Multiplicity of Environmental Satellite Data Uses
It is a fact that NOAA will never fly another “weather” satellite. The next generation of polar operational environmental satellites (POES) and geostationary operational environmental satellites (GOES) that will fly near the end of this decade are designed to expand observational capability beyond severe weather and near-term forecasting to take on the comprehensive environmental mission identified in NOAA’s vision, mission, and goals (see Box 2.1). NASA’s Earth Science Enterprise mission is “to understand and protect our home planet by using our view from space to study the Earth system and improve prediction of Earth system change.”1 Today’s user community is already using data and information collected by NOAA’s operational satellites, and NASA’s research satellites, to address a multiplicity of environmental applications.
EXAMPLES OF USES OF ENVIRONMENTAL SATELLITE DATA IN 2010
In the second decade of the 21st century, information that in some way is derived from operational satellite data will be used ubiquitously. Much of this information will be generated directly by NOAA and NASA; the rest will be produced by other government agencies or commercial vendors as “added-value” material. Because accurate information is part of any decision-making process, the opportunity
To move NOAA into the 21st century scientifically and operationally, in the same inter-related manner as the environment that we observe and forecast while recognizing the link between our global economy and our planet’s environment.
NOAA’ s Mission
To understand and predict changes in the Earth’s environment and conserve and manage coastal and marine resources to meet our Nation’s economic, social, and environmental needs.
NOAA’s Mission Goals
SOURCE: Excerpted from “New Priorities for the 21st Century, NOAA’s Strategic Plan for FY 2003–FY 2008 and Beyond,” available at http://www.spo.noaa.gov/pdfs/FinalMarch31st.pdf.
for satellite data to be employed to aid decision makers (or simply satisfy curiosities) is essentially limitless.
Historically, the dominant use of operational satellite data has been to serve NOAA’s mandated mission of weather forecasting through the arm of the National Weather Service (NWS). Thus, the bulk of the satellite-based products generated by NOAA were designed for these NWS applications. A new trend has developed, which will continue through the next decade, in which operational satellite data are used for all types of environmental monitoring of the Earth system. These operational data are now and will continue to be packaged and delivered to provide timely and targeted information for innumerable reasons, most of which relate to some type of decision-making process. Additionally, retrospective analysis of satellite products is also growing as demands for high-precision, long-term time series of environmental variables are required. Thus, new products based on operational satellite data are finding significant utility outside the traditional weather-forecasting arena. As a consequence, the user community is expanding rapidly, and NOAA’s role in fulfilling this demand for increasingly precise and up-to-date environmental information beyond weather forecasts must be addressed. The following is a sampling of uses presented here to alert the appropriate agencies to the growing demand for information that at least in part will require operational satellite data. These examples
extend beyond the typical research currently being performed within the traditional scientific disciplines.
In 2010, the dominant use of satellite data will likely remain unchanged as NOAA supports the NWS’s mandated forecasting mission, thus allowing the government to fulfill its obligation to protect life and property. Users at the level of producing high-value forecasts include the NWS, DOD (for military operations), international partners, and major commercial interests. Agencies and corporations at this level would also support the assessment, prediction, and mitigation of environmental threats. Because hazards are having an increasing impact on economies, the importance of accurate space-based information to detect and predict their consequences will remain an essential function of the agencies in the coming decades. Not only are the effects of natural disasters (e.g., floods) increasing, but now those of human-induced catastrophes (e.g., large-scale terror attacks) must also be factored into the monitoring and forecasting mission of the appropriate agencies. Today the impact of satellite data is much larger than the impact of data from radiosondes in both the Northern and Southern Hemispheres (Figure D.1). There is now a stronger dependence on satellite data in the European Centre for Medium-Range Weather Forecasts (ECMWF) system, and the influence of other non-satellite data types is becoming less important (for details see the ECMWF case study in Appendix D).
Monitoring of Climate Variability
Satellite data now permit a global view, capturing the surface of the ocean and the land as well as the atmosphere. Remotely sensed sea-surface temperature fields and sea-surface elevation have provided the ability to track the evolution of large-scale patterns of climate variability involving the ocean, with the AVHRR and altimetry images of the evolution of the 1997-1998 ENSO a good recent example. Bringing such records together with remotely sensed vegetative index fields shows the impact on land of the drought and rainfall patterns linked to the large variability in sea-surface temperature. Improved accuracy and resolution in sea-surface temperature fields are sought not only by those studying and predicting climate variability, but also by the NWS community because of the role of sea-surface temperature in forcing the atmosphere, including its influence on hurricane tracks. High-quality surface vector winds and altimetry will also be sought because, together with in situ data from the ocean, these remotely sensed fields will allow estimation of the wind-driven currents and also the density-driven or geostrophic currents that together transport and redistribute heat in the ocean.
Detection of Global Change
Analysis of long time series of environmental data (e.g., the analysis of sea-surface temperature) has grown in importance, as have concerns about changes occurring in the Earth system and the role of human activity in those changes. Many of these changes are minuscule on a year-to-year and decade-to-decade basis, and detecting them therefore requires exceptionally meticulous, high-precision monitoring—which is a relatively new requirement for agencies. To achieve the levels of precision necessary for detection, retrospective reanalysis of many data sets is required. The recent finding that global terrestrial net primary production increased 6 percent between 1982 and 1999, the “greening of the biosphere” (see Plate 8), was possible only by building a climate data record for a normalized difference vegetation index (NDVI) based on the latest theory and algorithms applied to the full historical record2 (see the section “The AVHRR NDVI Pathfinder” in Appendix D). In such cases the use of NOAA-NASA satellite data falls into a category of scientific research that has no specifically designated home and thus is difficult to perform, given the many years required to develop and establish such activities. In a slightly different vein, data-mining efforts will expand in the coming decades as new products based on old operational satellite data are discovered and developed. Retrospective analyses and data-mining research emphasize the need for convenient and rapid access to archived raw and processed data.
Because the weather forecasting mission has dominated the use of operational satellite data, product generation has generally been tied to atmospheric and hydrologic systems. Detection of global change requires measurements that can show variations and trends in all types of environmental data often gathered only serendipitously in the course of traditional weather monitoring. Of particular concern is the place of satellite observations of terrestrial conditions. As indicated below, there are significant legal and economic development issues related to precise measurements of terrestrial systems. Beyond those applications is the need to develop the science of terrestrial variability in the global context. Because humanity lives and grows its food on the surface of the planet, any threats to the carrying capacity of the terrestrial sphere would have considerable implications for policy decisions regarding land use.
Production of information about this vital component of the Earth system from the global change detection standpoint could be formally assigned a home in the federal government. Additional aspects of the Earth system, such as atmospheric
chemical composition, habitat viability, and so on, will become more visible in science and policy initiatives as information on variations in such parameters is developed.
Economic growth and, in particular, sustainable development are themes likely to become a greater part of the environmental landscape in the next decade. To support the many civilian applications of the Global Positioning System (GPS), numerous companies have emerged with GPS-related technologies or services. For example, several companies now produce receivers, others focus on surveying and mapping, still others support navigation and guidance applications, and some are involved in tracking services and wireless technologies (see the GPS case study in Appendix D). Today the competition for economic opportunities is global and will likely only increase over the next decade. Environmental information is a necessary component in business decisions of this type. Because satellites in general are the only means of obtaining systematic measurements of the entire globe, it is possible that downstream products based on operational satellite data will be used extensively and with greater frequency in the coming decade to enhance a company’s prospects for business recruitment and success.
Over longer time periods, environmental data will be valuable in efforts to assess changes in ecosystems that may result in certain regulatory measures which in turn have economic consequences. In large part, citizens, who are increasingly being effectively represented through advocacy groups, desire clean, robust, and natural environmental surroundings. Assessments of the state of a particular ecosystem and determining what to do about current conditions may hinge on the products created from space-based data.
Resolution of Legal Issues
An emerging aspect of environmental data use relates to legal issues for which certified and accurate information is now required. For example, to set premiums the energy-use insurance industry must factor in estimates of upcoming weather conditions, and NOAA GOES-R can improve the accuracy of energy load forecasting.3 NOAA may find itself in the high-profile role of having to address these coming
situations on the basis of in situ and/or satellite data. Also, certification of environmental parameters and variation in them has the potential to become critically important in relation to bilateral or multilateral treaty obligations, particularly with respect to global climate change initiatives. In a more parochial sense, regulatory actions to deal with local pollution, for example, will have to take into account local weather factors and forecasts. The precise monitoring of such parameters, which can trip certain regulatory mandates, may have a large impact on local economic activity and, if not wisely applied, may result in significant legal challenges. Thus the means by and manner in which NOAA data are gathered and processed may increasingly become the subject of court disputes involving tremendous financial assets.
Remote sensing has begun to be used by health authorities to monitor conditions in the breeding regions of disease vectors, such as malaria-carrying mosquitoes.4 Data on rainfall, temperature, local vegetation, and soil moisture from satellites such as Landsat 7 and NASA’s Terra orbiter are used to build a profile, which is combined with high-resolution imagery from commercial satellites, such as Ikonos and QuikBird, to determine where mosquito-spawning areas are likely to appear. Alerts are issued when the conditions for outbreaks can be predicted. The technique of “landscape epidemiology,” first used in the 1960s, helps predict the spread of a disease, based on its surrounding geography and climate. Today, daily Earth examinations conducted by satellites in geostationary orbits have begun to provide epidemiologists with enough long-term data to begin making associations between climate and disease. “For a long time there was no good systematic collection of information that would let us establish that ecosystem-disease relationship,” Assaf Anyamba, a research scientist with NASA’s Goddard Space Flight Center, stated. “But now,” he continued, “we have a coherent picture from which to begin to see how that relationship forms.”
Transportation and Recreation
The lack of limits to the uses of environmental satellite data poses exciting possibilities. A recreational traveler today has a general idea of the road conditions ahead and how they might change during his journey. In the next decade, one can
imagine the same traveler purchasing a service that depicts kilometer-by-kilometer road conditions, tied in with high-resolution forecasts to let the traveler anticipate conditions for the entire trip. The next decade may also see recreational and commercial mariners being provided with up-to-date information on surface winds, wave heights and periods, sea-surface temperature, and other elements of marine weather—products and forecasts that will improve mariners’ safety at sea and the efficiency of vessel routing. In such instances, NOAA will provide satellite data to support and complement NWS forecasts, which would then be tailored by a service provider for a particular traveler. The Department of Transportation, also using NOAA data as well as the department’s own data sources, would generate road conditions and forecasts from which a service provider could again tailor the output. In this case, the chain of users has followed a path from NOAA to two government entities, to a service provider, and then to the end user. The end user is a fee-paying traveler with no requirement for IT sophistication, and so it is clear that intermediate users are essential to the successful delivery of the satellite-enhanced information.
The specific path (chain of users) of NOAA’s environmental data from observation to end user is now, and will continue to become, an increasingly complicated web woven principally by the invisible hands of entrepreneurial visionaries. The role of NOAA in enabling such an information explosion is addressed in Chapter 5.
USERS OF ENVIRONMENTAL SATELLITE DATA IN 2010
As indicated above, users of operational satellite data will span a broad spectrum encompassing mainstream users such as government agencies that require massive and expensive infrastructure as well as casual Web-surfers who rely on inexpensive, hand-held devices. Some will require the fundamental radiance counts transmitted from spacecraft to Earth, but most will receive a heavily processed product whose interpretation requires no training. In utilizing products that in some way originate in operational satellite data, a single person, company, or agency may fall into several categories of end user. Though not exhaustive, the following list suggests “discriminating dimensions” according to which users of or customers for operational satellite data might be categorized:
Adequacy of funding base: Cost of functional infrastructure essential for effective implementation;
Type of organization: federal, state, local, commercial, educational, non-profit/individual;
Location in chain of users: end user, intermediate user, source;
Component or discipline of interest: weather, hydrology, terrestrial/land use;
Site accessed for data: National Centers for Environmental Prediction (NCEP),
NWS, Earth Observing System Data and Information System (EOSDIS), National Climatic Data Center (NCDC), vendor, university, media, non-profit;
Level of product needed: digital counts, geophysical products, geolocated products for subsetting, highly processed images and information;
Requirement for timeliness: real time, near-real time, retrospective;
Motivation: profit, science, education, everyday life, curiosity, mandated mission; and
Cost sensitivity: recurring and non-recurring costs of data and information access, e.g., Landsat user fees.
The committee was presented a classification of users based on the expertise of individuals who are themselves users of EOSDIS satellite data sets. “Expertise,” then, may be considered another discriminating dimension. EOSDIS (discussed in “The Experience with EOSDIS” in Chapter 3) was designed to meet the needs of the relatively sophisticated Class 1 and Class 2 users described below, and so the data volumes discussed in the section that follows must be considered a fraction of what will develop as satellite data becomes more readily accessible.
Class 1: Highly technically competent users with an extensive background in remote sensing and full familiarity with new sensors and algorithms, for example, the ECMWF, which is an operational institute with strong research activity in all aspects of weather prediction and a heavy investment in the use of satellite data (for details, see the case study on ECMWF in Appendix D).
Class 2: Users who are competent in remote sensing but who lack familiarity with the new sensors and algorithms, for example, users of direct broadcast data, which is acquired by satellite sensors and broadcast in real time to any ground station within range of the satellite’s current position (see the case study on direct broadcast in Appendix D for details).
Class 3: New potential users with modest remote sensing training and minimal understanding of algorithms and data details. A primary objective of the NASA Earth Observing System has been to deliver usable remote sensing data products to a wider array of less sophisticated users (see the section “MODIS Fire Rapid Response System” in Appendix D).
Class 4: Non-technical users (education, law, policy, etc.) with no background in Earth sciences who have limited occasional use—e.g., the many people who access satellite-based weather data several times per day (i.e., composite NWS images of weather conditions). Although it was developed by the military for military purposes and continues to be operated by the military, civil users worldwide have found many applications for the GPS (see the case study on the GPS in Appendix D).
VOLUME OF REQUESTS MADE FOR NOAA-NASA PRODUCTS
Few models exist today that will allow for a reasonable estimation of the data-request load in 2010 for operational satellite data. It is clear that the volume of satellite data available for use will be at least an order of magnitude greater than the current volume, and it is anticipated that the number of uses and users will grow substantially. Requests from approximately 18,000 unique IP addresses are made each month for the mostly scientific data in the EOSDIS.5 In FY 2003, 228,000 distinct users received data and information products from EOSDIS. Depending on how “user” is defined, the range for EOSDIS extends from 7,000 distinct users (for the often-voluminous level-0 through level-4 scientific data products via the EOSDIS Core System) to more than 2.1 million distinct users (including Web page hits) based on e-mail addresses in FY2003. Designed to distribute the large EOS satellite data files, the EOSDIS Core System distributed 80 percent of the total distributed EOSDIS data volume.
The statistics on data use show a dramatic increase over 4 years in the number of products retrieved immediately from Web sites, FTP servers, and the data pools.6 This asymptotic convergence suggests a nearly total reliance on electronic delivery in the future. About 10 to 20 percent of the users are from U.S. educational institutions; these tend to be higher-volume users, accounting for 40 percent of the products received. The archive is growing at around 4.5 terabytes per day while the daily distribution of data amounts of about 2.5 terabytes partitioned in about 10,000 specific files. By June 2003 the total EOSDIS storage totaled over 2,500 terabytes.
To accommodate the expected rapid expansion of users (e.g., those engaged in doing elementary school projects, farming, recreation, and so on) of traditional satellite data products, NOAA and other agencies must be prepared to make a significant investment in a data system that is in alignment with the complexity and scale of the challenge. The Comprehensive Large Array-data Stewardship System (CLASS) is being designed by NOAA to catalog, archive, and disseminate all NOAA environmental satellite data produced after 2006. At present, the goals of NOAA’s CLASS are laudable:
One-stop shopping and access capability;
A common look and feel for access;
“EOSDIS Users and Usage: What We Know About Our Users,” summary of presentation to ESISS Scripps Institution, February 17, 2004; Vanessa Griffin and Jeanne Behnke, NASA/GSFC ESDIS Project, Robert Wolfe, Raytheon, Kathy Fontaine, Global Change Data Center, and Steve Adamson, CSC. See http://www.earth.nasa.gov/visions/ESSAAC_minutes.html#.
Integration of data for the user, to include search, browse, and geospatial capabilities;
High data quality and volume;
An efficient architecture for archiving and distribution, including reduced implementation costs through centralization; and
Capability for allowing NOAA to fulfill its requirements regarding archiving, accessing, and distributing large-array data sets.
As access to all types of digital information is made easier, so must the same be true of operational satellite data. As addressed in Chapter 3 of this report, the user interface has long been the greatest impediment to making satellite data readily accessible to public, private, and scientific communities.
SCIENTIFIC APPLICATIONS OF ENVIRONMENTAL SATELLITE DATA
As indicated above, the current flow of real-time and near-real-time information in NOAA is directly related to weather, ocean, and space monitoring and forecasting. These data are supplied to National Centers for Environmental Prediction (NCEP) users who may simply access a local NWS Web site and be directed to any number of satellite data products (essentially enhanced imagery) depicting current weather conditions and those of the immediate past. Other agencies (e.g., DOD, the U.S. Mission Control Center) and international partners (e.g., the United Kingdom) receive specific satellite data directly for their own operational purposes. Several satellite-based products (e.g., sea-surface temperature readings, soundings) are mounted to the Global Telecommunication System for access by member states. The level-1B POES, GOES (synoptic, event, continental United States), and other data product files are transmitted to the NCDC to be archived. Various other government and educational institutions house portions of the basic satellite data. As stated above, gaining access to these data is rather difficult for the typical scientist, and therefore almost insurmountable for the novice user.
Traditional disciplines in the Earth and biological sciences require satellite information as researchers seek to understand the global context of the component of the system being examined. NOAA supports data acquisition and dissemination for applications in meteorology, hydrology, oceanography, and agriculture and for studies of rivers, coasts, and fisheries, among others. Tropospheric ozone, for example, one of the Environmental Protection Agency’s (EPA’s) criteria pollutants, is observable from space as a result of the improved precision of algorithms (see the case study on ozone in Appendix D). Not to be overlooked is NOAA’s task of monitoring and predicting space weather to better accommodate the variations in solar and other influences on the space environment and their impacts on human infrastructure
both in space and on Earth’s surface. Applications in other disciplines for operational satellite data are growing, and all such disciplines will continue to rely on satellite data as researchers work to increase our understanding of the Earth system.
Ten years ago, most of us did not anticipate that we would be using cell phones, e-mail, and the Internet on a regular basis. Today these services are pervasive, and the communications activities thus made possible are commonplace. Commercial companies have been established to provide users with the tools and services they need to support these activities.
Private industry obtains data from today’s NOAA and NASA environmental satellite sensors and packages it for end users, for example, as weather data available on television and via the World Wide Web. The GOES-R sounder and imager cost/benefit analysis found that billions of dollars in cost savings could be realized through the utilization of future geostationary operational environmental satellite data, based on its examination of the eight case studies quoted from below:7
“Convective Weather Products: Benefits to Aviation. GOES advanced sounder data are expected to substantially improve the ability to predict where convective weather such as thunderstorms will initiate within broad regions of unstable air. This information will significantly reduce the cost of operational delays because air carriers will be able to make better tactical dispatch and routing decisions and avoid last-minute actions to bypass these storms.”
“Volcanic Ash Advisories: Benefits to Aviation. GOES advanced imager data will provide more accurate and timely warnings of the presence of airborne volcanic ash plumes that can seriously damage aircraft and jet engines and have the clear potential to cause serious aviation accidents. Winds derived from GOES advanced sounder data will enable more accurate and timely forecasts of the speed, altitude, and direction of these plumes. More accurate and timely volcanic ash advisories will reduce the cost of repairs and engine replacement from ash encounters and reduce the risk of catastrophic loss of aircraft, passengers, and crew from this hazard….”
“Temperature Forecasts: Cost Savings to Electric Utilities. GOES advanced imager data on clouds and winds and advanced sounder data on humidity profiles
are expected to substantially reduce both the average and the variance in error in short-term (3-hour) temperature forecasts. Improved accuracy in temperature forecasts will increase the accuracy of electric utilities’ short-term electricity load forecasts. Improved load forecasts will enable utilities to reduce their costs by reducing the average amount of generating capacity they keep in ready reserve (operating reserve) and the average amount of spot-power purchases they make in order to meet customer demand.”
“Temperature Forecasts: Benefits to Agriculture /Orchard Frost Mitigation. As in Case Study 3, GOES advanced imager data on clouds and winds and advanced sounder data on humidity profiles are expected to substantially reduce the amount of error in short-term (3-hour) temperature forecasts. The increased data density provided by ABI and HES will also improve forecasters’ ability to provide forecasts tailored for particular agricultural districts and areas. Improved temperature forecasts will improve orchardists’ decisions about how much to spend on frost mitigation on a given night during sensitive budding and flowering periods and will decrease the average amount they spend on mitigation activities over time.”
“Soil Moisture Measurements: Benefits to Agriculture—Improved Irrigation Efficiency. The GOES-R sounder will improve the accuracy of evapotranspiration (ET) estimates because of its ability to discriminate temperature and humidity changes at the lowest layer (boundary layer) of the atmosphere where plants and soils interact with air masses. In addition, the GOES-R sounder (if it uses the GIFTS sampling interval of 4 km) will provide these data with much more spatial detail than the current GOES sounder. The soil scientists at the University of Wisconsin (Norman and Diak) who are developing this technique state that the GOES-R sounder data will provide the greatest contribution to improving estimates of ET. In addition, they state that the GOES-R imager thermal channel will provide data on surface temperature changes (between sun-up and mid morning) on a substantially finer scale (2 km) than the current GOES imager (4 km). This is a four-fold improvement in spatial data and, when integrated with the GOES-R sounder data, will provide additional ability to discriminate ET at a scale closer to that of typical irrigated fields.
“Hurricane Landfall and Intensity Improvements: Benefits to Recreational Boating—Damage Avoidance. The increased spatial resolution and update cycle for GOES-R sea surface measurements will enable GOES-R to capture more continuous sea-surface temperature (SST) readings, thus providing the opportunity to more frequently re-initialize the SST data into models and therefore improve hurricane intensity forecasts. Rapid scan winds, tested on GOES 10, helped to better characterize the divergence, or lift, of the storm and thus the potential for intensification will be the norm on GOES-R. GOES-R improvements in the frequency and spatial resolution will improve the accuracy and density of wind-speed measurements (may double the number of wind vectors and double the accuracy of wind-speed esti-
mates). Improved knowledge of the location of the centers of circulation winds (storms) as well as the speed at which they are traveling (steering winds) will provide better information on when and where a particular storm will make landfall.”
“Temperature Forecasts: Benefits to Natural Gas—Load Forecasting Efficiency. More rapid updates of clouds from the GOES-R imager, when assimilated into forecast models, will improve model predictions about temperature maximums and minimums because clouds moderate temperature peaks and lows. More detailed data on the lower layer of the atmosphere from the GOES-R sounder, combined with more frequent updates and smaller sampling intervals, will, when assimilated into forecast models, also improve the parameterization (input of data on temperature, humidity, winds) of the boundary layer in forecast models. In turn, the models should produce more accurate and specific predictions of temperature, humidity, winds, and precipitation. These potential improvements are based on studies of the contribution of current GOES data to the forecast accuracy of Eta and RUC2 models (Zapotocny, Benjamin, and others).”
“Winter Weather Forecasting: Benefits to Trucking—Accident Reduction. GOES-R will better anticipate near-term ice formation conditions: better models of precipitation as well as more timely and accurate information on land surface temperature to indicate when the ground temperature is below freezing. GOES-R will also provide a higher resolution real time fog product that will allow drivers to more efficiently reroute.”
In looking toward the future, it is difficult to predict exactly what applications users will find for data from environmental satellite sensors (satellite-based or ground-based). However, it is clear that the demand for NOAA environmental satellite data will continue to increase and that users will expect and demand the commonplace availability of more and more processed data through their personal digital assistants or other such devices.
Imagine, for example, that recreational boaters will increasingly seek to determine ocean and weather conditions, both current and projected, in near real time before embarking on a recreational outing, and throughout the duration of the activity. Similarly, people will want to know the micro-climate weather conditions at an event (such as little-league games, weddings, or concerts) that they are planning to attend, and while they are in attendance.
Entrepreneurs will explore the market demand for data and services from NOAA sensors, and companies will be formed, with varying degrees of success, to provide users with the data and the services they desire. Although it was developed by the military for military purposes and continues to be operated by the military, civil users worldwide have found many applications for the GPS (see the case study on GPS in Appendix D). As technology continues to advance, more and more applica-
tions of environmental satellite data will find become apparent in commercial products and services.
LAND DATA AND LAND MANAGEMENT AGENCIES
NOAA, because of its historical agency mission focus on oceans and atmospheres, does not have much experience with land data sets. Major advances in land remote sensing have occurred in the last decade, fostered primarily by the development of the NASA Earth Observing System. These satellite data include derived biophysical variables such as vegetation cover, vegetation continuous fields, bidirectional reflectance distribution function, leaf area index, fraction of absorbed photosynthetically active radiation, photosynthesis, net primary production, and vegetation phenology. All of these are competed and selected MODIS land variables with established, documented algorithms and ongoing production by EOSDIS, yet none are listed as environmental data records (EDRs) for NPOESS. In fact, out of 58 EDRs defined for NPOESS, only 6 are specifically for land and of these only two are vegetation oriented. For the 2012 flight of GOES-R, only 20 of the approximately 170 environmental observation requirements (EORs) are land-surface related; of these, only 4 are vegetation related. Neither NOAA nor the land management agencies are effectively utilizing current satellite technologies and data sets for vegetation science, management, or applications.
Operational satellites provide global environmental weather and ocean monitoring data at kilometer spatial scales, sufficient to track hurricanes and other severe weather, and sufficient to monitor large-scale changes in surface conditions. NPOESS and the next-generation GOES will dramatically improve this capability, with spatial scales dropping from a few to one kilometer, and the frequency of observations improving severalfold. But current NPOESS and GOES-R plans appear to insufficiently address long-term terrestrial utilization trends, observations of which would enable climate monitoring and prediction to fulfill the new NOAA environmental observation vision. And current plans do not invoke a sufficiently fine spatial scale to allow the detailed assessment of land features that is required to track ecosystem health.
NOAA’s vision, as stated in its latest strategic plan, “New Priorities for the 21st Century, NOAA’s Strategic Plan for FY 2003–FY 2008 and Beyond,”8 is “to move NOAA into the 21st Century scientifically and operationally, in the same inter-related manner as the environment that we observe and forecast, while recognizing
See “New Priorities for the 21st Century, NOAA’s Strategic Plan for FY 2003–FY 2008 and Beyond,” available at http://www.spo.noaa.gov/pdfs/FinalMarch31st.pdf.
the link between the global economy and our planet’s environment” [emphasis added]. This suggests that the coupling between the land and the ocean surface and the atmosphere is critical, given that cycles of water, carbon, heat, and so forth are all about fluxes across these interfaces. NOAA’s strategic plan also identifies five types of mission strategies and measures of success:
“Monitor and observe the land, sea, atmosphere, and space and create a data collection network to track Earth’s changing systems.”
“Understand and describe how natural systems work together through investigation and interpretation of information.”
“Assess and predict the changes of natural systems, and provide information about the future.”
“Engage, advise, and inform individuals, partners, communities, and industries to facilitate information flow, assure coordination and cooperation, and provide assistance in the use, evaluation, and application of information.”
“Manage coastal and ocean resources to optimize benefits to the environment, the economy, and public safety.”
The generation of an enhanced set of operational land vegetation variables from NPOESS and other operational systems would have high utility for land management. In addition, Landsat-type observations fill an important niche between the highly repetitive but coarse-spatial-resolution observations from the current NOAA AVHRR and NASA EOS MODIS and the future NPOESS VIIRS instruments and the ultrahigh-spatial-resolution, local observatories such as the IKONOS instrument operated by the Space Imaging Corporation. Landsat-class imagery provides systematic global coverage at a frequency sufficient to capture seasonal variations and at a spatial resolution where land cover dynamics, under the influence of natural processes and human activities, is clearly evident. If indeed we are to understand global change and its relationship to local environmental conditions, then Landsat-type observations will remain a fundamental requirement. These technical capabilities, combined with the 30-year archive, provide the underpinning for addressing emerging science and policy questions with environmental satellite data.
NOAA’s second mission goal, to “understand climate variability and change to enhance society’s ability to plan and respond,” is also discussed in the recent multiagency “Climate Change Science Program Strategic Plan.” It recognizes that “weather- and climate-sensitive industries, both directly and indirectly, account for about one-third of the Nation’s gross domestic product, or $3.0 trillion.” It continues:
Seasonal and interannual variations in climate, like El Niño, led to economic impacts on the order of $25 billion for 1997-98, with property losses of over
$2.5 billion and crop losses approaching $2.0 billion. Given such stresses as population growth, drought, and increasing demand for fresh water, and emerging infectious diseases, it is essential for NOAA to provide reliable observations, forecasts, and assessments of climate, water, and ecosystems to enhance decision makers’ ability to minimize climate risks…. In the U.S. agricultural sector alone, better forecasts can be worth over $300 million in avoided losses annually. To enable society to better respond to changing climate conditions, NOAA, working with national and international partners, will employ an end-to-end system comprised of integrated observations of key atmospheric, oceanic, and terrestrial variables…. [emphasis added]
To achieve this mission goal, as well as pursue the first mission strategy and measure of success (monitor and observe), NOAA plans to “invest in needed climate quality observations and encourage other national and international investments to provide a comprehensive observing system in support of climate assessments and forecasts,” with an “increased number of long-term observations collected, archived, available, and accessible….” [emphasis added]
The land imperative has been demonstrated by NASA’s Landsat program through a series of highly successful sensors that have been operating continuously since 1972. As a NASA program, however, Landsat has yet to achieve operational status and has not had the funding continuity to be part of NOAA/NESDIS’s integrated operational environmental observation system. NASA has, however, proven Landsat’s benefits and has recently demonstrated technology to dramatically lower operational cost. While the current Landsat 7 is still operating, it has reached its 5-year design life, and continuity is not assured even with immediate program restart.
As with the programmatic precedent in the NPOESS Preparatory Project (NPP), a second “span” of the NPOESS “bridge” could easily add climate and land observations with an Operational Land Imager (OLI). OLI technology has been demonstrated by the NASA Earth Orbiter 1 (EO-1) mission. After 4 years in orbit (twice its design life), EO-1 continues to produce data consistent in character with that of Landsat 7 via a sensor a tenth the mass of the Landsat 7 sensor. The reduced mass enables OLI to fit on a second NPP spacecraft with other sensors, including the Visible/Infrared Imager/Radiometer Suite (VIIRS). Coupled with parallel measurements from the NPP, such a second bridge mission could provide global measurements of the complete environment. Climate, atmosphere, land, and ocean would be observed with sufficient spatial scope and detail, frequency, and radiometric fidelity to address all the NOAA mission imperatives. NPOESS will continue the measurements and realize the integrated EOS vision.
VIIRS and OLI would provide complementary observations to complete NOAA’s environmental satellite mission. VIIRS will offer almost daily coverage of Earth’s entire surface in 22 spectral bands at spatial resolution from 400 to 800 m. OLI will
afford less frequent coverage at 30-m spatial resolution in eight spectral bands optimized for vegetation and land. Large-scale change detected through VIIRS can be more closely evaluated, studied, and analyzed using OLI. Furthermore, VIIRS will provide data in spectral bands that can be used to atmospherically correct OLI, while OLI can be used to better calibrate VIIRS to validate climate and environmental data records derived from VIIRS. VIIRS will track dynamic Earth processes such as snow accumulation and melt-back, vegetation green-up and senescence, and fires on an interannual basis. OLI will focus on detailed land cover change, disturbance, and recovery, discerning the forces of change, and discriminating between natural and man-made causes, allowing us to predict key consequences and provide meaningful policy advice. Moreover, VIIRS and OLI synergy has been demonstrated by formation flying of the EOS Terra and Landsat 7 satellites. Terra MODIS and Landsat 7 Enhanced Thematic Mapper plus (ETM+) have proven VIIRS and OLI synergy and demonstrated the future of NPOESS to meet the complete NOAA vision.
NOAA needs to address the need to organize a multidisciplinary team to develop a land, vegetation, and agriculture product set for land management agencies and agricultural applications and for the ecological sciences. NOAA should convene an intergovernmental committee with NASA, the U.S. Department of Agriculture, the Department of the Interior, the EPA, and other interested parties to select operational land vegetation variables for generation from NPOESS, GOES, and other operational systems that will have high utility for land management. Only with direct and ongoing interaction with the land management agencies can the optimum mix of variables, time and space resolutions, variable units, data formats, distribution pipe-lines, and related details be determined. The land management agencies need to dedicate personnel and resources on their end to optimize reception and use of these data sets. The continuous and comprehensive monitoring provided by satellites of the millions of square kilometers of publicly managed land is not available in any other way.