Reproduced, with permission, from:
Goward, S. N. 1989. Satellite bioclimatology. Journal of Climate 2: 710-20.(Manuscript received 21 April 1988, in final form 28 November 1988)
* This paper is part of a series of papers on satellite observations and climate.
** Also affiliated with GIMMS Group, Earth Resources Branch, Laboratory for Terrestrial Physics, NASA Goddard Space Flight Center, Greenbelt, Maryland.
Corresponding author address: Dr. Samuel N. Goward, Department of Geography, Remote Sensing Systems Laboratory, University of Maryland, College Park, MD 20742.
Satellite-acquired, remotely sensed observations of the earth's land areas are substantially advancing knowledge of global vegetation patterns. Recognition that combined visible/near infrared spectral reflectance observations are a general indicator of the presence, condition and magnitude of vegetation foliage provides a basis for explanation. This information is of considerable value in climatic research because of the links between climate variables and vegetation foliage. Presence of vegetation foliage is predominantly determined by a combination of local heat and moisture conditions. In turn, foliar presence determines local rates of photosynthesis, affects surface albedo, and influences local rates of evapotranspiration as well as other elements of surface energy/mass balance. Availability of these remotely sensed data provides, for the first time, a consistent, global means to directly study interactions between climate and vegetation. This understanding is now being incorporated in climatological research and should improve understanding of macroscale bioclimatology. Remote sensing technology and understanding of this technology are continuing to develop rapidly and further major advances in this new field of "satellite bioclimatology" can be expected in the near future.
Analysis of the relations between vegetation and climate is a central theme in terrestrial research (e.g., Merriam 1898; Koppen 1930; Thornthwaite 1931; Holdridge 1947; Leith 1956; Monteith 1973; Budyko 1974; Tuhkanen 1980; Box 1981; Monteith 1981; Walter 1985; Woodward 1987). Recent studies of global climate dynamics have focused attention on the need to improve understanding of vegetation/climate interactions (Hansen et al. 1981; Shukla and Mintz 1982; Dickinson 1983; Rosenzweig and Dickinson 1986). Efforts to develop new models of bioclimatology, however, are currently constrained by the paucity of measurements which may be used to describe and evaluate vegetation activity (Fung et al. 1983; Emanuel et al. 1985; Sellers et al. 1986; Willmott and Klink 1986).
Remotely sensed observations of electromagnetic radiant exitance from the earth's surface may provide the needed measurements (NASA 1983; NRC 1986b). Research carried out over the last two decades is beginning to conclude that multispectral remotely sensed observations provide one or more general indicators of vegetation foliar status. Foliar status in this context includes presence and magnitude (i.e., a combination of leaf area index and leaf angle distribution) of leaves as well as the pigment types and concentrations in the leaves. This vegetation foliar status is broadly dependent on adequate moisture and air temperatures, predominantly determines land photosynthesis rates and directly effects climate by determining the character of land surface energy exchange with the atmosphere. Continuous operation of the Landsat observing system since 1972 and recent observations from the NOAA operational and Nimbus experimental meteorological satellites have begun to produce a long-term record of this vegetation activity. These satellite observations offer great potential for advancing knowledge of bioclimatology and intensive analysis of these data is currently being pursued to develop this potential (Rasool 1987)
Remotely sensed observations should be of value in vegetation research. In most landscapes, vegetation canopies constitute a major, if not dominant, element of the interface between the land surface and the atmosphere and therefore are the predominant source of observed radiation fluxes. Remote sensing instruments are capable of providing high temporal resolution, spatially disaggregated measurements of these fluxes; a fundamental requirement for studying dynamic, heterogeneous vegetation phenomena. Indeed, aerial and ground photography have been used in vegetation research for more than a century (e.g., Colwell 1960), although quantitative use of these observations has been limited by the constraints of the photographic process (Pease and Pease 1972; Jones 1977). Scientific and technological developments that occurred during World War II stimulated current vegetation remote sensing research. Vegetation reflectance spectroscopy revealed the unique visible/near infrared spectral reflectance properties of healthy green vegetation (Krinov 1947: Billings and Morris 1951; Gates et al. 1965). This knowledge produced color infrared films for vegetation research and led directly to deployment of the Landsat observatory (e.g., Colwell 1956; Park 1983). Experiments with electronic imaging also contributed to Landsat deployment by providing a numerical source of multispectral data which could easily be telemetered from the satellite to ground receiving stations (Swain and Davis 1978). There was early recognition that electronic sensing would provide an excellent means for measuring land surface phenomena such as albedo and surface temperature (e.g., Kung et al. 1965; Malila and Wagner 1972; Pease et al. 1976; Goward and Oliver 1977; Short and Stuart, Jr. 1982; Pinker 1985; Brest and Goward 1987). However, the potential of these multispectral observations as a means to measure vegetation activity is only now becoming fully apparent.
There are many aspects of electromagnetic remote sensing which may be of value in bioclimatic research. This broad potential is explored later in this paper. Vegetation indices derived from combined visible and near infrared observations are the milestone in terrestrial remote sensing that has led to current interest in satellite bioclimatology. These visible/near infrared indices are therefore emphasized.
a. Visible/near infrared vegetation indices
Intensive analysis of aircraft and Landsat multispectral data has produced evidence that the basic spectral information structure of visible/near infrared multispectral land observations is two-dimensional, consisting of signals from the photosynthetically active "green" foliage component of vegetation canopies mixed with signals, of variable brightness, from background soils and litter (e.g., Deering et al. 1975; Kauth and Thomas 1976; Richardson and Wiegand 1977; NASA/JSC 1982; Hogg 1986). Recognition that visible/near infrared observations contained a measure of vegetation photosynthetically active "green" foliage led to the development of various numerical combinations of the visible and near infrared measurements aimed at isolating the vegetation signal (e.g., Tucker 1979; Jackson 1983). These numerical transforms of visible/near infrared observations have been widely shown to vary with the seasonal magnitude of green foliage (i.e., green leaf area index, green biomass or percentage green foliage ground cover) present in grasslands, agricultural crops and forests and as a result are often referred to as vegetation indices (e.g., Dethier 1974; Deering et al. 1975; Blair and Baumgardner 1977; Daughtry et al. 1982). Because a large number of vegetation indices are already used in ecological research, the expression visible/near infrared vegetation index (VNVI), will be used here to distinguish these remotely sensed vegetation measurements.1
b. Physical basis of visible/near infrared vegetation indices
Vegetation leaves are the only earth surfaces known to strongly absorb visible light but to absorb little or no light in the near infrared spectral region (Fig. 1). Spectral reflectance of other materials, such as soil and litter, generally increase monotonically with wavelength in the visible/near infrared region (Fig. 2). Therefore, at first order, the difference of visible versus near infrared reflectance from the earth's surface measures the presence of photosynthetically active vegetation surfaces. Numerous vegetation canopy parameters, including leaf area index, above ground biomass and percentage canopy closure, have been correlated with VNVIs (Colwell 1974; Holben et al. 1980, Bauer et al. 1981; Jensen 1983; Curran 1983; Steven 1985; Peterson et al. 1987). These relations tend to be species or site specific, however, because VNVIs result from light interactions with the entire geometry and optics of the vegetation canopy interface (Allen and Richardson 1968; Idso and DeWit 1970; Suits 1972; Colwell 1974; Kimes and Kirchner 1982; Smith 1983; Verhoef 1984). For example, leaf optical properties of vegetation in semiarid regions have been shown to be highly variable, suggesting that no simple interpretation of vegetation foliage amount may be possible, generally from VNVI measurements (Billings and Morris 1951; Ehleringer and Werk 1986).
c. Absorbed photosynthetically active radiation and VNVIs
An alternative explanation of the physical significance of VNVIs has recently been put forward (Kumar and Monteith 1981; Asrar et al. 1984; Hatfield et al. 1984; Wiegand and Richardson 1984; Sellers 1985; Daughtry and Ranson 1986; Choudhury 1987). A near-linear relation has been shown to exist, theoretically and empirically, between the relative proportion of incident photosynthetically active radiation (0.4 to 0.7 um ) which is absorbed (APAR) in vegetation canopies and the magnitude of the VNVI (Fig. 3). The relation between normalized difference vegetation index (NDVI) measurements and percentage APAR appears to be quite stable, over space and time.
The relation between APAR and VNVIs is intuitively appealing because both APAR and VNVIs are the result of vegetation canopy radiative transfer and such a relationship provides a direct link to a climatic variable, incident PAR solar radiation. Estimation of the proportion of incident PAR which is absorbed by photosynthetically active vegetation is fundamental to evaluating rates of photosynthesis and transpiration. Rates of photosynthesis and transpiration are controlled by stomatal conductance which, under non-stressed conditions, is determined by the amount of photosynthetically active radiation that is absorbed in vegetation canopies (Rosenberg et al. 1983; Sellers 1985; Landsberg 1986).
The conceptual basis for deriving APAR from VNVIs is a direct extension of the explanation for their occurrence. Because essentially no near infrared light is absorbed by photosynthetically active vegetation canopy elements, the visible/near infrared differential measures the ratio of the total incident light which interacted with these elements of the canopy to the amount of PAR absorbed by these elements. This explanation holds explicitly only when leaves absorb no near infrared light, and when background materials, including dead leaves, branches and stems, are perfect, diffuse reflectors. Where canopy materials other than these theoretical elements are present, the relation between percentage APAR and VNVIs is indirect and varies as a function of leaf near infrared absorptance as well as the visible and near infrared absorptances of the background materials (Huete et al. 1986; Choudhury 1987). There is a clear need for further research to ascertain the precision with which APAR may be derived from VNVIs, and a more broadly based explanation of the VNVI information content may result. There is, however, growing empirical evidence that this APAR explanation is essentially correct.
Field research has shown that, for crops and grasslands, there is a relation between the seasonal integration of VNVIs and seasonal accumulation of biomass (Tucker et al. 1981; Daughtry et al. 1982; Hatfield 1983; Steven et al. 1983). Early analyses of Landsat observations revealed that the seasonal character and and annual productivity of vegetation activity in grasslands and forests could be studied with remotely sensed observations (Dethier 1974; Deering et al. 1975; Blair and Baumgardner 1977). Intensive investigation of Landsat observations for global monitoring of crop production has also shown that the temporal pattern of VNVIs is diagnostic of crop conditions and crop type (Thompson and Wehmanen 1979; Hall and Badhwar 1987).
With its 16-18 day repeat cycle, the Landsat system alone is generally not able to collect the frequent global observations needed to track vegetation seasonality. With the launch of NOAA-6 in 1979, the required supplement to Landsat was unintentionally provided. The advanced very high resolution radiometer (AVHRR) on the polar-orbiting series of NOAA (National Oceanic and Atmospheric Administration) meteorological satellites was developed to provide detailed observations of global cloud patterns, twice daily (Schneider and McGinnis 1977; Tarpley et al. 1984). The AVHRR sensor spectral coverage was expanded for the NOAA-6 mission in an effort to improve discrimination between clouds and land. The solar reflective band (0.55-0.90 um) on previous AVHRR sensors was subdivided into two bands, a visible band (0.58-0.68 um) and a near infrared band (0.73-1.1 um). This change provided, for the first time, daily global measurements of visible and near infrared reflected spectral radiance.
Because a significant portion of the earth on any given day is cloud covered, it is generally not possible to derive daily estimates of vegetation foliar status change from the AVHRR data. With daily coverage, however, the AVHRR system provides, for most regions of the earth, the potential of observing the land surface at least once a month, and for many regions twice a month (Justice et al. 1985) (Fig. 4). "Clear-sky" views of continental- to global-scale regions are produced by compositing a series of temporal contiguous observations for a specified time interval. Compositing is a process which selects, for every image picture element, the highest VNVI measurement observed at that location during the specified time interval. This process effectively removes cloud-obscured observations and reduces the effects of variable atmospheric attenuation (Holben 1986). One limitation of the compositing approach is that if more than one clear surface view occurs during the compositing period then the technique will still select the "greenest" measurement, which may bias observation of the precise timing in foliar changes through the growing season. There is the alternative of inspecting each image individually and locating clear view, but the magnitude of effort required to accomplish this task generally far outweighs the value gained in temporal precision.
Preliminary analyses of the AVHRR NDVI measurements, for selected regions, demonstrated their value for bioclimatic research (Townshend and Tucker 1981; Gatlin et al. 1981; Ormsby 1982; Norwine and Greegor 1983). Continental to global-scale studies of AVHRR-derived VNVIs have shown that these measurements relate to the geography and seasonality of vegetative cover, the global carbon cycle, biome-level net primary productivity and seasonal cycles of temperature and precipitation (Tucker et al. 1985; Goward et al. 1985b; Justice et al. 1985; Tucker et al. 1986; Malingreau 1986; Justice 1986; Goward et al. 1987). Through a combination of climate data and NDVI estimates of APAR, reasonable estimates of annual vegetation productivity rates, at continental to global scales, have been computed (Dye 1985; Prentice 1986 Goward and Dye 1987).
The use of VNVIs in bioclimatic research is still in its infancy and much is still to be learned about this simple, broadband, visible/near infrared index of vegetation activity. Intensive analysis of VNVI measurements is currently being pursued and numerous efforts are underway to incorporate these remote sensing observations into studies of the biosphere and bioclimatology (e.g., NRC 1986a,b; Dyer and Crossley, Jr. 1986; Rasool 1987). Numerous other climatically important variables may be derived from remote sensing and these measurements, when combined with VNVIs, should further advance the current development of satellite bioclimatology (Yates et al. 1986). Remote sensing technology is rapidly developing, increasing the capacity for simultaneously observing electromagnetic exitance from land areas in finer radiometric, spectral and spatial detail (e.g., Goetz et al. 1985; NASA 1986b). Limited research already suggests that additional information about vegetation activity and related conditions can be derived by increasing the spectral resolution and spectral range of the observations (e.g., Waring et al. 1986). These scientific and technological advances are expected to substantially expand the capability for pursuing bioclimatic research with satellite remotely sensed observations.
a. Current research activities
Recognition of the potential for conducting vegetation research with remotely sensed observations has created a broad range of research and applications activities directed toward realizing this potential. The U.S. National Oceanic and Atmospheric Administration has developed an operational global vegetation index (GVI) product from AVHRR data and has supported application of this product in agricultural assessment (Tarpley et al. 1984; Johnson et al. 1987). The U.S. Department of Agriculture is taking advantage of this technology in their foreign commodities assessment (Philipson and Teng 1988). USAID is also supporting development of a famine warning system based, in part, on these satellite-acquired vegetation measurements (Walsh 1988).
The U.S. National Aeronautics and Space Administration (NASA) is focusing considerable attention on refinement of this technology. In particular, the Global Inventory Monitoring and Modeling Studies (GIMMS) group, at the NASA Goddard Space Flight Center, was developed in 1983 for the purpose of conducting macroscale vegetation research with remotely sensed data. With the support of NASA, NOAA, the United Nations Food and Agriculture Organization and other agencies, the GIMMS group has acquired the historical record of global AVHRR data and is in the process of producing a long-term global record of vegetation dynamics with these data (e.g., Justice et al. 1985; Tucker et al. 1985; Justice 1986; Hielkema et al. 1988). Basic research on a range of topics including atmospheric interference, bidirectional reflectance, sensor calibration and land surface radiative transfer as well as applications in ecology and hydrology are supported at universities and NASA research centers throughout the United States under the NASA Land Processes research program. These efforts are directed toward improving knowledge of the earth and should lead to developing a new generation of earth observing sensors which will refine capabilities to conduct terrestrial research from space (NASA 1986b).
ISLSCP. Recognition that remotely sensed observations may provide an indicator of vegetation photosynthetic capacity, along with climatically important parameters such as albedo and surface temperature, has led to a new international scientific initiative to study interactions between land conditions and climate with these remotely sensed data (Rasool and Bolle 1984). The International Satellite Land Surface Climatology Project (ISLSCP), sponsored by the World Meteorological Organization, The International Council of Scientific Unions Committee on Space Research (COSPAR) and United Nations Environment Program, now has active research programs in the United States, Europe, Africa, U.S.S.R., China and Australia. The U.S. element of the program is typical of international efforts. Two research efforts are underway: a retrospective analysis of the historical satellite data record and an intensive field experiment (First ISLSCP Field Experiment or FIFE). Sponsorship is provided by NASA, NOAA, National Science Foundation, U.S. Department of Agriculture and the Corp of Engineers. In both studies the VNVIs are a central focus of attention. In the retrospective analysis selected regions of the Great Plains and the Southwest are being subjected to analysis over the 15-year record of Landsat data. These regions were selected because they occur in the arid and semiarid regions of the continent and therefore are expected to reveal both short-term and possibly elements of longer term vegetation/climate dynamics. The FIFE experiment is being carried out on the Konza Prairie outside of Manhattan, Kansas (Sellers et al. 1988). During the 1987 growing season an intensive campaign of field measurements, aircraft and satellite observations was carried out for the purpose of evaluating whether surface energy budgets and photosynthetic processes can be derived from the satellite observations. The results of these research efforts can be expected to advance substantially the use of remotely sensed data in bioclimatic research.
b. Beyond VNVIs
Solar spectrum. Additional measurements in the visible spectral region may permit analysis of lichen-dominated high latitude ecosystems where the ecological impact of predicted climate warming may be first recorded because lichens spectrally reflect solar radiation differently than vascular plants (Petzold and Goward 1988). Fine spectral observations in the far red region may provide an indicator of vegetation stress because measurements in this region appear to "shift" as stress occurs (Rock et al. 1986). There is some evidence that observations in the shortwave infrared (SWIR) (1.4 to 2.5 um) solar reflective region may measure plant moisture status, although there is some uncertainty about what aspect of moisture status is observed (Goward 1985; Hunt, Jr. et al. 1987). There is even some evidence that Shortwave Infrared (1.3 um to 2.5 um ) spectroscopy may be used to evaluate plant biochemistry (Spanner et al. 1985).
Thermal infrared. The potential of thermal infrared (TIR) measurements in vegetation analysis appears large because surface thermal emissions are the net product of surface energy balance. An extensive record of research demonstrates that estimates of surface energy balance, evapotranspiration and vegetation stress may be derived from these measurements (e.g. Fuchs and Tanner 1966; Idso et al. 1975; Heilman et al. 1976; Carlson and Boland 1978; Hatfield 1979; Price 1980; Kimes 1980; Carlson et al. 1981; Goward 1981; Jackson et al. 1981; Seguin and Itier 1983; Jackson et al. 1983; Smith et al. 1985; Serafini 1987). With the exception of the Heat Capacity Mapping Mission (HCMM), however, there have been few sources of suitable land TIR data until recently (Short and Stuart, Jr. 1982). Although the second-generation Landsat Thematic Mapper sensor includes TIR observations, the observation time (1000 local) occurs when land thermal contrasts are minimal and surface fluxes are rapidly changing. Experimental data from the TIROS and Nimbus satellites have recently been processed for land surface temperatures and may be of great promise in bioclimate research (Susskind et al. 1984; Stowe et al. 1987).
The NOAA AVHRR system, with NOAA-7 and NOAA-9, combines TIR and VNVI observations at a 1430 local observing time, near the time of maximum surface temperatures and, under clear sky conditions, when surface fluxes of heat and moisture are not changing rapidly. With the combination of VNVIs and TIR observations, estimates of actual rates (in contrast to potential) of surface evapotranspiration and photosynthesis may be possible (Goward et al. 1985a; Hope et al. 1987). This concept is currently under intensive analysis as a part of FIFE. Similar analysis is being carried out in the coniferous forests of Montana (Nemani and Running 1989).
Microwave. Use of measurements from the microwave regions of the spectrum for biophysical analysis of vegetation is just beginning. A combination of VNVIs and passive microwave observations appears to provide a good index of soil moisture status in arid to semiarid regions of the globe (Theis et al. 1984; Choudhury et al. 1987). Perhaps one of the most novel recent developments in microwave remote sensing has been the recognition that cross-polarized observations at certain wavelengths provide another measure vegetation activity (Choudhury and Tucker 1987). Global observations from the 97 Ghz channel on the Nimbus Scanning Multichannel Microwave Radiometer (SMMR) sensor have been used to produce global maps of vegetation which are qualitatively similar to AVHRR-produced maps. The SMMR data appear particularly useful in arid and semiarid regions where they are apparently more sensitive than VNVIs to variations in vegetation activity. Active microwave observations of vegetation are still not well understood but recent theoretical and analytical research suggests that they may be of value in evaluating surface roughness as related to standing biomass (Paris 1986; Pitts et al. 1987; Van Zeal et al. 1987; Zebkar et al. 1987).
Progress in understanding the biophysical significance of multispectral observations of electromagnetic exitance from the earth's land areas has led to the recognition that one or more general measures of vegetation foliar status may be derived from remotely sensed data. These new measures of vegetation activity provide an opportunity to study vegetation/climate interactions at a level of detail not previously possible. Preliminary empirical analyses of these data suggest that the relations between vegetation activity and climate are strong, a finding which agrees with previously hypothesized macroscale bioclimatic theories. A direct link between the remotely sensed VNVIs and climate/vegetation interactions has been proposed in the relation of VNVIs to APAR. Although this concept needs further investigation, the empirical evidence strongly supports this hypothesis. Availability of these remotely sensed data provides an opportunity to test and refine bioclimatic theories by providing the vegetation measurements needed for this research. A broad range of studies are currently underway to develop the understanding needed to use remotely sensed data in bioclimatic research. In the context of current international scientific interest in the study of "Global Change," these innovations in satellite bioclimatology are timely.
The Landsat data record is now seventeen years in length and the AVHRR data record is now ten years in length. Other sensor systems are beginning to accumulate similar time histories. With the current operational and research satellite observatories followed by the proposed Earth Observing System, a true "climatology" of terrestrial vegetation activity should be available shortly after the turn of the century. As this time record of biospheric dynamics becomes more complete understanding of climate/biosphere interactions should significantly improve. New advances are developing rapidly in remote sensing technology, as well as progress in understanding the value of this technology in vegetation analysis. This progress should lead to further improvements in the use of remote sensing technology for studying the terrestrial biosphere and its interactions with the earth's climate. The potential for developing a satellite-based terrestrial bioclimatic monitoring system appears great and the proposed NASA/NOAA Earth Observing System should go a long way toward fulfilling this promise.
Acknowledgments. This research is supported under NASA HQ Grant NAGW-1152 and NASA Cooperative Agreement NCC 5-26 with the Goddard Space Flight Center. Encouragement from the staff of the Land Processes Branch, NASA/HQ and the GIMMS Group, as well as other members of the Laboratory for Terrestrial Physics, NASA/GSFC is most appreciated. Specifically, input from Chris Justice, C. J. Tucker, Bhaskar Choudhury and Tom Goff assisted in this study. Particular note must be given to Virginia Kalb, NASA/GSFC, who makes sure that the author does not get too lost in the GIMMS computer software. Mr. Dennis Dye, doctoral candidate in Geography at the University of Maryland, provided substantial support in this analysis. Discussions with J. Monteith, R. Waring, E. Box, W. Emanual, J. Olson and H. Lieth contributed to the preparation of this paper.
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