagaries of weather and by the effects of fire, wind, and water. Earth observation programs employing remotely sensed data have been used extensively in agricultural
applications. Landsat data have been used to produce detailed crop information for large areas. The LACIE (Large Area Crop Inventory Experiment) project demonstrated the utility of processed Landsat information combined with other data to develop estimates of worldwide wheat production. Other common Landsat applications in agriculture include the monitoring of irrigated lands and assessment of water needs, determination of the location and spread of crop disease and insect infestations, detection of salinity, and mapping of general agricultural land capability. For example, Landsat data were used to update the inventory of four million acres of irrigated lands along the Snake River in Idahoâa task that the time and cost of conventional techniques had ruled out for the past decade. Minerals and Petroleum Exploration Satellite images combined with other forms of data have helped in maintaining inventories and surveys of existing mineral and petroleum resources. Repeat coverage has provided surface change maps that help monitor mining operations and describe progress. Landsat data have provided a new dimension in the ability to select likely locations for exploration. Geologic applications of remote sensing include geodetic measurements (namely, historical data, patterns of past tectonic activity, and crustal movements), geologic environments (including sedimentary basins, domes, and igneous and raetamorphic formations), and episodic events (such as landslides, avalanches, volcanic eruptions, erosion, and coastal change). Land Water Resources Water is an important component of agriculture, forestry, and rangeland use; minerals and petroleum exploration; and land use. Land water resources are different from ocean and estuarine waters; land water resources are those water bodies, surface and subterranean, existing or originating on land. These include rivers, streams and creeks, reservoirs, lakes, ponds or other standing water bodies, groundwater and underground water, aquifers, and tables.
10 Landsat has been used to conduct watershed inventories that have enabled states to foresee flood problems, drought, and water supply fluctuations. By integrating information on snow depth from ground stations with the snow-covered area estimates obtained from the satellite, accurate predictions can be made of future water runoff and anticipated water supplies within drainage basins. Landsat can also help states inventory, measure, and monitor surface water levels. As a result of congressional legislation requiring the safety inspection of dams, numerous states have used Landsat computer analysis techniques to identify and map water reservoirs. As an example of the magnitude of this effort, Texas used Landsat data as an aid in the inventory of 4,240 dams, each impounding 50 acre-feet or more of water. Landsat, with a l6- to l8-day coverage cycle, is an excellent tool for recording fluctuations in water levels caused by drought or flood conditions. The availability of such current information allows states to more quickly and effectively deal with certain types of disasters. Coastal Zone Management The coastal zone programs, resulting from both federal and state legislation, require frequent and current information. This information may vary from delineation of the coastal zone and measurement of the shoreline, to monitoring its erosion and mapping of its vegetative cover and land use changes. Alabama officials found that conventional methods of shoreline measurement did not meet the needs for repetitive and timely measurement of shoreline erosion. Through Landsat*s computerized information, a cost-effective method to more accurately determine shoreline length was developed. The New Jersey Department of Environmental Protection has used a combination of satellites and aircraft to detect land use changes in the coastal zone. It also has monitored ocean waste disposal and measured shoreline erosion as required for the receipt of federal funds under the Coastal Zone Management Act. Land Resource Planning and Management Information on current land development patterns is required for many urban, regional, state, and national
l1 programs. Landsat can provide information on land use so that changes can be measured quickly and easily. To date, one of the most successful and beneficial state applications of Landsat data has been in meeting the requirements for the Enviromental Protection Agency's Section 208 Area-wide Waste-water Treatment Program. A basic objective of the program is to determine the types and distribution of nonpoint sources of water pollution as a basis for developing a plan for their abatement. The states of South Dakota, Ohio, and Illinois, the North Carolina Triangle J, and the Ohio-Kentucky-Indiana Regional Councils of Governments are among numerous state and local governments that use information interpreted from Landsat data to help meet EPA Section 208 requirements. States often encounter problems when gathering information about the larger geographic areas used for resource development. Land and water inventories necessary for many developmental decisions can be produced quickly and inexpensively using Landsat. In addition, vegetation can be mapped to help determine land capability and wildlife impact. While Landsat can be used effectively for overviews and for selecting areas that require more detailed analysis, more specific information derived through high-altitude photography or ground surveys may be needed for further detailed analysis. However, the general overview from Landsat data is helpful to legislators in determining the location and extent of area in need of policy change. TECHNOLOGIES NEEDED The technologies for earth resources involve sensors, processors, storage, and communications systems. It is felt that these technologies are progressing rapidly, and should be ready for implementation and exploitation in the space station time period. Sensor Technology Space sensor technology has quickly shifted from a photographic silver halide media to multispectral detectors with digital output. Even the multispectral sensors are changing. Complex mirror scan systems are being replaced by linear array "push broom" detectors that
l2 "sweep" the earth with the satellite motion. These sensors represent the future technologies, but have some deficiencies. The sensors currently used are limited to the visible and near-infrared portion of the electomagnetic spectrum. It is anticipated that a broader spectral range is needed, including the thermal IR. Some advanced push-broom sensors include pointing capability, which is needed in order to be able to acquire images of opportunity that may be off-nadir. This capability will also provide a stereo type of image, useful for geological exploration. Recent experiments have shown that a higher spectral resolution and many spectral bands may be important for improved feature discrimination. Because of the increased data rate that would result, the ability to select the "best bands" will become increasingly important. Processing Technology Digital computers are now used routinely for processing digital images. Both general purpose and special purpose computers are being used. Because of the large amount of data to be processed and handled in future earth observation missions, it is likely that the necessary processor architecture will be one that can support both general and special purpose functions. For example, data management processing can be handled adequately with a general purpose computer, but some complex image processing functions, such as multispectral classification, will require special purpose computers. Some applications, involving many operations on the data, may require parallel processor architecture. An increasingly important function is to geometrically "merge" diverse data sets into the same geographic coordinates, such that a multitier data base results. This involves geometric manipulation of all sensor data sets for a particular geographic region. This type of data set is particularly useful for analysis and information extraction, but it requires significant processor power. Once all space station functions have been defined, such as calibration, geometric correction, information extraction, data compression, data presentation, and data handling, an appropriate architecture can be developed. Low power and weight and high performance will be a difficult but important objective.
l3 Storage The space station can serve as an orbiting archive. At the least, it will be necessary to store and assemble data from multiple sensors before distribution to the users. Thus, large memory requirements can result. A current Landsat-4 Thematic Mapper scene consists of about 260 million bytes, which corresponds to about 2 billion bits. If multiple scenes from different sensors are to be combined in the satellite, the onboard requirements could be about l0 billion bits. If the space station serves as an orbiting archive, the storage requirements can be orders of magnitude larger. Low-power storage technologies would be necessary to support these operations. Communicat ions Communications technology has kept up with the demands of space systems. The Tracking and Data Relay Satellite System now supports data rates of 85 million bits per second for Landsat-4, and could provide even greater data rates. However, future operational systems may swamp these capabilities, as there are physical limits to the number of channels and the data rates that they can support. In addition, interference is an increasingly serious problem. When current and future applications are taken into consideration, there will be a deficit of communications channels. It is likely that the space station may decrease the demands upon communications in that the potential exists to convert sensed data into information products that have several orders of magnitude fewer bits than the raw data. If the information products are sent directly to the users, a reduction in the communications and processing requirements may result. POSSIBLE USES OF A SPACE STATION TO SUPPORT DATA ACQUISITION AND PROCESSING Previous unmanned systems for earth observation data acquisition, processing, and distribution have suffered from several problems: An excess of data Incomplete calibration of the sensor data A small percentage of the acquired data processed
14 Nontimely distribution of the data to the user community High data costs The space station may offer an opportunity to improve this situation. At least, it can explore methods, technologies, and procedures to improve and make more efficient the flow of data to the users. Reducing the Excess of Data Past unmanned sensor operation would acquire data during the time the sensor has been programmed to be on. With human control of the operation of space station sensors and systems, there could be a reduction in the amount of data that is acquired. Cloud cover, failed or faulty sensor operation, and other conditions that should inhibit sensor operation could be monitored by a human in the space station and used to control the data acquisition periods. It is likely that images of opportunity could be acquired by an attentive operator, such as fire, storm, and other conditions. In this way, the sensor is focused on the event of interest, improving the information-to-data ratio. Eliminating or Reducing Defective Sensor Data Sensor problems, such as a failed detector, noisy detectors, or incomplete or improper radiometric calibration, are frequently not detected until the data have been received by the ground system. If these problems are not detected on a timely basis, repeat observations need to be scheduled. With an attentive operator in the space station, these kinds of problems could be detected immediately and corrected, reducing the amount of defective data transmitted to the ground. Improving the Percentage of Processed Data That Is Acquired The space station provides the potential for having an intelligently controlled platform and sensor. Thus, nearly all data that are requested are reliable and can be used and processed. Further specific data requests could
l5 be scheduled, acquired, and specially processed for the user. These data could be directly disseminated to the user after acquisition and preprocessing, thus reducing the need for additional backup data. With sufficient processing capability on the space station, information extraction operations, such as multispectral classification and principal component analysis, could be performed, thus reducing the amount of bits that need to be transmitted and providing information products directly to the user. Providing Data on a Timely Basis to the User Previous systems have provided data to the user late; weeks or even months have elapsed from the time of data acquisition. As some of the data are perishableâthat is, they have little value if conditions have changed (this is particularly important in agriculture and hydrology)âthis can be a serious problem to the user. It is likely that, if sufficient data processing capability exists on the space station, processed data and even information products could be sent directly to the user in nearly real-time. In any event, a space station could support experiments involving ground-based user control of the sensors and processing equipment. The space station operator would serve as a backup in an experiment directed toward future automated and user-controlled data acquisition systems. Reducing Costs The concentration of machine and human resources at the point of data acquisition could reduce costs. Current approaches involve multiple processing, communications, and data distribution nodes. There are many people and systems in the data path that increase the final cost of the data. Data preparation, recording, mailing, and handling are expensive. If the data flows through a minimum number of nodes, cost minimization is possible, f manned space station offers this possibility. An interesting concept is the use of the space station as an orbiting archive, thus allowing a user to query and receive data directly from a large data base and eliminating conventional methods of physical data handling, such as shipping, inspection, receiving, etc.
l6 Orbit Considerations Remote sensing satellites have been flown in the following types of orbits: Near-polar, circular, sun-synchronous, low earth orbits near or below l,000 km (exemplified by Nimbus, TIROS, Landsat, Seasat, and Defense Meteorological Satellite spacecraft) Low-inclination, asynchronous, low earth orbits (exemplified by Shuttle and Explorer-type missions) Geostationary orbitsâeither zero or very low inclination (exemplified by both communications and weather satellites primarily designed as operational-type missions) Sun-synchronous, low earth orbits are most important to earth resources users. Landsat uses an orbit that provides synoptic coverage because the satellite overflys the same point on earth at the same time of day at l6- to l8-day intervals. In summary, a near-polar, sun-synchronous orbit is essential for most remote sensing of the earth, but some sensors will have to be in geosynchronous orbit. Orbits giving skip coverage can better record episodic events, because the same general area is observed more frequently. Adjacent orbits are useful for mosaics and for signature extension (Landsats l, 2, and 3 were in adjacent orbits; Landsat 4 is in a skip orbit, i.e., where successive meridional paths are separated by one frame-width). For most sensors, equator crossing times should be in daylight, but thermal infrared sensors may require night crossing times. Circular or near-circular orbits are essential. THE ROLE OF MAN The Panel can identify a number of roles for a human in space which may be grouped under the following headings: transient-phenomena identification; data-quality assurance; data processing, compression, and storage; experimentation; and repair, maintenance, and servicing. These roles are described in ensuing paragraphs.
l7 Transient-Phenomena Identification Transient phenomena or episodic events such as hurricanes, volcanic activity, tornadoes, and floods cannot be predetermined as to precise time of occurrence or location, but a human in space could tell when a phenomenon was in progress or imminent, and could select the appropriate mode of data collection. For some events, the alerting of ground-based agencies could provide for better emergency planning. Direct notification of public communications channels as to the width, path, and direction of a natural disaster may help save lives and protect property. Data-Quality Assurance Man could be used to monitor the quality of data collected in a space station. A human in space will be nearer to the sensors and therefore could more readily identify the source of any sensing or measuring problem and make the necessary correction. He could also control the instruments by changing bandwidth, response intensity, and fidelity range. Further and more rapid improvement of data quality could be achieved if a person is observing the instruments as they perform. Data Processing, Compression, and Storage As previously noted, a trained human operator in a space station could accept or reject data, decide to apply data-compression techniques, and decide whether to store data onboard or transmit it to the ground. All of these functions could result in a substantial reduction of the enormous volume of data that would otherwise be transmitted to earth and would have to be processed before its utility could be evaluated. The savings in data relay demands and data processing costs could be significant. Repair and Servicing The in-flight repair of Skylab not only saved the mission from a disaster, but also enabled the astronauts to complete most of the experimental objectives. Many of the solutions for failures or problems in a space station
l8 would likely be determined on the ground, but a human in space would be needed to make the actual repairs. When one considers the variety of instruments and sensors that could be used for remote sensing from space, the value of a human for in-situ repair and servicing becomes apparent. CONCLUSIONS The Panel has identified some of the potential benefits to be derived from a manned space station. The Panel has identified some roles for man, although we cannot justify a space station solely on the basis of earth resources applications. A space station or unmanned platform would need to be in a low, near-polar, sun-synchronous orbit; some future provision should be made for a geostationary orbiting system. The sensor payload should be designed to operate interactively. Continuity of data should be assured and data formats should facilitate the integration of data from different sensor systems.