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Radiometric calibration of satellite sensors in the visible and near infrared: History and outlook
REMOTE SENSING OF ENVIRONMENT 22:3-9 (1987)
3
Radiometrie Calibration of Satellite Sensors in the Visible and Near Infrared: History and Outlook
JOHN C. PRICE U.S. Department of Agriculture, Agricultural Research Service, Remote Sensing Laboratory, Beltsville, Martfland 20705
Documentation for radiometric calibration of visible and near intrared sensors viewing the earth has been quite limited in the past. Recent quantitative me of satellite radiometry suggests the need for better information concerning instrumentation, estimation of atmospheric effects, and ground verification of satellite measured radiances. An example from the thermal infrared spectral region illustrates that analysis algorithms provide the link between satellite-derived results and the required accuracy of satellite calibration.
sification, do not utilize the physical units of the data in any way. For example, Interest in radiometric calibration of multiplying all radiometric values by a the earth-viewing satellites has developed factor of 2 would not affect any classificaonly recently, stimulated by the develop- tion results. Thus the need for quantitament of the capability to utilize quantita- tive radiometry has been absent from most tive radiometry. Although high spatial research work and applications. Lacking resolution remote sensing was initiated such motivation, the science of radiometmore than 20 years ago (e.g., Hovis and ric calibration has remained largely Knoll, 1983), the manipulation of calibra- academic in nature (Wyatt, 1978). In addition, the early years of satellite tion constants to permit comparison of data from various satellites dates to this instrumentation may be described as a present year (Price, 1987). It is reason- period of engineering development, since able to ask why this subject has taken so scientific considerations were largely overshadowed by NASA's desire to create long to develop. To begin with, the earth-viewing satel- high quality instrumentation which could lites represent a new tedmology, so that flmction over long periods of time in the applications and demonstrated require- space environment. This statement is ments for quantitative information hav/e based on personal familiarity with satelexisted only in the last few years. Data lite research programs (NASA, 1978). In from the Landsat Multispectral Scanners fact, the acceptance at a management were widely distributed and applied to level of the need for information on many earth resources problems, but the calibration is very recent indeed (see approaches used were generally qualita- Foreword to this issue). Note that the tive and image (picture) oriented, rather National Oceanic and Atmospheric Adthan employing the quantitative radiome- ministration (NOAA) is principally retry of the data (Robinov, 1982). I n fact, sponsible for prediction of weather and the most commonly used numerical tech- for research pertaining to weather and niques, supervised and unsupervised clas- climate, so that remote sensing of the Introduction
oo344257/87/$o.oo
4
I.C. PRICE
/ OBSERVATIONS
/
PRIMARY STANDARD
/
SECONDARY STANDARD FIGURE 1.
SENSOR
/
/
/
....
GROUND OBSERVATIONS
_
(~ R (~
APPLICATIONS
Summary of steps involved in establishing the calibration of a satellite radiometer.
land has fallen in a gray area between research and applications. As a final word of explanation we must recognize that the subject is extremely complex. Figure 1 illustrates the many technical issues involved in establishing preflight calibration of a satellite radiometer and then verifying this calibration during space operations. The fact that nine individual components may be identified suggests that a long term systematic approach is required, rather than simply a collection of research efforts. Of course, the principal uncertainties are associated with the satellite launch, which may alter the sensor's characteristics as established by preflight testing, and the inaccessibility of the instrument once it reaches the space environment. Various aspects of the numbered items are addressed in the papers that follow. However, as research
papers on specific topics, they do not consider the future evolution of the discipline and its usefulness for remote sensing applications. From a programmatic point of view, it appears that efforts should be devoted to better documentation of preflight calibration and inflight performance of radiometers, to systematic assessment of their long term stability, to quantification of requirements for calibration accuracy, and to field/ satellite data comparisons for verification of radiometric calibration.
Documentation of Preflight Calibration and Inflight Engineering Performance Past deficiencies in the documentation of calibration of Earth viewing satellites have been described by Williamson (1977)
RADIOMETRIC CALIBRATION OF SATELLITE SENSORS
and a specific example given by Slater (1979). It is unfortunate that much early information regarding the Landsat Multispectral Scanners has been discarded, as mentioned by Markham and Barker (1987) in this issue. The explanation for these deficiencies is straightforward. Preflight calibration is required to assure that output voltages during sensor operation will match the satellite data transmission system. Data on instrument performance in space are monitored routinely to verify sensor operation. The missing element has been a scientific commitment which accepts the significance of calibration and assumes the responsibility to monitor and document construction, testing, and operation of the sensor. Carrying out this task for the first time is nontrivial (Barnes and Price, 1980), but, once defined, the procedures and requirements are straightforward. Documentation of (housekeeping) engineering data serves the interests of both radiometric calibration and improved performance of future sensors. We note that both preflight radiometric calibration and ground radiometry for assessing satellite calibration are dependent on a primary reference standard. Information on services and standard sources may be obtained from the National Bureau of Standards (1982). Long Term Stability of Satellite Sensors Historically most applications of visible and near infrared satellite data have not required radiometric accuracy. In addition, neither theory nor field experiment predicts accurately the radiance levels expected at a radiometer observing the earth unless special effort is dedicated toward estimation of atmospheric effects. However, some applications, including
5
vegetation monitoring and assessment of man's activities on land surface ecology, depend on long term stability of the satellite calibration to produce useful estimates of long term variability. Future effects of human activities on regional scale habitability and possible long term weather modification can be addressed through study of a time series of satellite data. Since these applications require precision, rather than accuracy, data quality may be evaluated with a moderate level of confidence through repetitive measurements of a stable ground site. Results from the satellite data analysis may be verified and refined by occasional ground and atmospheric measurements at the site. The selection of a suitable site for satellite observations represents a compromise with weather induced variability. The best target is water (the ocean), which is unique in that both the wavelength dependence and absolute value of reflectance are known for clear ocean water. This permits simultaneous evaluation of atmospheric corrections and the surface reflectance, as discussed by Gordon (1987) in this issue. However, the reflectance of the ocean/atmosphere system is so low that observed radiances are not useful for assessing the performance of the sensor in the typical land reflectance range. If we exclude water bodies, we find that all natural surfaces are affected by surface moisture variations and by dust and particulates which are readily transported by the wind. The White Sands flats in New Mexico have been used for the study of Landsat data, e.g. Slater et al. (1987) and Frouin and Gautier (1987), this issue, as they are highly reflective, large in extent, and the region receives little rainfall. However, the very fine gypsum dust is easily picked up by
J. C. PRICE
wind, and part of the area is covered by shifting dunes. Another potential site is the Salar de Uyuni in Bolivia, a salt flat, which is larger, higher (less atmosphere), dryer, and near a moderately large water body, which provides a low reflectivity contrast point. The issue of spatial scale is significant, since locating ground control points in 1 km data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) is not always easy, and acquisition of adequate ground truth for comparison purposes raises sampling questions. It is much easier to validate higher spatial resolution data, such as Landsat Multispectral Scanner data. Unfortunately, field studies have been initiated only recently, leaving the accuracy and stability of early satellite data somewhat questionable (Nelson, 1985). Documentation of data availability for the early research satellites and their calibration information has been reviewed in an exceUent document by Malila and Anderson (1986).
Accuracy Requirements and Error Estimates We must admit that requirements for accurate satellite measurements in the visible and near infrared have not been demonstrated adequately at this time. One may construct lists of desired accuracies of physical variables, based on an educated guess as to their effect on theoretical models of the general circulation (World Meteorological Organization, 1975; NASA, 1984). However, these requirements are generally not based on analysis and thus are not quantitatively supported. Even if accuracy is required for a particular surface condition (e.g., vegetation), one may sometimes use aux-
iliary information, as a radiance from a water body or from an extended area which has known properties, in place of accurate knowledge of the sensor calibration. Thus the link between radiometric accuracy and general scientific goals is weak.
Evidently an intermediate step is needed: an explicit evaluation of the sensitivity to radiometric errors of each algorithm which yields a physical variable from the satellite radiances. In addition, the influence of the atmosphere as an error source must be evaluated, since independent data concerning atmospheric effects are seldom available to permit correction of satellite observations. As an example from another wavelength range, we consider thermal infrared estimates of sea surface temperature. This measurement is simplified by the homogeneity of temperature at the scale of satellite data, and by the ease with which a "'ground truth" value may be obtained with an inexpensive thermometer suspended in the surface water. Measurements of the radiance temperature Tll in the atmospheric window at 11 #m can provide an estimate of sea surface temperature Ts~t as follows: TssT = Tn + ST(atmosphere), where the emissivity effect is neglected for simplity (it is known accurately, in contrast to the circumstance for most land targets), and the atmospheric correction must either be derived by simultaneous independent measurements, as from radiosonde observation and radiative transfer theory, or inferred from other satellite radiometric measurements, or estimated from climatology. The case of simultaneous radiosonde observations is atypical and in fact represents an opportunity to
RADIOMETRIC CALIBRATION OF SATELLITE SENSORS
verify the calibration of the satellite sensor. It certainly cannot be assumed for regional or continental scale derivation of land or ocean surface parameters. If we accept climatological estimates for the value of the atmospheric correction, then the accuracy of the satellite estimate is given by = Tll + AT(climatological atmosphere) + ST(error from atmospheric variability). Thus the capability for calibration accuracy for the satellite sensor is limited by the atmospheric "noise" value to a typical range 2-3 C, unless some measure of atmospheric influence is provided. Since variability of the atmospheric correction is of the same order as interannual excursions of sea surface temperature in most locations, we conclude that this climatological approach does not produce a useful result for most oceanographic purposes. However, the atmospheric correction may be estimated through an additional measurement at 12 /~m, which corrects for atmospheric moisture, and a measurement from the visible channel, R, which implies an aerosol optical depth z (Griggs, 1985). The result may be written
rss = T11 + 2.58(T1
-
+ 7.27r - 10.62, where the complication of angular effects has been neglected by assuming nadir viewing. By differentiation we estimate the sensitivity to errors in the primary
7
viewing channel (11 ~tm), and in the derivation of the atmospheric correction. 6TssT = 8T H + 2.58(6Tll - ~T19.)+ 7.27-~--~8R. atmosphere This model example illustrates the approach for developing accuracy requirements for satellite radiometers. It appears that absence of quantitative requirements for visible-near-infrared calibration is largely due to the lack of algorithms for obtaining ground parameters from satellite radiances. The various forms of vegetation indices appear to support quantitative requirements, but they themselves are not accurately tied to measurements on the ground.
Field Verification Some papers in this volume consider approaches for verifying satellite calibration through independent measurements in the field. The logistics of such experiments are quite difficult and expensive, including the need to find an isolated and undisturbed location, or at least one which may be supervised and controlled, the need to set up atmospheric monitoring instruments, and the crucial problem of spatial scale. High spatial resolution measurements simplify the ground truth problem greatly, and it is evident that placing both high and low spatial resolution instruments on the same satellite has much to recommend it (Price, 1982). Accurate calibration of a high resolution sensor, e.g., Slater et al. (1987) (this issue) can provide a transfer point for calibra-
I" C. PRICE
tion of a low spatial resolution sensor such as AVHRR. Although subtleties remain (Curran and Hay, 1986), the principles are well enough established in the existing literature, with coordination a m o n g investigators and government agencies appearing as a principal need. The F u t u r e Remote sensing is in a period of transition, with the need for quantitative radiometry currently being established at the same time that the higher resolution sensors, like those on Landsat and SPOT, are being transferred to the private sector in the United States and France, respectively. Evidently calibration research will have to be supported through governm e n t programs, since the financial rewards to a commercial enterprise remain to be demonstrated in the indefinite future. It appears that we may reasonably expect support for this topic, given the long term benefits to remote sensing and to m a n y other scientific disciplines. In particular, the subject is of critical importance to long term climate monitoring, as in the International Land Surface Climatology Program.
References Barnes, W. L., and Price, J. c. (1980), Calibration of a satellite infrared radiometer, Appl. Opt. 19:2163-2161. Curran, P. J., and Hay, A. M. (1986), The importance of measurement error for certain procedures in remote sensing at optical wavelengths, Photogramm. Eng. Remote Sens. 52:229-241. Frouin, R., and Gautier, C. (1987), Calibration of NOAA-7, GOES-5 and GOES-6 VISSR/VAS solar channels, Remote Sens. Environ. 22:73-101.
Gordon, H., (1987), Calibration requirements and methodology for remote sensors viewing the ocean in the visible, Remote Sens. Environ. 22:103-126. Griggs, M., (1985), A method to correct satellite measurements of sea surface temperature for the effects of atmospheric aerosols, J. Geophys. Res. 90:951-959. Hovis, W. A., and Knoll, J. S. (1983), Characteristics of an internally illuminated calibration sphere, Appl. Opt. 22: 4004-4007. Malila, W. A., and Anderson, D. M. (1986), Satellite Data Availability and Calibration Documentation for Land Surface Climatology Studies, Environmental Research Institute of Michigan, NASA Contract NAS528715, 214 pp. Markham, B. L,, and Barker, J. L. (1987), Radiometric properties of U.S. processed Landsat MSS data, Remote Sens. Environ. 22:39-71. NASA (1978), Heat Capacity Mapping Mission User's Guide (J. Price, Ed.), Goddard Space Flight Center, Greenbelt, MD, 120 pp., rev. 1980. NASA (1984), Earth Observing System, Goddard Space Flight Center, Greenbelt, MD, Vol. 1, pp. 16-19. National Bureau of Standards (1982), Calibration and Related Measurement Service of the National Bureau of Standards, NBS Special Publication 250, 114 pp. Nelson, R. F. (1985), Sensor-Induced Variability of Landsat MSS Data, Remote Sens. Environ. 18:35-48. Price, J. c. (1982), Satellite Orbital Dynamics and Observation Strategies in Support of Agricultural Applications, Photogramm. Eng. Remote Sens. 48:1603-1611. Price, J. C. (1987), Calibration of satellite radiometers and the comparison of vegetation indices, Remote Sens. Environ. 22:3-9. Robinov, C. J. (1982) Computation of physical values from Landsat digital data, Photogramm. Eng. Remote Sens. 48:781-784.
RADIOMETRICCALIBRATIONOF SATELLITESENSORS Slater, P. N. (1979), A reexamination o{ the Landsat MSS, Photogramm. Eng. Remote Sens. 11:1479-1485. Slater, P. N. (1980), Remote Sensing, Optics and Optical Systems, Addison Wesley, Reading, MA, 575 pp. Slater, P. N., Biggar, S. F., Holm, R. G., Jackson, R. D., Mao, Y., Moran, M. S., Palmer, J. M., and Yuan, B. (1987), Reflectance based and radiance based methods for the inflight absolute calibration of multispectral sensors, Remote Sens. Environ. 22:11-37. Williamson, L. E. (1977), Calibration Tech-
9
nology for Meteorological Satellites, Atmospheric Sciences Laboratory Monograph No. 3, White Sands Missile Range, NM, 139 pp. World Meteorological Organization (1975), The Physical Basis of Climate and Climate Modeling, GARP Publication No. 16, pp. 76 -93. Wyatt, C. L. (1978), Radiometric Calibration: Theory and Methods, Academic, New York, 200 pp.
Received 10 September1986;revised18 December1986.
3
Radiometrie Calibration of Satellite Sensors in the Visible and Near Infrared: History and Outlook
JOHN C. PRICE U.S. Department of Agriculture, Agricultural Research Service, Remote Sensing Laboratory, Beltsville, Martfland 20705
Documentation for radiometric calibration of visible and near intrared sensors viewing the earth has been quite limited in the past. Recent quantitative me of satellite radiometry suggests the need for better information concerning instrumentation, estimation of atmospheric effects, and ground verification of satellite measured radiances. An example from the thermal infrared spectral region illustrates that analysis algorithms provide the link between satellite-derived results and the required accuracy of satellite calibration.
sification, do not utilize the physical units of the data in any way. For example, Interest in radiometric calibration of multiplying all radiometric values by a the earth-viewing satellites has developed factor of 2 would not affect any classificaonly recently, stimulated by the develop- tion results. Thus the need for quantitament of the capability to utilize quantita- tive radiometry has been absent from most tive radiometry. Although high spatial research work and applications. Lacking resolution remote sensing was initiated such motivation, the science of radiometmore than 20 years ago (e.g., Hovis and ric calibration has remained largely Knoll, 1983), the manipulation of calibra- academic in nature (Wyatt, 1978). In addition, the early years of satellite tion constants to permit comparison of data from various satellites dates to this instrumentation may be described as a present year (Price, 1987). It is reason- period of engineering development, since able to ask why this subject has taken so scientific considerations were largely overshadowed by NASA's desire to create long to develop. To begin with, the earth-viewing satel- high quality instrumentation which could lites represent a new tedmology, so that flmction over long periods of time in the applications and demonstrated require- space environment. This statement is ments for quantitative information hav/e based on personal familiarity with satelexisted only in the last few years. Data lite research programs (NASA, 1978). In from the Landsat Multispectral Scanners fact, the acceptance at a management were widely distributed and applied to level of the need for information on many earth resources problems, but the calibration is very recent indeed (see approaches used were generally qualita- Foreword to this issue). Note that the tive and image (picture) oriented, rather National Oceanic and Atmospheric Adthan employing the quantitative radiome- ministration (NOAA) is principally retry of the data (Robinov, 1982). I n fact, sponsible for prediction of weather and the most commonly used numerical tech- for research pertaining to weather and niques, supervised and unsupervised clas- climate, so that remote sensing of the Introduction
oo344257/87/$o.oo
4
I.C. PRICE
/ OBSERVATIONS
/
PRIMARY STANDARD
/
SECONDARY STANDARD FIGURE 1.
SENSOR
/
/
/
....
GROUND OBSERVATIONS
_
(~ R (~
APPLICATIONS
Summary of steps involved in establishing the calibration of a satellite radiometer.
land has fallen in a gray area between research and applications. As a final word of explanation we must recognize that the subject is extremely complex. Figure 1 illustrates the many technical issues involved in establishing preflight calibration of a satellite radiometer and then verifying this calibration during space operations. The fact that nine individual components may be identified suggests that a long term systematic approach is required, rather than simply a collection of research efforts. Of course, the principal uncertainties are associated with the satellite launch, which may alter the sensor's characteristics as established by preflight testing, and the inaccessibility of the instrument once it reaches the space environment. Various aspects of the numbered items are addressed in the papers that follow. However, as research
papers on specific topics, they do not consider the future evolution of the discipline and its usefulness for remote sensing applications. From a programmatic point of view, it appears that efforts should be devoted to better documentation of preflight calibration and inflight performance of radiometers, to systematic assessment of their long term stability, to quantification of requirements for calibration accuracy, and to field/ satellite data comparisons for verification of radiometric calibration.
Documentation of Preflight Calibration and Inflight Engineering Performance Past deficiencies in the documentation of calibration of Earth viewing satellites have been described by Williamson (1977)
RADIOMETRIC CALIBRATION OF SATELLITE SENSORS
and a specific example given by Slater (1979). It is unfortunate that much early information regarding the Landsat Multispectral Scanners has been discarded, as mentioned by Markham and Barker (1987) in this issue. The explanation for these deficiencies is straightforward. Preflight calibration is required to assure that output voltages during sensor operation will match the satellite data transmission system. Data on instrument performance in space are monitored routinely to verify sensor operation. The missing element has been a scientific commitment which accepts the significance of calibration and assumes the responsibility to monitor and document construction, testing, and operation of the sensor. Carrying out this task for the first time is nontrivial (Barnes and Price, 1980), but, once defined, the procedures and requirements are straightforward. Documentation of (housekeeping) engineering data serves the interests of both radiometric calibration and improved performance of future sensors. We note that both preflight radiometric calibration and ground radiometry for assessing satellite calibration are dependent on a primary reference standard. Information on services and standard sources may be obtained from the National Bureau of Standards (1982). Long Term Stability of Satellite Sensors Historically most applications of visible and near infrared satellite data have not required radiometric accuracy. In addition, neither theory nor field experiment predicts accurately the radiance levels expected at a radiometer observing the earth unless special effort is dedicated toward estimation of atmospheric effects. However, some applications, including
5
vegetation monitoring and assessment of man's activities on land surface ecology, depend on long term stability of the satellite calibration to produce useful estimates of long term variability. Future effects of human activities on regional scale habitability and possible long term weather modification can be addressed through study of a time series of satellite data. Since these applications require precision, rather than accuracy, data quality may be evaluated with a moderate level of confidence through repetitive measurements of a stable ground site. Results from the satellite data analysis may be verified and refined by occasional ground and atmospheric measurements at the site. The selection of a suitable site for satellite observations represents a compromise with weather induced variability. The best target is water (the ocean), which is unique in that both the wavelength dependence and absolute value of reflectance are known for clear ocean water. This permits simultaneous evaluation of atmospheric corrections and the surface reflectance, as discussed by Gordon (1987) in this issue. However, the reflectance of the ocean/atmosphere system is so low that observed radiances are not useful for assessing the performance of the sensor in the typical land reflectance range. If we exclude water bodies, we find that all natural surfaces are affected by surface moisture variations and by dust and particulates which are readily transported by the wind. The White Sands flats in New Mexico have been used for the study of Landsat data, e.g. Slater et al. (1987) and Frouin and Gautier (1987), this issue, as they are highly reflective, large in extent, and the region receives little rainfall. However, the very fine gypsum dust is easily picked up by
J. C. PRICE
wind, and part of the area is covered by shifting dunes. Another potential site is the Salar de Uyuni in Bolivia, a salt flat, which is larger, higher (less atmosphere), dryer, and near a moderately large water body, which provides a low reflectivity contrast point. The issue of spatial scale is significant, since locating ground control points in 1 km data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) is not always easy, and acquisition of adequate ground truth for comparison purposes raises sampling questions. It is much easier to validate higher spatial resolution data, such as Landsat Multispectral Scanner data. Unfortunately, field studies have been initiated only recently, leaving the accuracy and stability of early satellite data somewhat questionable (Nelson, 1985). Documentation of data availability for the early research satellites and their calibration information has been reviewed in an exceUent document by Malila and Anderson (1986).
Accuracy Requirements and Error Estimates We must admit that requirements for accurate satellite measurements in the visible and near infrared have not been demonstrated adequately at this time. One may construct lists of desired accuracies of physical variables, based on an educated guess as to their effect on theoretical models of the general circulation (World Meteorological Organization, 1975; NASA, 1984). However, these requirements are generally not based on analysis and thus are not quantitatively supported. Even if accuracy is required for a particular surface condition (e.g., vegetation), one may sometimes use aux-
iliary information, as a radiance from a water body or from an extended area which has known properties, in place of accurate knowledge of the sensor calibration. Thus the link between radiometric accuracy and general scientific goals is weak.
Evidently an intermediate step is needed: an explicit evaluation of the sensitivity to radiometric errors of each algorithm which yields a physical variable from the satellite radiances. In addition, the influence of the atmosphere as an error source must be evaluated, since independent data concerning atmospheric effects are seldom available to permit correction of satellite observations. As an example from another wavelength range, we consider thermal infrared estimates of sea surface temperature. This measurement is simplified by the homogeneity of temperature at the scale of satellite data, and by the ease with which a "'ground truth" value may be obtained with an inexpensive thermometer suspended in the surface water. Measurements of the radiance temperature Tll in the atmospheric window at 11 #m can provide an estimate of sea surface temperature Ts~t as follows: TssT = Tn + ST(atmosphere), where the emissivity effect is neglected for simplity (it is known accurately, in contrast to the circumstance for most land targets), and the atmospheric correction must either be derived by simultaneous independent measurements, as from radiosonde observation and radiative transfer theory, or inferred from other satellite radiometric measurements, or estimated from climatology. The case of simultaneous radiosonde observations is atypical and in fact represents an opportunity to
RADIOMETRIC CALIBRATION OF SATELLITE SENSORS
verify the calibration of the satellite sensor. It certainly cannot be assumed for regional or continental scale derivation of land or ocean surface parameters. If we accept climatological estimates for the value of the atmospheric correction, then the accuracy of the satellite estimate is given by = Tll + AT(climatological atmosphere) + ST(error from atmospheric variability). Thus the capability for calibration accuracy for the satellite sensor is limited by the atmospheric "noise" value to a typical range 2-3 C, unless some measure of atmospheric influence is provided. Since variability of the atmospheric correction is of the same order as interannual excursions of sea surface temperature in most locations, we conclude that this climatological approach does not produce a useful result for most oceanographic purposes. However, the atmospheric correction may be estimated through an additional measurement at 12 /~m, which corrects for atmospheric moisture, and a measurement from the visible channel, R, which implies an aerosol optical depth z (Griggs, 1985). The result may be written
rss = T11 + 2.58(T1
-
+ 7.27r - 10.62, where the complication of angular effects has been neglected by assuming nadir viewing. By differentiation we estimate the sensitivity to errors in the primary
7
viewing channel (11 ~tm), and in the derivation of the atmospheric correction. 6TssT = 8T H + 2.58(6Tll - ~T19.)+ 7.27-~--~8R. atmosphere This model example illustrates the approach for developing accuracy requirements for satellite radiometers. It appears that absence of quantitative requirements for visible-near-infrared calibration is largely due to the lack of algorithms for obtaining ground parameters from satellite radiances. The various forms of vegetation indices appear to support quantitative requirements, but they themselves are not accurately tied to measurements on the ground.
Field Verification Some papers in this volume consider approaches for verifying satellite calibration through independent measurements in the field. The logistics of such experiments are quite difficult and expensive, including the need to find an isolated and undisturbed location, or at least one which may be supervised and controlled, the need to set up atmospheric monitoring instruments, and the crucial problem of spatial scale. High spatial resolution measurements simplify the ground truth problem greatly, and it is evident that placing both high and low spatial resolution instruments on the same satellite has much to recommend it (Price, 1982). Accurate calibration of a high resolution sensor, e.g., Slater et al. (1987) (this issue) can provide a transfer point for calibra-
I" C. PRICE
tion of a low spatial resolution sensor such as AVHRR. Although subtleties remain (Curran and Hay, 1986), the principles are well enough established in the existing literature, with coordination a m o n g investigators and government agencies appearing as a principal need. The F u t u r e Remote sensing is in a period of transition, with the need for quantitative radiometry currently being established at the same time that the higher resolution sensors, like those on Landsat and SPOT, are being transferred to the private sector in the United States and France, respectively. Evidently calibration research will have to be supported through governm e n t programs, since the financial rewards to a commercial enterprise remain to be demonstrated in the indefinite future. It appears that we may reasonably expect support for this topic, given the long term benefits to remote sensing and to m a n y other scientific disciplines. In particular, the subject is of critical importance to long term climate monitoring, as in the International Land Surface Climatology Program.
References Barnes, W. L., and Price, J. c. (1980), Calibration of a satellite infrared radiometer, Appl. Opt. 19:2163-2161. Curran, P. J., and Hay, A. M. (1986), The importance of measurement error for certain procedures in remote sensing at optical wavelengths, Photogramm. Eng. Remote Sens. 52:229-241. Frouin, R., and Gautier, C. (1987), Calibration of NOAA-7, GOES-5 and GOES-6 VISSR/VAS solar channels, Remote Sens. Environ. 22:73-101.
Gordon, H., (1987), Calibration requirements and methodology for remote sensors viewing the ocean in the visible, Remote Sens. Environ. 22:103-126. Griggs, M., (1985), A method to correct satellite measurements of sea surface temperature for the effects of atmospheric aerosols, J. Geophys. Res. 90:951-959. Hovis, W. A., and Knoll, J. S. (1983), Characteristics of an internally illuminated calibration sphere, Appl. Opt. 22: 4004-4007. Malila, W. A., and Anderson, D. M. (1986), Satellite Data Availability and Calibration Documentation for Land Surface Climatology Studies, Environmental Research Institute of Michigan, NASA Contract NAS528715, 214 pp. Markham, B. L,, and Barker, J. L. (1987), Radiometric properties of U.S. processed Landsat MSS data, Remote Sens. Environ. 22:39-71. NASA (1978), Heat Capacity Mapping Mission User's Guide (J. Price, Ed.), Goddard Space Flight Center, Greenbelt, MD, 120 pp., rev. 1980. NASA (1984), Earth Observing System, Goddard Space Flight Center, Greenbelt, MD, Vol. 1, pp. 16-19. National Bureau of Standards (1982), Calibration and Related Measurement Service of the National Bureau of Standards, NBS Special Publication 250, 114 pp. Nelson, R. F. (1985), Sensor-Induced Variability of Landsat MSS Data, Remote Sens. Environ. 18:35-48. Price, J. c. (1982), Satellite Orbital Dynamics and Observation Strategies in Support of Agricultural Applications, Photogramm. Eng. Remote Sens. 48:1603-1611. Price, J. C. (1987), Calibration of satellite radiometers and the comparison of vegetation indices, Remote Sens. Environ. 22:3-9. Robinov, C. J. (1982) Computation of physical values from Landsat digital data, Photogramm. Eng. Remote Sens. 48:781-784.
RADIOMETRICCALIBRATIONOF SATELLITESENSORS Slater, P. N. (1979), A reexamination o{ the Landsat MSS, Photogramm. Eng. Remote Sens. 11:1479-1485. Slater, P. N. (1980), Remote Sensing, Optics and Optical Systems, Addison Wesley, Reading, MA, 575 pp. Slater, P. N., Biggar, S. F., Holm, R. G., Jackson, R. D., Mao, Y., Moran, M. S., Palmer, J. M., and Yuan, B. (1987), Reflectance based and radiance based methods for the inflight absolute calibration of multispectral sensors, Remote Sens. Environ. 22:11-37. Williamson, L. E. (1977), Calibration Tech-
9
nology for Meteorological Satellites, Atmospheric Sciences Laboratory Monograph No. 3, White Sands Missile Range, NM, 139 pp. World Meteorological Organization (1975), The Physical Basis of Climate and Climate Modeling, GARP Publication No. 16, pp. 76 -93. Wyatt, C. L. (1978), Radiometric Calibration: Theory and Methods, Academic, New York, 200 pp.
Received 10 September1986;revised18 December1986.