Derivation of Geophysical Parameters from AVHRR Data

  • Gérard Dedieu
Part of the Euro Courses book series (EURS, volume 5)

Abstract

In this chapter we present recent research developments in the use of data derived from the NOAA-AVHRR together with various types of models and ancillary data. The synergistic use of models and data is a promising way for the future use of remotely-sensed data. First, it provides a quantitative retrieval of geophysical parameters, such as surface albedo, which are closely related to satellite measurements. Second, this approach is attractive since coupling models and data may allow the estimation of model parameters (e.g. leaf area index) which are not directly linked to radiance measurements per se.

In this chapter we present two examples of studies which illustrate the combined use of satellite data and models to retrieve geophysical parameters. The objective of the first study is the assessment of surface albedo from AVHRR directional measurements in the shortwave channels. The aim of the second study is to estimate vegetational Net Primary Productivity at the global scale. In addition, these studies require measurements of the highest possible precision, and then consideration will illustrate the current state-of-the-art in data processing capabilities.

In their respective domains, these studies are at the forefront of current remote sensing applications, and the results presented here are preliminary. Further work is needed, particularly regarding validation. However, we think that these two studies represent significant examples of the new trends in the use of satellite measuremen

Keywords

Remote Sensing Zenith Angle Surface Albedo Solar Zenith Angle Heterotrophic Respiration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References and Bibliography for the “Surface albedo” topic

  1. Arino, O., Dedieu, G., and Deschamps, P.Y., 1991: Determination of land surface spectral reflectances using Meteosat and NOAA/AVHRR shortwave channel data. International Journal of Remote Sensing,13, 2263–2287.CrossRefGoogle Scholar
  2. Cabot, F., and Dedieu, G., 1993: Surface albedo from space : coupling bidirectional models and remotely sensed measurements. Submitted to Journal of Geophysical Research Google Scholar
  3. Cabot, F., Dedieu, G., and Maisongrande, P., 1993a : Surface albedo from space over HAPEX SAHEL sites. To be published in the Proceedings of the 6th AVHRR Data User’s Meeting, EUMETSAT-JRC, Belgirate, Italy, 28th June–2nd July, 1993.Google Scholar
  4. Cabot, F., Maisongrande, P., and Dedieu, G., 1993b : Monitoring the AVHRR calibration. To be published in the proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS’93), Tokyo, Japan, August 18–21,1993.Google Scholar
  5. Deering, D.W, Eck, T.F., and Otterman, J., 1990 : Bidirectional reflectances of selected desert surfaces and their three-parameter soil characterisation.Agricultural and Forest Meteorology, 52, 71–93.CrossRefGoogle Scholar
  6. Eaton, F.D., and Dirmhira, I., 1979: Reflected irradiance indicatrices of natural surfaces and their effect on albedo. Applied Optics, 18, 994–1008.CrossRefGoogle Scholar
  7. Faizoun, C.A., and Dedieu, G., 1993 : Atmospheric effects on NOAA/AVHRR shortwave measurements: Sensitivity study and use of atmospheric climatology to correct AVHRR time series. To be published in Proceedings of 6th AVHRR Data User’s Meeting, EUMETSAT-JRC, Belgirate, Italy, 28th June–2nd July, 1993.Google Scholar
  8. Goward, S.N., Markham, B., Dye, D.G., Dulaney, W., and Yang, J., 1991 : Normalized difference vegetation index measurements from the advanced very high resolution radiometer. Remote Sensing of Environment, 35, 257–277.CrossRefGoogle Scholar
  9. Gutman, G.G., Ohring, G., Tarpley, D., and Ambroziak, R., 1989 : Albedo of the U.S. Great Plains as determined from NOAA–9 AVHRR Data. Journal of Climate, 2, 608– 617.CrossRefGoogle Scholar
  10. Gutman, G.G., 1991 : Vegetation indices from AVHRR: an update and future prospects. Remote Sensing of Environment, 35, 121–136.CrossRefGoogle Scholar
  11. Hapke, B., 1981 : Bidirectional reflectance spectroscopy 1. Theory. Journal o f Geophysical Research, 86, 3039–3054.CrossRefGoogle Scholar
  12. Holben, B.N., 1986 : Characteristics of maximum-value composite images from temporal AVHRR data. International Journal of Remote Sensing, 7, 1417–1434.CrossRefGoogle Scholar
  13. Irons, J.R., and Smith, J.A., 1990 : Soil surface roughness characterization from light scattering observations. Proceedings of IGARSS’90, Washington, USA, 20–24 May, 1990, 1007–1010, 1990.Google Scholar
  14. Kerr, Y., and Lagouarde, J.P., 1989 : On the derivation of land surface temperature from AVHRR data. Proceedings of the 4th A VHRR data users’ meeting. Rothenburg, FRG, 157–160.Google Scholar
  15. Kimes, D.S., and Sellers, P., 1985 : Inferring hemispherical reflectance of the Earth’s surface for global energy budgets from remotely sensed nadir or directional radiance values. Remote Sensing of Environment, 18, 205–223.CrossRefGoogle Scholar
  16. Kimes, D.S., and Holben, B.N., 1992 : Extracting spectral albedo from NOAA-9 AVHRR multiple view data using an atmospheric correction procedure and an expert system. International Journal of Remote Sensing, 13, 275–289.CrossRefGoogle Scholar
  17. Kimes, D.S., 1983 : Dynamics of directional reflectance factor distribution for vegetation canopies. Applied Optics, 22, 1354–1372.CrossRefGoogle Scholar
  18. Kimes, D.S., Newcomb, W., Tucker, C.J., Zonneveld, I.S., Van Wijngaarden, W., DeLeeuw, J., and Epema, G.F., 1985 : Directional reflectance factor distributions for cover types of Northern Africa. Remote Sensing of Environment, 18, 1–19.CrossRefGoogle Scholar
  19. London, J., Bojkov, R.D., Oltmans, S., and Kelley, J.I., 1976 : Atlas of the global distribution of total ozone July 1957 – June 1967, NCAR/TN-113+STR. Google Scholar
  20. McClatchey, R.A., Fenn, R.W., Selby, J.E.A., Garing, J.S., and Volz, F.E., 1971 : Optical properties of the atmosphere. (AFCLR-71-0279) Air Force Cambridge Research Lab., Bedford, Mas.Google Scholar
  21. Pinty, B., Verstraete, M.M., and Dickinson, R.E., 1989: A physical model for predicting bidirectional reflectances over bare soil. Remote Sensing of Environment, 27, 273–288.CrossRefGoogle Scholar
  22. Rahman, H., and Dedieu. G., 1993 : A simple method for the atmospheric correction of satellite measurements in the solar spectrum. Submitted to International Journal of Remote Sensing.Google Scholar
  23. Rahman, H., Pinty, B., and Verstraete, M.M., 1993 : A coupled surface-atmosphere reflectance (CSAR) model part 1: model description and inversion on synthetic data, Submitted to Remote Sensing of Environment.Google Scholar
  24. Ross, J.K., 1981: The radiation regime and architecture of plant stands, 1981 : Dr W.Junk Publishers, Boston.Google Scholar
  25. Roujean, J.L., Leroy, M., and Deschamps, P.Y., 1992 : A bidirectional reflectance model of the Earth’s surface for the correction of remote sensing data. Journal of Geophysical Research, 97, (20) 455–468.Google Scholar
  26. Roujean, J.L., Leroy, M., and Deschamps, P.Y., and Podaire, A., 1992 :Evidence of surface bidirectional effects from a NOAA/AVHRR multitemporal data set.International Journal of Remote Sensing, 13, 685–698.CrossRefGoogle Scholar
  27. Shibayama, M., and Wiegand, C.L., 1985 : View azimuth and zenith, and solar angle effects on wheat canopy reflectance. Remote Sensing of Environment, 18, 91–103.CrossRefGoogle Scholar
  28. Tanre, D, Deroo, C., Duhaut, P., Herman, M., Morcrette, J.J., Perbos, J., and Deschamps, P.Y., 1990 : Description of a computer code to simulate the satellite signal in the solar spectrum: the 5S code. International Journal of Remote Sensing, 11, 659–668.CrossRefGoogle Scholar
  29. Verstraete, MM, Pinty, B., and Dickinson, RE., 1990 : A physical model of the bidirectional reflectance of vegetation canopies, 1. Theory. Journal of Geophysical Research 95. (11) 755–765.Google Scholar
  30. Ågren, G.J., McMurtie, R.E., Parton, W.J., Pastor, J., and Shugart, H.H., 1991 : Stateof- the-art of models of production-decomposition linkages in conifer and grassland ecosystems. Ecological Applications, 761, 118–138.CrossRefGoogle Scholar
  31. Asrar, G., Fuchs, M., Kanemasu, E.T., and Hatfield, J.L., 1984 : Estimating absorbed photosynthetic radiation and leaf area index from spectral reflectance in wheat. Agronomy Journal, 76, 300–306. CrossRefGoogle Scholar
  32. Band, L.E., Patterson, P., Nemani, R., and Running, S.W. 1993 : Forest ecosystem processes at the watershed scale: incorporating hillslope hydrology. Agricultural and Forest Meteorology, 63, 93–126.CrossRefGoogle Scholar
  33. Bascatowe, R., Adams, J.A., Keeling, C.D., Moss, D.J., Whorf, TP., and Wong, C.S. 1980 : Response of atmospheric carbon dioxide to the weak 1975 El Nino. Science, 210, 66–68.CrossRefGoogle Scholar
  34. Bolin, B. 1986 : How much C02 will remain in the atmosphere - The carbon cycle and projections for the future. In greenhouse effect, climate change and ecosystems,SCOPE 29, Bolin, Doos, Warrick and Jager (Eds), John Wiley & Sons, pp 93–155.Google Scholar
  35. Bonan, G.B. 1991 : Atmosphere-Biosphere exchange of carbon dioxide in boreal forest. Journal of Geophysical Research, 96, D4, 7301–7312.CrossRefGoogle Scholar
  36. Bouman, B.A.M. 1991 : The linking if crop growth models and multi-sensor remote sensing data. Proceedings of the 5th int. Coll. on Physical Measurements and Signatures in Remote Sensing. Courchevel, France, 14–18 January 1991, ESA SP–319, 583–588.Google Scholar
  37. Box, E. 1988 : Estimating the seasonal carbon source-sink geography of a natural, steadystate terrestrial biosphere. PJournal of Applied Meteorology, 27, 1109–1123. CrossRefGoogle Scholar
  38. Dedieu, G., Deschamps, P.Y., and Kerr, Y.H. 1987 : Satellite estimation of solar irradiance at the surface of the earth and of surface albedo using a physical model applied to Meteosat data. Journal of Climate and Applied Meteorology, 26, 79–87.CrossRefGoogle Scholar
  39. Esser, G. 1991 : Osnabriick Biosphere Model : structure, construction, results. In :Modern Ecology : basic and applied aspects. Esser, G. and Overdieck (Eds), Elsevier, Amsterdam, London, New York, Tokyo, pp 679–709.Google Scholar
  40. Fung, I.Y., Prentice, K., Matthews, E., Lerner, J., and Russel, G. 1983 : Three dimensional tracer model study of the atmospheric C02: response to seasonal exchanges with the terrestrial biosphere. Journal of Geophysical Research, 88, 1281– 1294.CrossRefGoogle Scholar
  41. Fung, I.Y., Tucker, C.J., and Prentice, K.C. 1987 : Application of Advanced Very High Resolution Radiometer to study atmospheric-biosphere exchange of C02. Journal of Geophysical Research, 92, 2999–3015.CrossRefGoogle Scholar
  42. Heimann, M., and Keeling, C.D. 1989 : A three-dimensional model of atmospheric C02 transport based on observed winds. 2. Model description and simulated tracer experiments. In : D.H. Peterson (Ed) : Aspects of climate variability in the Pacific and the Western Americas. Geophysical Monograph 55, pp 237–274.CrossRefGoogle Scholar
  43. Holdridge, L.R. 1947 : Determination of world formations from simple climatic data. Science, 105, 367–368.CrossRefGoogle Scholar
  44. Janecek, A., Benderoth, G., Liideke, M.K.B., Kindermann, J., and Kohlmaier, G.H. 1989 : Model of the seasonal and perennial carbon dynamics in deciduous-type forests controlled by climatic variables. Ecological Modelling, 49, 101–124. CrossRefGoogle Scholar
  45. Keeling, C.D., Piper, S.C., and Heimann, M. 1989 : A three-dimensional model of atmospheric C02 transport based on observed winds : 4. Mean annual gradients and interannual variations. In : D.H. Peterson (Ed) : Aspects of climate variability in the Pacific and the Western Americas. Geophysical Monograph 55, pp 305–363.CrossRefGoogle Scholar
  46. Kergoa, L., and Dedieu, G. 1993 : A Generic Model for Global Carbon Study and Satellite Data Assimilation. To be submitted for the proceedings of the 4th International C02 Conference, Carqueiranne, France - September 13–17, 1993.Google Scholar
  47. Lieth, H. 1975 : Primary production of the major vegetation units of the world. In : Primary Productivity of the Biosphere, Lieth, H., and Whittaker, R.H., (Eds), Berlin- Heidelberg-New York, Springer Verlag, pp 237–263.Google Scholar
  48. Martin, P. 1993 : Vegetation responses and feedbacks to climate : a review of models and processes. Climate Dynamics 8, 201–210.CrossRefGoogle Scholar
  49. Melillo, J.M., McGuire, A.D., Kicklighter, D.W., Moore, B., Vorosmarty, C.J., and Schloss, A.L. 1993 : Global climate change and terrestrial net primary production. Nature, 363, 234–240.CrossRefGoogle Scholar
  50. Monteith, J.L. 1972 : Solar radiation and productivity in tropical ecosystems. Journal of Applied Ecology, 9, 277–294.Google Scholar
  51. Monteith, J.L. 1977 : Climate and the efficiency of crop production in Britain. Royal Society of London, Philosophical Transaction, Series B, 281, 277–294.CrossRefGoogle Scholar
  52. Moulin, S., and Fischer, A. 1993 : Simulation of the temporal variations of NOAA/AVHRR reflectances. Coupling of functional model and satellite data. To appear in the proceedings of the 6th AVHRR Data Users’ Meeting, EUMETSAT-JRC,Belgirate, Italy, 28th June–2nd July 1993.Google Scholar
  53. Porter, J.R., Bragg, P.L., Rayner, J.H., Weir, A.H., and Landsberg, J.J. 1982 : The ARC Winter Wheat Model - principles and progress. British Plant Growth Regulator Group, Monograph 7, ’Opportunities for manipulation of cereal productivity (ed. A.F. Hawkins and B Jeffeoat).Google Scholar
  54. Prentice, I.C., Cramer, W., Harrison, S.P., Leemans, R, Monserud, R.A., and Soloman, A.M.1992 : A global biome model based on plant physiology and dominance, soil properties and climate. Journal of Biogeography, 19, 117–134.CrossRefGoogle Scholar
  55. Raich, J.W., Rasterrer, E.B, Melillo, J.M., Kicklighter, D.W., Steudler, P.A., Peterson, B.J., Grace, A.L., Moore, B., and Vorosmarty C.J. 1991 : Potential net primary productivity in South America: application of a global model. Ecological Applications, 1, 399,429.CrossRefGoogle Scholar
  56. Ruimy, A., Dedieu, G., and Saugier, B. 1993 : Methodology for the estimation of terrestrial net primary production from remotely sensed data. Submitted to Journal of Geophysical Research.Google Scholar
  57. Running, S.W., and Coughlan, J.C. 1988 : A general model of forest ecosystem processes for regional applications. I. Hydrologic balance, canopy gas exchange and primary production processes.Ecological Modelling, 42, 125–154.CrossRefGoogle Scholar
  58. Running, S.W., and Gower, S.T. 1991 : A general model of forest ecosystem processes for regional applications. II. Dynamic C allocation and nitrogen budgets. Tree Physiology, 9, 147–160.Google Scholar
  59. Running, S.W., Nemani, R.R., Peterson, D.L., Band, L.E., Potts, D.F, and Oierce, L.L. 1989 : Mapping regional forest evapotranspiration and photosynthesis by coupling satellite data with ecosystem simulation. Ecology, 70, 1090–1101.CrossRefGoogle Scholar
  60. Saldarriaga, J.G., and Luxmoore, R.J. 1991 : Solar energy conversion efficiencies during succession of a tropical rain forest in Amazonia. Journal of Tropical Ecology, 7, 233– 242CrossRefGoogle Scholar
  61. Sellers, P.J. 1985 : Canopy reflectance, photosynthesis and transpiration. International Journal of Remote Sensing, 6, 1335–1372.CrossRefGoogle Scholar
  62. Sellers, P.J., 1987 : Canopy reflectance, photosynthesis and transpiration. H The role of biophysics in the linearity of their interdependence. Remote Sensing of Environment, 21, 143–183.CrossRefGoogle Scholar
  63. Sellers, P.J., Mintz, Y., Sud, Y.C., and Dalcher, A. 1986 : A simple biosphere model (SiB) for use within General Circulation Models. Journal of Atmospheric Sciences, 42, 505–531.CrossRefGoogle Scholar
  64. Spitters, C.J.T., van Keulen, H., and van Kraalingen, D.W.G. 1989 : A simple and universal crop growth simulator: SUCROS87, in Simulation and systems management in crop protection, R. Rabbinge, S.A. Ward and H.H. van Laar (Eds), Simulation Monographs 32, PUDOC, Wageningen.Google Scholar
  65. Taconet, O., Bernard, R., and Vidal-Modjar, D. 1986 : Evapotranspiration over an agricultural region using a surface flux/temperature model based on NOAA/AVHRR data. Journal of Climate and Applied Meteorology, 25, 284–307.CrossRefGoogle Scholar
  66. Talagrand, O. 1987 : Assimilation des observations meteorologiques. In Climatologie et Observations Spatiales. Summer School of CNES 1986. CEPADUES - Editions.Google Scholar
  67. Tans, P.T., Fung, I.Y., and Takahashi T. 1990 . Observational constraints on the global atmospheric C02 budget. Science, 247, 1431–1438.CrossRefGoogle Scholar
  68. Whitlock, C.H., Charlock, T., Staylor, W.F, Pinker, R.T., Laslo, I., DiPasquale, Ritchey. 1993 : WCRPSRB SW Data Product Description - Version 1.1 NASA TM 107747.Google Scholar
  69. Whitlock, C.H., Staylor, W.F., Darnell, W.L., Chou, M.D., Dedieu, G., Deschamps, P.Y., Ellis, J., Gautier, C., Frouin, R., Pinker, R.T., Laslo, I., Rossow, W.B., and Tarpley, D. 1990 : Comparison of surface radiation budget satellite algorithms for downwelled shortwave irradiance with Wisconsin FIRE/SRB surface-truth data. Proceedings of the Seventh Conference on Atmospheric Radiation, July 23–27, San Francisco, California. Published by the American Meteorological Society, Boston, Mass. Pp 237–242.Google Scholar
  70. Woodward F.I. 1987 : Climate and Plant DistributionCambridge University Press.Google Scholar

Copyright information

© ECSC, EEC, EAEC, Brussels and Luxembourg 1996

Authors and Affiliations

  • Gérard Dedieu
    • 1
  1. 1.Unité mixte CNES-CNRSLERTSToulouse CedexFrance

Personalised recommendations