4

Land Cover

INTRODUCTION

Land-cover and land-use changes are major components of national and international global change research programs and are topics of considerable societal relevance. Land cover—the assemblage of vegetation, exposed soil, rock, or water that occupies the land surface —and land use are significant agents of global change, with important influences on biogeochemical cycles, hydrology, and climate. Environmental change includes both anthropogenic change, caused, for example, by demographic or macroeconomic trends, and interannual, decadal, and centennial climatic trends. The environmental data records (EDRs) that specifically address vegetation assessment are the Normalized Difference Vegetation Index (NDVI; a ratio of near-infrared and red reflectance where high index values relate to the absorption of photosynthetically active radiation, a property correlated with biomass and primary production), Land Surface Temperature, Snow Cover and Depth, and Vegetation Index/ Surface Type, ranked in that order by the Land Discipline Panel in the February 1997 NPOESS Climate Measurement Workshop (NOAA, 1997). Additional EDRs related to the assessment of vegetation condition and cover include Soil Moisture, Surface Albedo, and Cloud Cover. Thresholds and objectives for NPOESS land-cover EDRs are shown in Table 4.1.

BASIC SCIENCE ISSUES

Today, land-related climate-change research programs are focusing on determining the impact of land-cover and land-use change on biogeochemical cycling, on coupling land processes into global and regional climate models, and on developing an understanding of the processes that cause change (Janetos et al., 1996; Turner et al., 1995). Underlying climate-related land-cover and land-use research are fundamental questions of natural resource management and sustainable development, and the necessary integration of physical and social sciences (Turner et al., 1994).

A strong policy mandate to better understand global climate change has prioritized research on balancing the carbon budget (USGCRP, 1999). The immediate goal has been to quantify major anthropogenic greenhouse gas source terms affected by the rates of land-cover change in the tropics and the extent and frequency of fires. Understanding net terrestrial ecosystem emissions requires quantification of sinks as well as source terms, which can be done only by application of ecosystem process models. Characterizing how sources and sinks of carbon dioxide (CO2) and other trace gases vary with land cover and land use for the major biogeochemical cycles is clearly a major research challenge. It requires a combination of satellite and airborne remote sensing, in situ measurements, process studies, and numerical modeling (Skole et al., 1997).



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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN 4 Land Cover INTRODUCTION Land-cover and land-use changes are major components of national and international global change research programs and are topics of considerable societal relevance. Land cover—the assemblage of vegetation, exposed soil, rock, or water that occupies the land surface —and land use are significant agents of global change, with important influences on biogeochemical cycles, hydrology, and climate. Environmental change includes both anthropogenic change, caused, for example, by demographic or macroeconomic trends, and interannual, decadal, and centennial climatic trends. The environmental data records (EDRs) that specifically address vegetation assessment are the Normalized Difference Vegetation Index (NDVI; a ratio of near-infrared and red reflectance where high index values relate to the absorption of photosynthetically active radiation, a property correlated with biomass and primary production), Land Surface Temperature, Snow Cover and Depth, and Vegetation Index/ Surface Type, ranked in that order by the Land Discipline Panel in the February 1997 NPOESS Climate Measurement Workshop (NOAA, 1997). Additional EDRs related to the assessment of vegetation condition and cover include Soil Moisture, Surface Albedo, and Cloud Cover. Thresholds and objectives for NPOESS land-cover EDRs are shown in Table 4.1. BASIC SCIENCE ISSUES Today, land-related climate-change research programs are focusing on determining the impact of land-cover and land-use change on biogeochemical cycling, on coupling land processes into global and regional climate models, and on developing an understanding of the processes that cause change (Janetos et al., 1996; Turner et al., 1995). Underlying climate-related land-cover and land-use research are fundamental questions of natural resource management and sustainable development, and the necessary integration of physical and social sciences (Turner et al., 1994). A strong policy mandate to better understand global climate change has prioritized research on balancing the carbon budget (USGCRP, 1999). The immediate goal has been to quantify major anthropogenic greenhouse gas source terms affected by the rates of land-cover change in the tropics and the extent and frequency of fires. Understanding net terrestrial ecosystem emissions requires quantification of sinks as well as source terms, which can be done only by application of ecosystem process models. Characterizing how sources and sinks of carbon dioxide (CO2) and other trace gases vary with land cover and land use for the major biogeochemical cycles is clearly a major research challenge. It requires a combination of satellite and airborne remote sensing, in situ measurements, process studies, and numerical modeling (Skole et al., 1997).

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN TABLE 4.1 Planned NPOESS Land-Cover Environmental Data Records Environmental Data Record System Capability Threshold Objective Normalized Difference Vegetation Index (NDVI) Horizontal resolution Mapping accuracy Measurement range Measurement precision Measurement accuracy Refresh Long-term stability 4 km 2 km −1 to +1 0.04 NDVI ±0.05 NDVI 24 h 0.04 NDVI 1 km 0.5 km 0.01 ±0.01 2× per day (9:30 a.m., 1:30 p.m.) Snow Cover and Depth Sensing depth Horizontal resolution Vertical sampling interval Mapping accuracy Measurement accuracy Refresh Long-term stability 0-50 cm 25 km >10 cm 4 km ±10% clear /±20% cloudy 12 h 10% regional / 2% continental 0-1 m 1 km >5, 10, 20, 30, 50, 100 cm 0.5 km ±30% snow depth 2× per day (5:30 a.m., 1:00 p.m.) 5% regional / 1% continental Land Surface Temperature Horizontal resolution Mapping accuracy Measurement range Measurement precision Measurement accuracy Refresh 30 km cloudy /4 km clear 2 km −90 to 70 °C 0.1 °C Clear ±2.8 °C Clear: 6 h 12.5 cloudy /1 km clear 0.5 km 0.025 °C ±1 °C 4 h Vegetation Index/ Surface Type Horizontal resolution Mapping accuracy Measurement range Measurement accuracy Refresh 4 km global / 4 km regional 2 km 21 types 70% correct 1× per year 1 km global / 0.25 km regional 1 km 0-100% vegetation + 21 types 90% 4× per year Soil Moisturea Sensing depth Horizontal resolution Vertical sampling Mapping accuracy Measurement accuracy Refresh Thermal IR, 1 cm 1 km 1 cm 0.5 km ±10% of total volume 2× per day (daytime) Microwave, 0-5 cm 10 km 5 cm 5 km ±10% of total volume Every other day aFor soil moisture, “Thermal IR” replaces “Threshold,” and “Microwave” replaces “Objective,” as explained in NOAA (1997) p. 46. SOURCE: Extracted from NOAA (1997). In general, land use is harder to quantify from space than land cover, though certain types and intensities of land use can be determined directly or indirectly. Time-series satellite data are used to provide a temporal record of changes or trends in these characteristics and the underpinning for remotely sensed land-cover research. The remotely sensed data can be used independently, combined with ancillary or in situ data, or used to parameterize or validate process models. The different model types include soil vegetation atmosphere transfer (SVAT) models, ecosystem process models, vegetation canopy structure models, land-use models, and integrated assessment models.

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN FUTURE DIRECTIONS Global Biogeochemical Cycles The recent ecological emphasis of the U.S. Global Change Research Program (USGCRP) has focused on understanding the global carbon cycle and its impacts on climate and ecosystems. Discussions of biogeochemical cycling have focused largely on its relation to atmospheric CO2 and the potential for biological fixation of carbon. Research priorities may shift as awareness increases that human effects on the nitrogen cycle, driven primarily by use of fossil fuels and fertilizers at a rate approximating the natural biological fixation of nitrogen (Galloway et al., 1995; Howarth et al., 1996; Vitousek et al., 1997), may cause more serious environmental problems over a shorter time than the direct effects of increased atmospheric CO2. Anthropogenically driven changes are also increasing for other biogeochemical cycles, for example, the phosphorus cycle, which may lead to potentially significant global impacts at slightly longer time horizons. These issues suggest that there will be greater scientific emphasis on observing local to regional biogeochemical impacts of global change and developing techniques for mitigation and improved land management. It is likely that future research will focus more attention on the near-term impacts (intra-annual to decadal time periods) of climate change on regional ecosystems and how they affect the ability to provide goods and services for the growing human population, including management for control of atmospheric trace gas concentrations. Understanding the changing patterns of carbon sequestration and emissions demands better understanding of the scaling relationships between the age and structure of plant stands and regional climate processes, requiring better-resolved observations and models. Extreme Climate Disturbances Despite the rapid changes in land use; fragmentation of landscapes; pollution and contamination; and changes in biodiversity caused by human activities, there is little understanding about how these impacts feed back on the climate, biological, or hydrological systems. Over the next few decades the environmental consequences of anthropogenic effects may be greater than those directly attributable to increasing concentrations of atmospheric carbon. One of the major scientific challenges to understanding and predicting the consequences of climate change on biogeochemical cycling is how to integrate land-use change given the complex interrelated temporal and spatial dynamics (NRC, 1994). These issues drive the need for improved understanding of regional climate responses, which cannot be resolved without experimental and observational studies addressing the underlying interacting time and space scales. Ecological science must develop more realistic ecosystem models to predict the consequences of changing land cover on processes. This emphasis will require direct measurements of ecosystem composition; its vertical and horizontal structures for canopy height, biomass, and surface roughness; and more detailed information on phenology—including plant litter, allocation to above- and below-ground plant components, and turnover rates. Biodiversity Large changes in biodiversity and loss of habitat are among the most obvious impacts of human activity on global ecosystems. Although global in extent, these impacts are expressed locally due to shifting patterns of land use, introduction of invasive nonnative species, and extinction(s) of local populations and species. If current trends continue or accelerate with growing human population density and demand for environmental goods and services, the ecosystems of the next century will become increasingly homogeneous and species richness will decline. However, it is recognized that some ecosystems may manifest more transient local heterogeneity. The interactions between climate and land use affect the structure and function of ecosystems, which will drive changes in net primary productivity and net ecosystem productivity. Although changes in trophic food webs, such as removal of herbivores or predators, have been shown to cause substantial alterations in ecosystem structure

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN and function (Tilman and Downing, 1994; Tilman et al., 1997; Wedin and Tilman, 1996), no ecosystem theory predicts which species, species guilds, or other structural descriptors will be essential to maintaining ecosystem function and services. At present it is not possible to predict long-term impacts on ecosystem functioning, to know which biological components are essential for sustainability, or to develop coherent management strategies to restore, mitigate, or enhance the potential sustainability of global ecosystems. Integrated ecosystem models based on new theory are needed. Similarly integrated assessment models (IAMs) will have to be developed to predict economic and societal impacts of global change over a range of land-use practices. Models must be applicable over a range of time and space scales to improve prediction and address questions of sustainability. CURRENT SATELLITE SAMPLING STRATEGIES The satellite data on land use require a range of sampling strategies. Periodic sampling several times per year at high spatial resolutions (10 m to 100 m) is needed to quantify spatial change, and long-term near-daily monitoring at moderate resolutions (100 m to 4 km) is needed to characterize land cover and detect changes. Long-term measurements spanning decades are an integral part of the observation strategy for detecting and monitoring land-cover changes. Short-term observations over 1 or 2 years can be used to understand specific processes or test new technologies. Land-cover classifications (Anderson et al., 1976) are made at high resolution, preferably using multispectral data obtained at a time optimal for discrimination. Depending on the complexity, more than one image may be used during the annual cycle to improve discrimination or in hierarchical time series (DeFries et al., 1995; Running et al., 1995). Maps of areal extent of land cover can quantify the degree of ecosystem fragmentation (Skole and Tucker, 1993). Data from successive years are used to quantify land-cover change and to characterize types of land use. At moderate to coarse resolution, daily data can characterize vegetation phenology. These temporal vegetation patterns may be used to discriminate among vegetation types (DeFries and Townshend, 1994; Laporte et al., 1995). The requirements for global land-cover characterization have been well articulated in the literature (Townshend et al., 1994). Various approaches can be used for time-series land-cover classification. Daily data at moderate resolutions can detect change where spatial changes are large, such as burn scars from savannah or boreal fires (Justice et al., 1993; Roy et al., 1999; Kasischke and French, 1995). 1 Very high spatial resolution data (defined as having a spatial resolution of less than 20 m) can be used to (1) characterize species composition and disturbance regimes such as insect infestations, disease, or environmental stress patterns; (2) quantify small changes in land cover; and (3) identify land-use types, such as grazing, selective logging, or mechanized farming. These data provide important information for resolving ambiguities in coarse-resolution satellite data, for addressing questions of scaling, and for monitoring carbon management. Currently such very-high-spatial-resolution satellite coverage is limited to the Russian KVR-1000 panchromatic band. The methods adopted for use with these data are derived from standard air-photo interpretation. Securing cloud-free imagery is an overarching requirement for optical sensing systems for land-cover research. This often requires a high number of data acquisitions. Some areas are consistently cloudy and optical data are extremely difficult to obtain, sometimes even over a period of years. For such areas, microwave systems provide a marked advantage. CURRENT OBSERVATION SYSTEMS The Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) multitemporal data, used extensively for land-cover classification and characterization since 1981 (Justice et al., 1985; Tucker et 1   More recent literature, cited further on in the chapter, can be found, for example, in the September 1999 issue of Photogrammetric Engineering and Remote Sensing.

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN al., 1985), have been used to monitor the expansion and contraction of desert margins (Tucker et al., 1994) and changes in the length of the boreal growing season (Myneni et al., 1997a). Yet development of a consistent data set for global land-cover classification has until recently been largely inadequate (DeFries and Townshend, 1994). NASA has supported two major initiatives to develop reprocessing of the GAC data (James and Kalluri, 1994). More recently, global 1 km AVHRR data have been collected and formed into a multipurpose data set that has already been used to derive global fields of land cover (Townshend et al., 1994; Eidenshink and Faundeen, 1994; Loveland and Belward, 1997; Belward et al., 1999). Exploration into using Scanning Multichannel Microwave Radiometer (SMMR) data (25 km) demonstrated the potential use of time-series coarse-resolution microwave data for terrestrial studies (Choudhury, 1989). A global 1 km AVHRR database was developed through the International Geosphere-Biosphere Program (IGBP) to permit improved land-cover mapping (Eidenshink and Faundeen, 1994). The same database can be used to map active fires (Justice et al., 1996). New moderate-resolution sensing systems have been built that improve on the AVHRR record for land-remote sensing (nominal resolution of 1 km), such as the European Along Track Scanning Radiometer (ATSR), Systeme Pour l' Observation de la Terre (SPOT), and SeaWiFS. High spatial-resolution multispectral data have been available since 1972 through the Landsat program. The Landsat system has evolved technologically from the Multispectral Scanner (MSS) to the Thematic Mapper (TM). Landsat data were commercialized in the mid-1980s and data were acquired by EOSAT Corporation, based largely on customer requests. As a result, the global coverage is patchy, and data acquired by foreign ground stations are necessary to improve historical coverage. Landsat data have been the primary source for land-cover research at high spatial resolution, but the cost of commercialized Landsat data has been prohibitive for the research community. Until NASA began the Landsat Data Collection program to subsidize data purchase, researchers were not able to realize the scientific potential of these data. With the applications potential for natural resource management and mapping, the French Centre National d'Etudes Spatiales (CNES) launched the SPOT system in the mid-1980s. A patchy historical global archive also exists for these data at SPOT IMAGE, a leading supplier of geographic information from satellites, and at various foreign ground stations. SPOT IMAGE also provides a 10-m panchromatic band to enhance its 20-m multispectral capability for land-cover mapping. More recently, the Indian Space Agency launched the Indian Remote Sensing (IRS) series of satellites, providing an additional source of high-resolution data. These data are commercially available from Space Imaging/EOSAT Corporation; however, data coverage remains incomplete. Access to digital very-high-spatial-resolution data has traditionally been restricted to the surveillance community. Since the 1980s, digitized commercial high-resolution Russian KVR-1000 photographs (2 to 3 m) have been available for selected locations. Recent commercial initiatives have expanded the supply of declassified data to a broader community. These data appear to have considerable potential for ecosystem characterization such as community structure, tree mortality, and land-use mapping. High-temporal-frequency data are available from geostationary satellites such as the Geostationary Operational Environmental Satellite (GOES). Such data have generally been considered too coarse in their spatial and spectral resolution for land-cover studies; however, middle-infrared subpixel fire detection has been used to sample the diurnal cycle of fire activity (Prins and Menzel, 1996). The GOES 8/9 visible and reflected infrared band is acquired at 0.9 km resolution and can be analyzed for subscenes at that resolution. Microwave systems have been strongly supported by the European and the Japanese space agencies. The Earth Resources Satellite (ERS) and Japan's Earth Resources Satellite (JERS) high-resolution images (100 m and 12.5 m, respectively) can augment land-cover maps from optical systems. For example, JERS data are used to map inundated forests in the tropics (Saatchi et al., 1997). Multiband microwave data from the space shuttle have demonstrated the utility of synthetic aperture radar (SAR) for vegetation mapping, biomass estimation, and characterization of flooding, ice, and snow (Saatchi and Rignot, 1997; Sun and Ranson, 1998). The variable spatial resolution data from the Canadian Radarsat are now commercially available (Luscombe et al., 1993). Aircraft data play an important role in the land-cover research program, providing a testbed for developing instruments and algorithms. Airborne simulators are available for most spaceborne sensors, including multispectral, hyperspectral, thermal infrared, radar, and microwave sensors. NASA airborne sensors test new technologies, for example, the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS), a 224-band hyperspectral sensor; the

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN MODIS Airborne Simulator (MAS) and a multiband optical and thermal infrared sensor (MASTER); the Airborne Synthetic Aperture Radar (AirSAR), a multiband quad-polarized radar sensor; the Airborne Multi-angle Imaging Spectroradiometer (AIRMISR), a multiband, multiview-angle sensor for characterizing the radiative properties of Earth's atmosphere and land surfaces; and the Vegetation Canopy Lidar (VCL), a simulator to characterize the canopy structure. As part of a balanced research program, NASA has invested in a number of major field campaigns aimed at improving understanding of critical land-atmosphere processes. Examples include the First ISLSCP Field Experiment (FIFE), Boreal Ecosystem-Atmosphere Study (BOREAS), Niger Hydrological-Atmospheric Pilot Experiment (HAPEX), and the Amazon Large-scale Biosphere Atmosphere (LBA) experiments, targeting specific science questions (Sellers and Hall, 1992; Sellers et al., 1996, 1997; Prince et al., 1995). Both NOAA and NASA support hydrological research under the Global Energy and Water Cycle Experiment Continental-scale International Project (GEWEX GCIP) campaign in the United States, which includes a land-surface research component (IGPO, 1994). The cost of funding comprehensive field campaigns has limited the effort largely to the examples cited above; however, such experiments are essential to scientific advances. Ground data are also collected to validate satellite data products and provide vicarious calibration of satellite instruments (Justice et al., 1998a). A noteworthy development is the Aeronet network of Sun photometers used to characterize atmospheric optical depth and to validate atmospheric correction algorithms for multiple land-imaging satellites (Vermote et al., 1997). As recognition of the need for in situ observation networks for field testing and validation of satellite data products has increased, data collection at long-term ecological and environmental research sites is becoming integrated with the satellite data in climate-related monitoring programs (Skole et al., 1997). Examples of these sites include the national and international Long-Term Ecological Research sites, the Ameriflux and Euroflux sites (Baldocchi et al., 1996), national parks, and preserves. These sites provide a globally distributed resource for evaluating scientific data products. Lack of data access has been an impediment to advancing climate-related land cover and land-use research. The research community has had to rely on buying low-level data products (e.g., Level 1B) from centralized archives or arranging access to higher-level products through individual principal investigators (PIs), with varying degrees of success (Justice and Townshend, 1994). The Earth Observing System (EOS) Pathfinder program marked a watershed in data availability of key AVHRR and Landsat data for the land-cover and land-use community (Maiden and Greco, 1994; Justice et al., 1995). Internationally, the IGBP data and information system (DIS) has identified some of the science requirements and coordinated the international community to help generate critical land-research data sets at the global scale, such as land cover, fire, topography, Digital Elevation Model (DEM), and gross primary productivity (GPP). Similarly, the International Satellite Land Surface Climatology Project (ISLSCP) developed a CD-ROM of multisource data sets suited to modeling land-atmosphere interactions. OBSERVING STRATEGIES IPO/NPOESS Plans In the next 5 years, there will be significant improvements in the availability of satellite data for land-cover studies (Figure 4.1). The AVHRR long-term record will continue with the improved AVHRR 3 on NOAA K, L, and M, providing a global 1-km data set. The VIIRS EDR objectives for land cover appear to be based on today's AVHRR capability rather than building on the capabilities of the sensors of the coming decade. The VIIRS will replace the current AVHRR as the moderate-resolution imager. NASA's Plans The EOS AM platform should provide a marked improvement in moderate-resolution land remote sensing and spectral resolution (Running et al., 1994). The MODIS sensor will provide improvements over AVHRR in its spectral bandwidth, instrument calibration, signal-to-noise ratio, locational accuracy, and spatial resolution (Barnes et al., 1998). The availability of near-daily 500-m and 250-m MODIS data will lead to major advances for land-

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN cover characterization and will mark a new era in land science and applications (Townshend and Justice, 1990). The fire detection and mapping capability of MODIS will be significantly better than that of AVHRR, which saturates at low fire temperatures, particularly after both morning and afternoon MODIS instruments are in orbit (Justice et al., 1995; Kaufman et al., 1998). New MODIS algorithms for vegetation indices, such as leaf area index/fraction of absorbed photosynthetically active radiation (LAI/FPAR), net primary productivity, bidirectional reflectance distribution function/albedo, surface temperature, snow cover, fire, land cover and land-cover change, will provide the science community a new suite of high-priority science data products (Justice et al., 1998b). The Multi-angle Imaging Spectroradiometer (MISR) could also contribute to improvements in the measurement of these canopy properties. FIGURE 4.1 Time line of planned satellite observations for land-cover and land-use research. Acronyms are defined in Appendix B. The ASTER instrument will provide improved multispectral optical and thermal data at high spatial resolution for land studies (Yamaguchi et al., 1998). The MISR instrument will provide new data to study surface directional reflectance properties with the potential for improved characterization of vegetation structure and atmospheric composition (Diner et al., 1998). The planned launch of the MODIS PM in 2001 will continue the MODIS data record and provide diurnal sampling and increased opportunities for cloud-free observation. The launch of Landsat 7 and the Enhanced Thematic Mapper (ETM+) will continue the high-resolution data record and provide the next step in product continuity with technological evolution (Irons et al., 1996). In addition to better instrument performance and a new 15-m panchromatic sharpening band, Landsat 7 will for the first time have a global data acquisition strategy driven by science requirements and a major increase in data availability (Goward and Williams, 1997).

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN In addition to continuing and enhancing the long-term data records, some of NASA's exploratory missions target the land-cover research community. As the first of its Earth System Science Pathfinder (ESSP) missions, NASA's Vegetation Canopy Lidar (VCL) will provide improved characterization of vegetation canopy structure and offers considerable potential for detecting ecosystem disturbance, such as damage from severe storms. LightSAR is a proposed lightweight synthetic aperture imaging radar satellite that will use advanced technologies for research, land management, and emergency response applications (NRC, 1998). LightSAR will provide all-weather, day-night, multiband, dual polarization images of most of Earth. The proposed interferometric configuration would allow development of high-resolution digital elevation maps. The centerpiece of the Earth Observer-1 (EO-1) satellite in the New Millennium Program is the Advanced Land Imager (ALI), which will provide paired scene comparisons between the ALI and ETM+ to validate the suitability of the multispectral capability of the ALI. ALI incorporates alternative and innovative approaches to future land imaging, including a hyperspectral imaging sensor to assess the feasibility of synthesizing Landsat bands. This will open the door for advanced imaging information products for characterizing Earth's surface. Depending on the success of this mission, these technologies could provide the basis for a new generation of Landsat instruments. International and Commercial Plans At the international scale, plans exist for new sensors that will provide data relevant to the land-cover community, for example the Japanese Global Imager (GLI) and the European Medium Resolution Imaging Spectrometer (MERIS), to augment the moderate-resolution capability. Plans are also under way for in situ data collection associated with the land-cover objectives. As part of its series of campaigns, NASA is investing significant resources in the Large Scale Biosphere Atmospheric Experiment in the Amazon. A smaller field campaign operating through the same period will be the Southern Africa Fires Atmosphere Research Initiative (SAFARI). In addition, a new initiative is being developed for the validation of NASA EOS data products. Plans for the EOS land-cover community have been summarized elsewhere (Justice et al., 1998b) and include a core-test-site in situ data collection program. These sites were developed from the hierarchical measurement suite proposed by the Terrestrial Observation Panel for Climate (GCOS, 1997) and provide a potential source of long-term in situ measurements. These examples are meant to be illustrative, but not encyclopedic, of the international efforts in this area. A new multiagency national planning initiative is developing around a series of tower-based flux measurements (Baldocchi et al., 1996). The Ameriflux activity contributes to the larger international FLUXNET program aimed at producing new data sets on gas and water fluxes to provide a better understanding of primary production and land atmosphere exchanges. INTERNATIONAL ASPECTS OF LAND-COVER OBSERVATION Given the lack of redundancy in the planned observing systems at the national level and the plans for complementary instruments by the international community, international collaboration may be a means of reducing risk. Collaborative activities, such as the planned addition of AVHRR and possibly VIIRS instruments on the EUMETSAT METOP series, are good examples of the mutual benefits of collaboration. International coordination on different aspects of research is continuing through international partner programs such as the IGBP International Human Dimensions Programme on Global Environmental Change (IHDP) and the World Climate Research Program (WCRP). In particular, significant progress has been made by IGBP-DIS in implementing land-related global data coordination initiatives (Townshend et al., 1994; Estes et al., 1999), the IGBP/IHDP Land-Use and Land-Cover Change (LUCC) program in identifying the leading land-cover and land-use research questions (Turner et al., 1995), IGBP-GAIM in a terrestrial model intercomparison, and the Global Energy and Water Cycle Experiment Project for Intercomparision of Land-Surface Parameterization Schemes (GEWEX PILPS) in comparing land-surface parameterizations of different general circulation models (GCMs) (Yang et al., 1995).

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN The International Global Observing Strategy (IGOS) initiative has provided a forum for developing the broader concepts for global observing systems and has encouraged the definition of science data requirements. As part of the Global Climate Observing System, the Terrestrial Observation Panel for Climate (TOPC) has provided the design of a hierarchical terrestrial observation network (Cihlar, 1997) and has recently started to coordinate a global net primary productivity activity. The Global Terrestrial Observing System (GTOS) has been very slow in developing, and the challenge to define the requirements for international terrestrial in situ networks remains. The Committee on Earth Observing Satellites (CEOS) provides a forum for the space agencies to coordinate their satellite programs. The CEOS Calibration/Validation working group provides a potential forum for coordinating the in situ networks needed to supplement the satellite programs. Recently CEOS has sponsored the development of pilot activities for the global observing systems. For the land-cover community, the implementation of the Global Observation of Forest Cover (GOFC) pilot study, led by the Canadian Space Agency, will have important implications for long-term land-cover monitoring for use in both science and applications. WHAT IS NEEDED IN ADDITION TO WHAT IS PLANNED There is a mismatch between what is needed for long-term monitoring of land cover and what is planned for NPOESS. (See Box 4.1.) In general, the land-cover EDRs (see Table 4.1) fall considerably short in specifying the long-term land data needed for climate research, especially when compared with the minimum set of terrestrial variables identified by Cihlar (1997). The land EDRs are poorly specified, and it is hard to determine the rationale for their selection and the specifications provided. The EDRs reflect a continuation of current or planned measurements rather than a set of records designed to meet climate-related research needs a decade or more from now. For the EDRs targeting the land community engaged in climate change research, the EDR objectives can be considered mandatory rather than optional, and achieving only the specified thresholds would be unacceptable. For the currently specified land EDRs, the thresholds and objectives should be revisited. For example, the Vegetation Index/Surface Type classes should be reconsidered, because neither the 21 classes nor the associated system capabilities identified make sense in a climate measurement context. The specified levels of spatial resolution, mapping accuracy, and measurement precision need clarification or justification because, for example, the accuracy of the measurements will depend on the spectral bands chosen for the NPOESS instrument, but these are not currently specified. A better balance is also required between continued and reliable long-term measurements and new experimental measurements. The current plans for long-term measurements could result in serious gaps and, in one case, a termination of the data record. There is little redundancy in the observation system at the national scale; a mission failure will cause major gaps in the data record. It is surprising that relatively little effort is being made by the agencies to develop an international observation strategy to alleviate this risk. Given recent experiences with mission failures, this approach appears to involve a very high risk. The committee is concerned because possible data gaps based on current plans could be filled if international cooperative plans were put in place. A combination of programs is needed both to process and analyze data from the existing sensing systems and to support cutting-edge research that will lead to improved sensors and analysis and reduced uncertainty in climate model predictions. There should also be a clear strategy for developing tested experimental measurements into an operational suite. As part of this strategy, mechanisms should be developed and applied for moving successful technology and measurements from experimental programs into operational programs. The programs should strengthen ongoing observation programs and add observations. Current NPOESS planning appears to recognize the requirement for meeting climate data needs, but no resources are included to accommodate these needs. Another factor to be considered in planning for new sensor missions is the uncertainty of the implications of the new national policy restricting NASA's selection of missions that may compete with private-sector investment in commercial space activities. Currently, the policy has restricted planning for hyperspectral sensors to follow the EO-1 testbed hyperspectral sensors because of a possible conflict with commercialization of the Department of Defense's (DOD's) Warfighter and Naval Earth Map Observer (NEMO) sensors. NASA has initiated discussions with DOD to evaluate the potential for these missions and technologies to meet Earth science requirements. In addition to agreements to purchase data to fill science needs, the proposed sensors must meet data quality standards, provide access to critical land-cover data sets, and ensure the long-term consistency of data acquisition plans and the timely availability of data. The committee is concerned that the fundamental mission requirements of these three groups—DOD, NASA, and commercial vendors—may conflict irreconcilably. The committee anticipates that the policy may lead to stopping or delaying the development of other sensors (e.g., thermal and radar) if commercial vendors have announced plans to build and launch satellites with similar or overlapping characteristics.

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN BOX 4.1 Summary and Findings Land-cover issues in the integration of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and Earth Observing System (EOS) have several implications for the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), and the Integrated Program Office (IPO). There is serious concern that the NPOESS sensor will not meet the need for continuation of the long-term Advanced Very High Resolution Radiometer (AVHRR) and Landsat data records. If NPOESS is to be the continuation of long-term measurements for both the operational and science communities, the IPO should provide the planned instrument characteristics and calibration strategy for the VIIRS instrument as soon as possible. This is essential for the utility of the VIIRS data to be evaluated by the science community. For the land data products, the system capabilities must be driven by the science objectives rather than the threshold environmental data records (EDRs). Based on the current documentation, the VIIRS instrument may have to be augmented in the middle-infrared so that it can generate data products for active wildfires and burned areas at a spatial resolution sufficient to detect change. Under current NPOESS planning, the land-cover climate research requirements for high-spatial-resolution data will not be met. This is considered a major omission for the land community engaged in climate change research. Long-term high-spatial-resolution measurements are essential for land-cover and land-use global change research. NASA may have to lead development of a high-resolution sensor and should explore a moderate-resolution imager mission (2004 to 2009) to bridge the data gap between the Moderate-resolution Imaging Spectroradiometer (MODIS) measurements and their continuation by the NPOESS VIIRS. Collocating a high-resolution imager with VIIRS is highly desirable. In the opinion of the committee, NOAA should continue the AVHRR time series through K, L, M, and N. A 2-year overlap strategy is needed with the MODIS and NPOESS data records. There is a need to strengthen the vicarious calibration program for the red and near-infrared channels. Reprocessing of the long-term AVHRR record is needed to provide consistent multiyear data products that incorporate recent improvements in calibration and atmospheric correction and to continue the long-term data record. This could best be implemented as part of a continued NASA/NOAA data pathfinder program. The characterization of land cover derived from the multispectral channels on Landsat TM, MODIS, and the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) will not be possible, or is uncertain, under the EDR descriptions. There is an urgent need for NOAA to clarify its role and commitment to the Landsat program beyond Landsat 7. For Landsat 7 and future high-resolution missions, there is also a critical need to develop real partnerships with international ground stations to augment the U.S. global acquisition strategy and secure arrangements for data provision. In the next few years, NASA will have to demonstrate the science utility of the new EOS land instruments (MODIS, the Multi-angle Imaging Spectrometer (MISR), and ASTER) and its other near-term missions (Vegetation Canopy Lidar (VCL), EO-1, and LightSAR). This will aid in identifying new measurements that might be integrated into long-term operational systems. A mechanism will then be necessary to implement that integration. The previous Operational Satellite Improvement Program (OSIP) structure may have to be revisited. NASA should support the remote-sensing science needed to define the next generation of exploratory instruments that address the emerging key land science questions in the 2004 to 2009 period. NASA should plan to fill the gap in the long-term AM time series from the post-2004 period, prior to the launch of NPOESS (2009), and determine its role with respect to the continuation of the high-resolution record beyond Landsat 7.

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN Although many commercial sensors have been announced (Stoney, 1997), not all of these are likely to be built, and some companies may cease operations if they are not economically viable. The fates of the Early Bird, Lewis, and Clark missions illustrate some of these problems. The implications of reliance on commercial-sector data sources for essential information needed for government programs and policy decisions require critical evaluation and development of a strategy for addressing critical data gaps. Additional Long-Term Measurement Needs Moderate Resolution The VIIRS EDRs fall short of what will be needed for climate-related land-cover and land-use studies at the end of the first decade of this new century. Important data products such as LAI/FPAR, fire, net primary productivity, and land surface reflectance have been developed for near-term missions but are missing from VIIRS. The approach of providing data record requirements rather than instrument specifications to instrument designers makes it unclear whether such products could be generated once sensor packages are selected. There is no unique means of correlating instrument specifications and data record specifications; that is, there are many ways to deliver data that meet a particular requirement. There are often significant differences in other aspects of data quality that are not covered in the specifications. Scientific oversight is required at every step, not just in developing data product requirements. With the demise of the EOS second series, the 20-year data record initially intended for the MODIS will stop with the PM mission. Assuming that sufficient characteristics of the MODIS instrument can be built into the VIIRS to meet the climate community's needs, the data record could be continued by NPOESS. However, there is likely to be a gap from the end of the MODIS AM data record (ca. 2004) to the first VIIRS launch in 2009. One highly desirable solution, in the committee 's opinion, is for NASA to work with the Integrated Program Office (IPO) to develop an Advanced Global Imager for launch in the 2004 time frame which would continue many of the measurements made by MODIS and which could be extended later by VIIRS. Such a mission would provide a critical bridge between EOS and NPOESS measurements. Through its role in the IPO, NASA is currently examining the level of augmentation with respect to engineering and instrument characterization that would be needed to accommodate its requirements. An investment by NASA to upgrade the VIIRS to permit generation of additional data products would benefit the global change science community. This would be preferable to and presumably cheaper than NASA developing its own instrument bridging MODIS and VIIRS, with no data continuity with VIIRS. High Resolution: Optical The lack of clear plans for long-term high-resolution optical measurements beyond Landsat 7 is perhaps the most critical gap in the land-cover and land-use part of the U.S. climate observation program. Given the increased focus on regional-scale land studies and the need for carbon monitoring, the Landsat high-resolution data record should be continued. The global change land-cover community considers continuation of this data collection essential for evaluating models and addressing scaling issues for the global data sets. The future of the Landsat program after Landsat 7 is uncertain, owing to the 1992 Title IV law requiring possible commercialization of this program or creating an international consortium for a successor sensor, and the large number of possible Landsat-like sensors. Although the Landsat program has been viewed as successful over its 25-year history and the value in maintaining the continuity of the data record is widely accepted, there is no current agreement on how to

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN develop this next-generation sensor to meet the requirements for commercialization. For Landsat 8 to meet a 2004 launch, construction will have to begin by 2001, and these issues must be resolved by then. A high-resolution imager could occupy space currently available on the NPOESS platform with VIIRS, creating a very attractive combination for land-cover science. Simultaneous acquisition would enable the atmospheric bands of the VIIRS to be used for atmospheric correction of the high-resolution imager, which will clearly be a requirement for a Landsat follow-on. Experimental Missions with Associated Rationales Hyperspectral and Very-High-Spatial-Resolution Systems By 2000, 30 proposed satellites will be capable of providing spatial resolutions of 30 m or better (Stoney, 1997). Of these, 14 are planned commercial ventures and have pixel resolutions of 10 m or better; 8 are optical systems, and 2 are radar satellites that will be launched by other governments. The U.S. government will launch the EOS AM-1, two multispectral systems, and three satellites with hyperspectral sensors. Panchromatic data will be available at 1- to 5-m resolution from some commercial vendors. None of the four U.S. commercial satellites will have the shortwave infrared or thermal channels of Landsat TM. Four of the government satellites will have only panchromatic bands and will not be capable of multispectral imaging. France, India, and (jointly) China and Brazil will have satellites with some Landsat-like characteristics, but because of differences in sensor characteristics and spatial resolution, it is uncertain whether they will function as replacements for Landsat. Despite the general advantages of international cooperation, the committee does have some concerns about the practicality of relying on foreign governments to supply essential satellite information, especially on a long-term basis, given that economic or national security issues could block data acquisition or distribution of data to the United States. If all of these satellites become available, land-cover sites could be revisited at nearly 2-day intervals using data from a combination of sensors. Because of the cost of data acquisition and archiving, commercial satellite vendors have not been able to provide the types of postevent time-series data required for characterizing land-cover change. Therefore, if commercial sensors are to be the backbone in providing very-high-spatial-resolution data for the land remote-sensing community, it is essential to develop data purchase agreements that apply throughout the sensor lifetime, with the associated science acquisition strategy. Purchase agreements will have to include raw data so that calibrations can ensure consistency over time and across different sensor types. Two NASA sensors, two proposed commercial DOD hyperspectral satellite sensors, and one commercial Australian hyperspectral sensor are planned for launch in the 2000 time frame. The proposed NASA sensors will be part of the sensor packages on NASA's EO-1 New Millennium mission; the commercially built sensors to be launched include the dual-use U.S. Air Force Warfighter I (built by Orbital Sciences Corporation for the OrbView-4 satellite), the U.S. Naval Research Laboratory 's NEMO (built by Space Technology Development Corporation), and the Australian AIRES sensor. Each of these has hyperspectral capability (about 200 narrow wavelength bands) over the 400- to 2,500-nm region and high-spatial-resolution pixels (8 to 30 m). The Warfighter sensor has 80 medium wavelength infrared (MWIR) bands, which could be useful for wildfire monitoring. The commercial rationales for the DOD satellites are identification and mapping of coastal margin and ocean color patterns and land-cover spectral signature recognition. If the data are consistently available over long-term test sites, these sensors would be valuable in developing cross-sensor calibration, improving detection and understanding of seasonal to interannual changes in land cover, and providing key data to test spatial and spectral scaling algorithms. High-Resolution Microwave Both the optical and microwave portions of the spectrum are well suited for use in land-cover classification and estimation of forest biophysical properties. The sensor response in both spectral regions is determined to a large extent by structural attributes of the vegetation cover, differing as a consequence of sensor-specific illumination and viewing geometry. At the microscale, scattering properties are controlled by surface chemistry (i.e.,

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN pigments and water) in the optical regime and by dielectric properties (i.e., liquid water content) in the microwave regime. Hence, optical and microwave (e.g., SAR) data sets are somewhat correlated but provide much complementary information that can be exploited to improve vegetation classification and biophysical data retrievals. Kasischke et al. (1997) reviewed the use of SAR data for land-cover classification and cited 90 percent classification accuracies for both agricultural and forested land cover. These studies commonly optimize classifications for a given airborne or orbital SAR, and comparisons (i.e., frequency and polarization configuration) are complicated by the use of diverse methodologies. Dobson et al. (2000) reported a comparison of SAR configurations for mixed-temperate forests, northern hardwoods, pine plantations, lowland forests, marshes, and prairies in northern Michigan. Shuttle Imaging Radar (SIR-C/X-SAR) polarimetric data at the L- (23 cm) and C-bands (6 cm) and vv-polarized data at the X-band (3 cm) were used to simulate SAR system scenarios representing (1) currently orbiting SAR systems (i.e., ERS-1 with C-band and vv-polarization, JERS-1 with L-band and hh-polarization, and RADARSAT with C-band and hh-polarization); (2) the combination or fusion of these systems; and (3) a suite of future orbital SAR systems under construction or in the design phase (e.g., PALSAR with dual-polarized L-band, ENVISAT with dual-polarized C-band, and LightSAR with L-band polarimetry and possible multifrequency enhancements at the C- or X-bands). A moderate-resolution SAR system capable of repeated coverage is needed as a follow-on mission to EOS for biomass retrieval, vegetation classifications, and mapping vegetation changes (Dobson et al., 1996; Kasischke et al., 1997; Sun and Ranson, 1998). High-Temporal-Resolution Systems Several strategies can be considered to improve the temporal resolution of land observation satellites, including use of high-resolution geostationary satellite data such as the full-spatial-resolution GOES visible and near-infrared (VNIR) image data, use of all-day and night overpasses of the various polar orbiters, or development of lightweight or low-cost constellations of polar-orbiting imaging sensors. There have been very few examples of the use of geostationary data for land studies. CALIBRATION AND VALIDATION AND MISSION OVERLAP STRATEGIES Both technology innovations and the demands of physically based ecosystem models require data calibrated to physical units rather than to digital numbers or radiance units. These models must account for the absorption and scattering properties of the atmosphere and for instrument characteristics and drift. Radiative transfer models must improve characterization of spatially varying atmospheric properties—specifically, aerosols, water vapor, smoke, and dust—to predict surface radiative properties more accurately. The Aeronet network of Sun photometers provides a strong foundation for the in situ component of an aerosol monitoring network, which can also be used for surface reflectance product validation. Calibration and instrument characterization are essential for satellite-based climate measurement systems. Prelaunch instrument characterization, onboard calibration, vicarious calibration, and interinstrument cross-calibration are all critical components of a calibration program. A review of recent instrument specifications and their associated prelaunch characterization testing would help to identify areas of improvement for future systems. A closer connection between desired product characteristics and instrument specifications and tests is needed. New techniques and methods of onboard calibration that do not greatly increase weight and power requirements need to be developed and incorporated into NPOESS. Empirical Corrections Empirical atmospheric correction methods will continue to be integral to deriving surface reflectance and emission characteristics from satellite data. The high spatial resolution of many sensors and orientation and pointing knowledge, combined with location information of field measurements obtained from global positioning system satellites, will make it possible to calibrate sensor output accurately using vicarious methods and to validate specific pixels for specific data products. Consistent and well-registered time-series satellite and field

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN measurements of specific, well-characterized sites are critical to developing an understanding of seasonal and interannual changes in surface conditions and evaluation of land cover. This strategy will require consistent observations, obtained repeatedly, of specific ground targets by multiple Earth-observing satellites. In addition, it requires continued acquisition of the standard in situ ecological data sets that have developed in the major field campaigns. Selecting globally distributed land-cover sites to evaluate ecosystem data products and to establish current vegetation conditions is more difficult than using the bare-earth desert sites often selected for vicarious sensor calibration. Phenological changes and spatial complexity require a significant long-term commitment of resources at test sites. Great strides have been made in identifying and organizing global sites through the EOS Pathfinder program, the IGBP, and national and international long-term ecological programs. The primary limitation in achieving this goal is the uncertainty about institutional commitments to financially support the long-term data acquisition effort and the database infrastructure required for its use. An international initiative to coordinate test site instrumentation and data collection protocols could be envisioned in the framework of the CEOS Calibration/ Validation Working Group. Vicarious Calibration The land-cover science community would benefit considerably from a coordinated, long-term instrument calibration program. A network of calibration sites with regular measurements could serve multiple instruments. Measurements are needed to characterize surface reflectance and emission, as well as the atmosphere over areas equivalent to several satellite footprints, and cross-calibration between in situ and satellite instruments is essential. Calibration sites are needed for both optical and thermal instruments. New initiatives are necessary to develop calibration sites suited to different parts of the spectrum. Instrumentation comparisons and ground and airborne measurement procedures should be developed to allow a distributed approach to vicarious calibration. Similarly, continuous automated vicarious methods need to be developed, building, for example, on procedures developed by Roger and Vermote (1998). Online access to regular community consensus updates on instrument calibration is essential. Overlap and Cross-Sensor Calibrations Since many sensors will be capable of simultaneous or near-simultaneous imaging of the same ground points, more rigorous cross-sensor calibrations and evaluation of consistency of land-cover information derived from these instruments will be obtained. This synergy may require using data products from one sensor as inputs to improve the calibration of other sensors, such as using MISR data to improve atmospheric corrections of MODIS and ASTER data. This will shift the research focus from intercalibration of data from one sensor to intercalibration of data among sensors. An overlap between successive AVHRRs and follow-on missions such as MODIS will be essential for inter-instrument cross-calibration. Optical sensors are limited by cloud cover; therefore, developing and validating techniques to merge or fuse radar and optical data for vegetation assessment are a high priority. The high spatial resolution of LightSAR will contribute to developing this fusion. Based on theory, radar and shortwave reflected infrared bands should probe more deeply into the canopy than visible and near-infrared bands. These differences should be exploited as a basis for increasing the range of information extracted about canopy structure. Commercial Sensors For researchers to obtain commercially retrieved data, mechanisms such as “data buys” should be identified to allow the climate research community to incorporate commercial sensor data into the global database. This is particularly important for consistent access to very-high-spatial-resolution and hyperspectral data over calibration sites and targeted sites as these will be available primarily from commercial sensors. Raw unprocessed data must be purchased from vendors, allowing scientists to use calibration methods consistent with those applied to other

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN sensors. Both onboard and vicarious correction methods are required for sensor calibration and validation strategies. Ground Networks The ground networks for nonsatellite-related data unfortunately are in decline and are not addressed by this report. The IGBP FLUXNET activity and the DOE/NASA AMERIFLUX networks provide encouraging examples of how in situ measurement systems and protocols are coordinated. As new land data products are adopted by the modeling community, increased emphasis on product accuracy is necessary. In situ validation networks developing within the EOS program provide a strong foundation for the correlative measurement program required for product validation. The EOS land community has adopted core land-validation sites representing a range of biomes and atmospheric conditions that must be augmented and strengthened to validate future land-data products. Coordinated and periodic ground-based measurement of such variables as surface reflectance, LAI/FPAR, canopy structure land cover, fire-burned area, and net primary productivity will provide a critical component for assessing product accuracy. A research challenge is to tie measurements to the equivalent satellite products. In particular, continuous tower-based (point) eddy flux measurements will have to be related to satellite and model-derived net primary productivity. Future systems generating higher-order data products such as the VIIRS should include an explicit validation component to enable science users to characterize error budgets in their analysis. Automated and reliable in situ instrumentation is highly desirable. The validation community should continue to develop protocols for collecting data for validation and for instrument calibration that allow a distributed and international validation system to be developed. DATA PROCESSING AND MANAGEMENT Data processing, archiving, and distribution are important components of a land-cover monitoring system. Characterization and monitoring of data quality are essential to the data production chain. Procedures for operational quality assurance associated with land data production should be developed and applied to future data systems. The federation concept for data archiving is being prototyped over the next three years through the Earth System Science Information Partnerships (ESSIPS), which will provide additional and alternative services to those of the EOSDIS Core System (ECS). The ESSIPS will move the community toward a more distributed data system. As part of its current approach, NASA is also involving scientists more closely in the data system design and implementation through what it calls “PI processing,” ensuring greater ownership of the data system and products by the science community. Successive reprocessing should be built into the plans for data management to ensure a consistent data record. Processing of satellite data for land-cover analysis often involves using ancillary products such as digital elevation models and assimilated climate data. Timely provision of these data is an important part of the data chain. Arrangements have to be made for provision and archiving of these data sets for initial processing, and also for reprocessing of these data. THE NECESSARY OBSERVATION STRATEGY A Multisatellite, Multisensor Approach Current methods typically involve analyzing single-sensor data, either as a one-time image or as a multi-temporal data set. Limited access to radar and thermal sensor data has meant that there is little history of combining data from different spectral regions to optimize characterization of land-cover properties. The availability of new sensors will likely place greater emphasis on fusing data using (1) multiple sensors for multiresolution analysis and statistical subsampling approaches or (2) sensor suites, that is, combinations of optical and radar or

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN optical and thermal sensors, that provide collocated and coincident temporal data. Better understanding of the spectral, spatial, and temporal scaling issues and use of high-resolution data as subsampling for moderate-resolution sensors is necessary. The spatial scale of regional land-cover problems requires higher-resolution data than the 1 to 4 km for VIIRS to characterize surface conditions and quantify the rates of land-cover change. A higher spatial scale is essential to understanding global change mechanisms, while scaling studies may reduce uncertainties in interpretation of VIIRS data. Within the next 5 years, national computing capacity is likely to increase to make land parameterization at a 1 km grid feasible. This will drive a demand for collection of moderate-resolution data, e.g., 250 to 500 m. Improved and New Measurements One area where improved resolution is necessary is in the estimation of LAI/FPAR, which will lead to significant improvements in estimates of net primary productivity at midlatitudes and high latitudes. The current emphasis on the use of NDVI has been largely driven by spectral availability of long-term data sets. The limitations of NDVI in certain habitats (very high or very low cover) has resulted in the development of a number of derived indices to improve this product, but no method has been shown to perform better consistently. Improving estimates of vegetation phenology will reduce errors in net primary productivity and net ecosystem productivity. Direct measurement of biomass and vertical and horizontal vegetation structure is also needed to parameterize and validate ecosystem models. NASA EOS sensors may produce new information on canopy water content, separation of photosynthetic pigments, dry plant matter, and soil quality. Canopy water content increases linearly with LAI, greatly increasing the range of sensitivity derived from NDVI measurements (Roberts et al., 1997; Asner et al., 1998). Methods using radiative transfer appear promising (Myneni et al., 1997b). Separation of photosynthetic pigments (Penuelas et al., 1995; Gamon et al., 1997) could eliminate much of the error in modeled net primary productivity estimates and significantly reduce uncertainties in biogeochemical budgets and estimates of evapotranspiration. Improved estimates of dry plant matter greatly reduce errors in estimates of surface albedo, soil processes, erosion, and wildfire hazard. This information would improve wildfire assessments (Ustin et al., 1998; Roberts et al., 1998) and estimates of biomass and decomposition. Monitoring land-cover change, the type and intensity of changes, and evidence of land degradation will benefit from new vegetation indices using other spectral regions. Change-detection accuracy will improve with the use of calibrated, atmospherically corrected surface reflectance data. Precise multitemporal registration of time-series data is essential. Issues related to understanding biodiversity changes, species invasions, and the changing distribution of tree ages in forests, from older to younger stands, require new types of data analysis. Both LightSAR and VCL promise to contribute to this assessment, as do methods derived from hyperspectral and very-high-spatial-resolution sensors. New methods that include use of neural nets, wavelets, mixture and multiple end-member models, and inverse canopy modeling developed for high-spatial-resolution mapping of vegetation types need more critical evaluation over a wide variety of global biomes. While changes in large patterns of land cover resulting from land use and wildfires will be identifiable using VIIRS data specified at its current land-cover EDR objective of 250 m, it is certain that higher-spatial-resolution sensors (about 20 m) will also be needed to provide direct quantification of land use, types, and intensity of use and land degradation. The VIIRS EDR for land classification will be inadequate for this assessment. AREAS FOR RESEARCH AND DEVELOPMENT Among the areas associated with satellite observations that are appropriate for further research and development by the land-cover community are the following examples: Development of multiscale sampling strategies for forest monitoring, such as combining MODIS and Landsat 7; Development of automated change detection methodologies;

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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN Evaluation of the role of very-high-spatial-resolution and hyperspectral data for land-cover and land-use characterization; Development of approaches to monitoring and modeling changes in biodiversity at the landscape scale; Development of product validation protocols for addressing issues of surface heterogeneity, such as scaling from point-flux measurements to satellite footprints; Development of methods for data fusion that will allow analysis of data from multiple sensing systems at multiple resolutions, including SAR and VCL; and Development of tools for managing large volumes of data, desktop data processing, and automated data retrieval and analysis. BIBLIOGRAPHY Anderson, J.R., E.E. Hardy, J.T. Roach, and R.E. Witner. 1976. A land use land cover classification system for use with remote sensing data. Geological Survey Professional Paper 964. 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Levy, A. Michaels, and J.L. Schnoor. 1995. Nitrogen fixation—anthropogenic enhancement-environmental response. Global Biogeochemical Cycles 9(2): 235-252. Gamon, J.A., L. Serrano, and J.S. Surfus. 1997. The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels. Oecol. Plant. 112(4): 492-501. Global Climate Observing System (GCOS). 1997. Global Hierarchical Observing Strategy (GHOST). GCOS Report 33, WMO TD No. 862. World Meteorological Organization. June 1997. Goward, S.N., and D.L. Williams. 1997. Landsat and Earth systems science: development of terrestrial monitoring . Photogramm. Eng. Remote Sensing 63(7): 887-900. Hansen, A.J., S.L. Garman, J.F. Weigand, D.L. Urban, et al. 1995. Alternative silvicultural regimes in the Pacific Northwest—simulations of ecological and economic effects. Ecol. Appl. 5(3): 535-554. Harrell, P.A., E.S. Kasischke, L.L. Bourgeau-Chavez, E.M. Haney, and N.L. 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