Research Article
BibTex RIS Cite

Monitoring Directional Dynamics of Growing Wheat Crop Canopy Using Ground based Time Series Remote Sensing Radiative Measurements

Year 2022, Volume: 9 Issue: 1, 25 - 39, 06.03.2022
https://doi.org/10.30897/ijegeo.877226

Abstract

Agricultural crop monitoring is an issue of extreme importance under global climate change, increased natural disasters and population explosion threatening global food security. In this paper, dynamic behaviour of spectro-directional reflectance properties of wheat canopy has been studied using radiometric measurements performed over a wheat field during the entire crop life cycle under varying viewing geometries. The study reveals that biological growth rhythm of wheat crop associated with continuous alteration in canopy condition particularly in terms of optical and morphological properties during the life cycle results in a distinct and systematic changing pattern of bidirectional responses in red and near Infrared (NIR). Analysis shows appreciable sensitivity of radiometric measurements both in the red and NIR regions to crop phenological transformation and changes. Soil background influenced the overall angular anisotropy pattern and manifested relatively high surface reflectance specifically at the early growth stage. At this stage, changes in viewing direction give rise to additional variability in directional reflectance due to varying proportion of soil-vegetation and enhanced contrast between wheat crop and its soil background. Both amplitude and angular pattern of directional response of the canopy undergo appreciable changes with time. Asymmetry in directional reflectance has been noticed in both the spectral regions on either side of nadir in the principal plane. In this connection, time varying angular characteristics of normalized difference vegetation index (NDVI) has also been studied in relation to crop growth.

Thanks

This paper is a contribution to the Biological Growth Rhythm Study Program of Bangladesh Space Research and Remote Sensing Organization (SPARRSO) and is financed by SPARRSO.

References

  • Anatoly A. Gitelson, Yoram J. Kaufman, Robert Starkc, Don Rundquista, 2002, Novel algorithms for remote estimation of vegetation fraction. Remote Sensing of Environment, 80, 76– 87.
  • Asrar, G., M. Fuchs, E. T. Kanemasu, and J. L. Hatfield, 1984, Estimating absorbed photosynthetic radiation and leaf area index from spectral reflectance in wheat, Agronomy Journal, 76, 300–306.
  • Bartlett, D. S., G. J. Whiting, and J. M. Hartman, 1990, Use of vegetation indices to estimate intercepted solar radiation and net carbon dioxide exchange of a grass canopy. Remote Sensing of Environment 30:115–128.
  • Billings, W.D., Morris R.J., 1951, Reflection of visible and infrared radiation from leaves of different ecological groups, Am. J. Bot., 38:327-331.
  • Boyer, M., Miller J., Belanger M., Hare E., Wu J., 1988, Senescence and spectral reflectance in leaves in Northen Pin Oak (Quercus palustris Muenchh.), Remote Sensing Environment, 25:71-87.
  • Breece, H.T. and Holmes R.A., 1971, Bidirectional scattering characteristics of healthy green soybeans and corn leaves in vivo, Applied Optics, 10(1): 119-127.
  • Breon, F.M., F. Maignan, M. Leroy and I. Grant, 2001, A Statistical Analysis of Hot Spot directional signatures measured from space. Proceedings of the 8th International Symposium:
  • Bunnik, N.,J.,J., 1978, The multispectral reflectance of shortwave radiation by agricultural crops in relation with their morphological and optical properties.
  • Camacho-de Coca, F., M. A. Gilabert and J. Meliá, 2001, Hot Spot Signature Dynamics with variyng LAI. Proceedings of the 8th International Symposium: Physical Measurements and Signatures in Remote Sensing. Aussois.
  • Chopping, M.J., Rango, A., Havstad, K.M., Schiebe, F.R., Ritchie, J.C., Schmugge, T.J., French, A.N. Su, L.H., McKee, L. and M.R. Davis, 2003, Canopy attributes of desert grassland and transition communities derived from multiangular airborne imagery. Remote Sensing of Environment, 85, 339-354.
  • Choudhury, B.,J., 1987, Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis. Remote Sensing of Environment, 22, 209-233.
  • Colwell, J. E., 1974, Vegetation canopy reflectance. Remote Sensing of Environment, 3, 175– 183.
  • Daughtry, C., S., T., and Biehl, L., L., 1985, Changes in spectral properties of detached birch leaves. Remote Sensing of Environment, 17, 281-289.
  • Daughtry, C. S. T., Vanderbilt, V. C. and V. J. Pollara, 1982, Variability of reflectance measurements with sensor altitude and canopy type. Agronomy Journal, 74, 744-751.
  • Daughtry, C. S. T., Bauer, M. E., Crecelius, D. W., and Hixson, M. M. 1980, Effects of management practices on reflectance of spring wheat canopies. Agronomy Journal, 72, 1055–1060.
  • Deering, D.,W. and T., F., Eck, 1987, Atmospheric optical depth effects on angular anisotropy of plant canopy reflectance. International Journal of Remote Sensing, Vol. 8, No. 6, 893-916.
  • Deering, D. W., Eck, T. F., and Banerjee, B., 1999, Characterization of the reflectance anisotropy of three boreal forest canopies in spring–summer. Remote Sensing of Environment, 67, 205–229.
  • Dickinson, R., E., 1983, Land surface processes and climate-surface albedo and energy balance. Adv. Geophys., 25, 305-353.
  • Diner, D., J., Martonchik, J., V., Borel, C., Gerstl, S., A., W., Gordon, H., R., Knyazikhin, Y., Myneni, R., Pinty, B., and M., M., Verstraete, 1998, MISR level 2 surface retrieval algorithm theoretical basis document. Technical Report, JPL D-11401, Rev. C, NASA Jet Propulsion Laboratory.
  • Diner, D., J., 1998, Multi-angle Imaging Spectro-Radiometer (MISR) instrument description and experiment overview, IEEE Transaction on Geoscience and Remote Sensing, 36, 1,072-1,087.
  • Fernandez, S.,Vidal, D., Simon, E.,&Sole-Sugranes, L., 1994, Radiometric characteristics of triticum aestivum cv. astral under water and nitrogen stress. International Journal of Remote Sensing, 15, 1867– 1884.
  • Gallo, K.P., Daughtry, C.S.T. and Bauer, M.E., 1985, Spectral estimation of absorbed photosynthetically active radiation in corn canopies. Remote Sensing of Environment, 17, 17,221-17,232.
  • Galvao, L.S., Ponzoni, F.J., Epiphanio, J.C.N., Rudorff, B.F.T. and A.R. Formaggio, 2004, Sun and view angle effects on NDVI determination of land cover types in the Brazilian Amazon region with hyperspectral data. International Journal of Remote Sensing, 25, 1861-1879.
  • Gates, D.,M., 1965, Energy, plants, and ecology, Ecology, 46(1&2):1-13.
  • Gausman, Harold W. 1985. Plant Leaf Optical Properties in Visible and Near-Infrared Light. Texas Tech Press: Lubock, Texas.
  • Gausman, H., W., Allen, W., A., Cardenas, R., and Richards, A., J., 1970, Relationship of light reflectance to histological and physical evaluations of cotton maturity (Gossypium hirsutum, L.), Applied Optics, 9, 545-552.
  • Gobron, N., Pinty, B., Verstraete, M., M. and Govaerts, Y., 1999, The MERIS Global vegetation Index (MGVI): Description and preliminary application. International Journal of Remote Sensing, 20, 1,917-1,027.
  • Gobron, N., Pinty, B., Verstraete, M., M., Martonchik, J., V., Knyyazikhin, Y. and Diner, D., J., 2000, Potential of multiangular spectral measurements to characterize land surfaces: Conceptual approach and exploratory application. Journal of Geophysical Research, Vol. 105, No. 13, 17,539-17,549.
  • Goel, N., S., 1987, Models of vegetation canopy reflectance and their use in estimation of biophysical parameters from reflectance data. Remote Sensing Review, 3, 1-212.
  • Goel, N., S. and D. W. Deering, 1985, Evaluation of a canopy reflectance model for LAI estimation through its inversion. IEEE Transaction on Geoscience Remote Sensing, GE-23, 674-684.
  • Grant, L., 1987, Diffuse and specular characteristics of leaf reflectance. Remote Sensing of Environment, 22, 309-322.
  • Hall,D.O. and Rao,K.K., 1987, Photosynthesis. New Studies in Biology Edward Arnold, Great Britain, pp.1-119.
  • Hatfield, J.,L., Asrar, G. and E.T. Kanemasu, 1984, Intercepted photosynthetically active radiation estimated by spectral reflectance. Remote Sensing of Environment, 14, 65-75.
  • Hoffer, R.M., 1978, Biological and physical considerations in applying computer-aided analysis techniques to remote sensor data. In Remote Sensing: The Quantitative Approach, edited by Swain, P.H. and Davis, S.M., McGraw Hill, New York, 227-289.
  • Holben, B., Kimes, D. and R., S., Fraser, 1986, Directional reflectance response in AVHRR Red and Near-IR bands for three cover types and varying atmospheric conditions. Remote Sensing of Environment, 19, 213-236.
  • Huete, A. Didan, K., Miura, T., Rodriguez, E.P., Gao, X. and L.G., Ferreira, 2002, Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83, 195-213.
  • Huete, A.R., 1988, A soil Adjusted vegetation index (SAVI). Remote Sensing of the Environment 25:295-309.
  • Huete, A. R., Jackson, R. D. and Post, D. F., 1985, Spectral response of plant canopy with different soil background. Remote Sensing of Environment, 17, 37–53.
  • Jackson, R. D. and Ezra, C. E., 1985, Spectral response of cotton to suddenly induced water stress. International Journal of Remote Sensing, 6, 177– 185.
  • Kanemasu, E. T., 1974, Seasonal canopy reflectance patterns of wheat, sorghum, and soybean. Remote Sensing of Environment, 3, 43–47.
  • Kimes, D.S., 1983, Dynamics of Directional Reflectance Factor Distributions for Vegetation Canopies. Applied Optics, vol. 22, nº.9, 1,364-1,372.
  • Khlopenkov, K., Trishchenko and Y. Luo, 2004, Analysis of BRDF and albedo properties of pure and mixed surface types from Terra MISR using Landsat high-resolution land cover and angular unmixing technique. Fourteenth ARM Science Team Meeting Proceedings, Albuquerque, New Mexico, March 22-26, 2004.
  • Kumar, L., Schmidt, K.S., Dury, S., Skidmore, A.K., 2001, Imaging spectrometry and vegetation science. In F. van de Meer. and S.M. de Jong (Eds). Imaging Spectrometry (Kluwer Academic Press: Dordrecht), pp 111-155.
  • Leamer, R. W., Noriega, J. R., and Gerbermann, A. H., 1980, Reflectance of wheat cultivars as related to physiological growth stages. Agronomy Journal, 72, 1029–1032.
  • Leblanc, S.G., J.M. Chen, P. White, J. Cihlar, R. Lacaze, J.L. Roujean and R. Latifovic, 2001, Mapping Vegetation Clumping Index from Directional Satellites Measurements. Proceedings of the 8th International Symposium: Physical Measurements and Signatures in Remote Sensing. Aussois.
  • Lee, T., Y. and Y., J., Kaufman, 1986, Non-lambertian effects on remote sensing of surface reflectance and vegetation index. IEEE Transaction on Geoscience and Remote Sensing, Vol. GE-24, No. 5, 699-708.
  • van Leeuwen, W. J. D., & Huete, A. R., 1996, Effects of standing litter on the biophysical interpretation of plant canopies with spectral indices. Remote Sensing of Environment, 55(2), 123-138.
  • Luo, Y., Trishchenko, A., P., Latifovic, R. and Z. Li , 2003, Surface Bi-Directional Reflectance Properties Over the ARM SGP Area from Satellite Multi-Platform Observations. Thirteenth ARM Science Team Meeting Proceedings, Broomfield, Colorado, March 31-April 4, 2003. Maas, S.J. and Dunlap J.R., 1989, Reflectance, transmittance, and absorptance of light by normal, etiolated, and albino corn leaves, Agronomy Journal, 81:105-110.
  • Martonchik, J., D., Diner, D., Pinty, B., Verstraete, M., M., Myneni, R., Knyazikhin, Y., and H. Godron, 1998, Determination of land and ocean reflective, and biophysical properties using multiangular imaging. IEEE Transaction on Geoscience and Remote Sensing, 36, 1,266-1,281.
  • Myers, V. Ed.,1983, Remote sensing applications in agriculture. In Manual of Remote Sensing, 2nd ed. (R. N. Colwell, Ed.), American Society of Photogrammetry, The Sheridan Press, Falls Church, VA.
  • D.I., Pagano, R.J. and Reilly, T.H., 1989, MISR: A Multiangle Imaging Spectroradiometer for Geophysical and Climatological Research from EOS. I.E.E.E. Transactions on Geoscience and Remote Sensing, 27, 200-214.
  • Pinty, B., Verstraete, M., M. and R., E., Dickinson, 1990, A physical model of the bidirectional reflectance of vegetation canopies 2. Inversion and validation. Journal of Geophysical Research, 95, No. D8, 11,767-11,775.
  • Pinty, B., Gobron, G., Widlowski, J., L., Gerstl, S., A., W., Verstraete, M., M., Antunes, M., Bacour, C., Gascon, F., Gastellu, J., P., Goel, N., Jacquemoud, S., North, P., Qin, W. and R. Thompson, 2001, Radiation transfer model intercomparison (RAMI) exercise. Journal of Geophysical Research, Vol. 196, No. D11, 11,937-11,956.
  • Rahman, H., 2001, Influence of Atmospheric Correction on the Estimation of Biophysical Parameters of Crop Canopy Using Satellite Remote Sensing. International Journal of Remote Sensing, Vol. 22, No. 7, 1245-1268.
  • Rahman, H., Quadir, D.A., Islam, A.Z.Md. and Sukumar Dutta, 1999, Viewing Angle Effect on the Remote Sensing Monitoring of Wheat and Rice Crops. Geocarto International, Vol. 14, No. 1, 75-79.
  • Rahman, H., 1996, Atmospheric optical depth and water vapour effects on the angular characteristics of surface reflectance on NOAA AVHRR channel 1 and channel 2. International Journal of Remote Sensing, 17, 2,981-2,999.
  • Rahman, H. and G. Dedieu, 1994, SMAC: A simplified method for the atmospheric correction of satellite measurements in the solar spectrum. International Journal Remote Sensing, Vol. 15, pp 123-143.
  • Rahman, H., Pinty, B. and M.M. Verstraete. 1993a. Coupled surface-atmosphere reflectance (CSAR) model 1. Model description and inversion on synthetic data. Journal of Geophysical Research, Vol. 98, No. D11, pp 20,779-20,789.
  • Rahman, H., Pinty, B. and M.M. Verstraete, 1993b, Coupled surface-atmosphere reflectance (CSAR) model 2. Semiempirical surface model usable with NOAA Advanced Very High Resolution Radiometer Data. Journal of Geophysical Research, 98, 20,791-20,801.
  • Ranson, K., J., Biehl, L., L. and C.S.T. Daughtry, 1984, Soybean canopy reflectance modeling datasets. Technical Report 07158, 22 pp., Laboratory of Applied Remote Sensing, Purdue University, West Lafayette, Ind.
  • Ranson, K., J., C. S. T. Daughtry, L. L. Biehl, and M. E. Bauer, 1985, Sun-view angle effects on reflectance factors of corn canopies. Remote Sensing Environment, vol. 18, 147- 161.
  • Ranson, K., J., Daughtry, C., S., T. and L. L. Biehl, 1986, Sun angle, view angle and background effects on response of simulated balsam fir canopies. Photogrammetic. Engineering and Remote Sensing, 52, 649-658.
  • Ross, J.,K., 1981, The Radiation Regime and Architecture of Plant Stands. Kluwer, Boston, MA, U.S.A.
  • Sandmeier, S., C. Müller, Hosgood, B. and G. Andreoli, 1998, Physical mechanisms in Hyperspectral BRDF Data of Grass and Watercress. Remote Sensing of Environment, 66: 222-223.
  • Sanger, J.,E, 1971, Quantitative investigations of leaf pigments from their inception in buds through autumn coloration to decomposition in falling leaves. Ecology, 52, 1075–1081.
  • Sellers, P.J., 1985, Canopy reflectance, photosynthesis and transpiration. International Journal of Remote Sensing, 6, 1335-1372.
  • Sellers, P.,J., 1987, Canopy reflectance, photosynthesis, and transpiration II: The role of biophysics in the linearity of their interdependence. Remote Sensing Environment, 21, 143-183.
  • Sinclair, T., R., Hoffer, R., M., and Screiber, M., M., 1971, Reflectance and internal structure of leaves from several crops during a growing season. Agronomy Journal, 63, 864-868. Stricker, N., Hahne, A., Smith, D., Delderfield, J., Oliver, M., and T., Edwards, 1995, ATSR-2: The evolution and its design from ERS-1 to ERS-2, ESA Bulletin, 83, 32-37.
  • Tanré, D., M. Herman, and P. Y. Deschamps, 1983, Influence of the atmosphere on space measurements of directional properties. Applied Optics, 22, 733 741.
  • Tucker, C.J. and P., J., Sellers, 1986, Satellite remote sensing of primary production. International Journal of Remote Sensing, 7, 1,395-1,416.
  • Tucker, C. J., Holben, B. N., Elgin, J. H. J. and McMurtrey, J. E. III, 1981, Remote sensing of total dry-matter accumulation in winter wheat. Remote Sensing of Environment, 11, 171– 189.
  • Weiss, M., Baret, F., Myneni, R.B., Pragnere, A., Knyazikhin, Y., 2000, Investigation of a model inversion technique to estimate canopy biophysical variables from spectral and directional reflectance data. Agronomie, 20, 3–22.
  • Vogelmann, T.C. and Björn L.O., 1986, Plants as light traps, Physiol. Plantarum, 68:704-708.
  • Widlowski, J., L., Pinty, B., Gobron, N., Verstraete, M., M., and A., B., Davis, 2001, Characterization of surface heterogeneity detected at the MISR/TERRA subpixel scale. Geophysical Research Letters, Vol. 28, Number 24, 4,639-4,642.
Year 2022, Volume: 9 Issue: 1, 25 - 39, 06.03.2022
https://doi.org/10.30897/ijegeo.877226

Abstract

References

  • Anatoly A. Gitelson, Yoram J. Kaufman, Robert Starkc, Don Rundquista, 2002, Novel algorithms for remote estimation of vegetation fraction. Remote Sensing of Environment, 80, 76– 87.
  • Asrar, G., M. Fuchs, E. T. Kanemasu, and J. L. Hatfield, 1984, Estimating absorbed photosynthetic radiation and leaf area index from spectral reflectance in wheat, Agronomy Journal, 76, 300–306.
  • Bartlett, D. S., G. J. Whiting, and J. M. Hartman, 1990, Use of vegetation indices to estimate intercepted solar radiation and net carbon dioxide exchange of a grass canopy. Remote Sensing of Environment 30:115–128.
  • Billings, W.D., Morris R.J., 1951, Reflection of visible and infrared radiation from leaves of different ecological groups, Am. J. Bot., 38:327-331.
  • Boyer, M., Miller J., Belanger M., Hare E., Wu J., 1988, Senescence and spectral reflectance in leaves in Northen Pin Oak (Quercus palustris Muenchh.), Remote Sensing Environment, 25:71-87.
  • Breece, H.T. and Holmes R.A., 1971, Bidirectional scattering characteristics of healthy green soybeans and corn leaves in vivo, Applied Optics, 10(1): 119-127.
  • Breon, F.M., F. Maignan, M. Leroy and I. Grant, 2001, A Statistical Analysis of Hot Spot directional signatures measured from space. Proceedings of the 8th International Symposium:
  • Bunnik, N.,J.,J., 1978, The multispectral reflectance of shortwave radiation by agricultural crops in relation with their morphological and optical properties.
  • Camacho-de Coca, F., M. A. Gilabert and J. Meliá, 2001, Hot Spot Signature Dynamics with variyng LAI. Proceedings of the 8th International Symposium: Physical Measurements and Signatures in Remote Sensing. Aussois.
  • Chopping, M.J., Rango, A., Havstad, K.M., Schiebe, F.R., Ritchie, J.C., Schmugge, T.J., French, A.N. Su, L.H., McKee, L. and M.R. Davis, 2003, Canopy attributes of desert grassland and transition communities derived from multiangular airborne imagery. Remote Sensing of Environment, 85, 339-354.
  • Choudhury, B.,J., 1987, Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis. Remote Sensing of Environment, 22, 209-233.
  • Colwell, J. E., 1974, Vegetation canopy reflectance. Remote Sensing of Environment, 3, 175– 183.
  • Daughtry, C., S., T., and Biehl, L., L., 1985, Changes in spectral properties of detached birch leaves. Remote Sensing of Environment, 17, 281-289.
  • Daughtry, C. S. T., Vanderbilt, V. C. and V. J. Pollara, 1982, Variability of reflectance measurements with sensor altitude and canopy type. Agronomy Journal, 74, 744-751.
  • Daughtry, C. S. T., Bauer, M. E., Crecelius, D. W., and Hixson, M. M. 1980, Effects of management practices on reflectance of spring wheat canopies. Agronomy Journal, 72, 1055–1060.
  • Deering, D.,W. and T., F., Eck, 1987, Atmospheric optical depth effects on angular anisotropy of plant canopy reflectance. International Journal of Remote Sensing, Vol. 8, No. 6, 893-916.
  • Deering, D. W., Eck, T. F., and Banerjee, B., 1999, Characterization of the reflectance anisotropy of three boreal forest canopies in spring–summer. Remote Sensing of Environment, 67, 205–229.
  • Dickinson, R., E., 1983, Land surface processes and climate-surface albedo and energy balance. Adv. Geophys., 25, 305-353.
  • Diner, D., J., Martonchik, J., V., Borel, C., Gerstl, S., A., W., Gordon, H., R., Knyazikhin, Y., Myneni, R., Pinty, B., and M., M., Verstraete, 1998, MISR level 2 surface retrieval algorithm theoretical basis document. Technical Report, JPL D-11401, Rev. C, NASA Jet Propulsion Laboratory.
  • Diner, D., J., 1998, Multi-angle Imaging Spectro-Radiometer (MISR) instrument description and experiment overview, IEEE Transaction on Geoscience and Remote Sensing, 36, 1,072-1,087.
  • Fernandez, S.,Vidal, D., Simon, E.,&Sole-Sugranes, L., 1994, Radiometric characteristics of triticum aestivum cv. astral under water and nitrogen stress. International Journal of Remote Sensing, 15, 1867– 1884.
  • Gallo, K.P., Daughtry, C.S.T. and Bauer, M.E., 1985, Spectral estimation of absorbed photosynthetically active radiation in corn canopies. Remote Sensing of Environment, 17, 17,221-17,232.
  • Galvao, L.S., Ponzoni, F.J., Epiphanio, J.C.N., Rudorff, B.F.T. and A.R. Formaggio, 2004, Sun and view angle effects on NDVI determination of land cover types in the Brazilian Amazon region with hyperspectral data. International Journal of Remote Sensing, 25, 1861-1879.
  • Gates, D.,M., 1965, Energy, plants, and ecology, Ecology, 46(1&2):1-13.
  • Gausman, Harold W. 1985. Plant Leaf Optical Properties in Visible and Near-Infrared Light. Texas Tech Press: Lubock, Texas.
  • Gausman, H., W., Allen, W., A., Cardenas, R., and Richards, A., J., 1970, Relationship of light reflectance to histological and physical evaluations of cotton maturity (Gossypium hirsutum, L.), Applied Optics, 9, 545-552.
  • Gobron, N., Pinty, B., Verstraete, M., M. and Govaerts, Y., 1999, The MERIS Global vegetation Index (MGVI): Description and preliminary application. International Journal of Remote Sensing, 20, 1,917-1,027.
  • Gobron, N., Pinty, B., Verstraete, M., M., Martonchik, J., V., Knyyazikhin, Y. and Diner, D., J., 2000, Potential of multiangular spectral measurements to characterize land surfaces: Conceptual approach and exploratory application. Journal of Geophysical Research, Vol. 105, No. 13, 17,539-17,549.
  • Goel, N., S., 1987, Models of vegetation canopy reflectance and their use in estimation of biophysical parameters from reflectance data. Remote Sensing Review, 3, 1-212.
  • Goel, N., S. and D. W. Deering, 1985, Evaluation of a canopy reflectance model for LAI estimation through its inversion. IEEE Transaction on Geoscience Remote Sensing, GE-23, 674-684.
  • Grant, L., 1987, Diffuse and specular characteristics of leaf reflectance. Remote Sensing of Environment, 22, 309-322.
  • Hall,D.O. and Rao,K.K., 1987, Photosynthesis. New Studies in Biology Edward Arnold, Great Britain, pp.1-119.
  • Hatfield, J.,L., Asrar, G. and E.T. Kanemasu, 1984, Intercepted photosynthetically active radiation estimated by spectral reflectance. Remote Sensing of Environment, 14, 65-75.
  • Hoffer, R.M., 1978, Biological and physical considerations in applying computer-aided analysis techniques to remote sensor data. In Remote Sensing: The Quantitative Approach, edited by Swain, P.H. and Davis, S.M., McGraw Hill, New York, 227-289.
  • Holben, B., Kimes, D. and R., S., Fraser, 1986, Directional reflectance response in AVHRR Red and Near-IR bands for three cover types and varying atmospheric conditions. Remote Sensing of Environment, 19, 213-236.
  • Huete, A. Didan, K., Miura, T., Rodriguez, E.P., Gao, X. and L.G., Ferreira, 2002, Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, 83, 195-213.
  • Huete, A.R., 1988, A soil Adjusted vegetation index (SAVI). Remote Sensing of the Environment 25:295-309.
  • Huete, A. R., Jackson, R. D. and Post, D. F., 1985, Spectral response of plant canopy with different soil background. Remote Sensing of Environment, 17, 37–53.
  • Jackson, R. D. and Ezra, C. E., 1985, Spectral response of cotton to suddenly induced water stress. International Journal of Remote Sensing, 6, 177– 185.
  • Kanemasu, E. T., 1974, Seasonal canopy reflectance patterns of wheat, sorghum, and soybean. Remote Sensing of Environment, 3, 43–47.
  • Kimes, D.S., 1983, Dynamics of Directional Reflectance Factor Distributions for Vegetation Canopies. Applied Optics, vol. 22, nº.9, 1,364-1,372.
  • Khlopenkov, K., Trishchenko and Y. Luo, 2004, Analysis of BRDF and albedo properties of pure and mixed surface types from Terra MISR using Landsat high-resolution land cover and angular unmixing technique. Fourteenth ARM Science Team Meeting Proceedings, Albuquerque, New Mexico, March 22-26, 2004.
  • Kumar, L., Schmidt, K.S., Dury, S., Skidmore, A.K., 2001, Imaging spectrometry and vegetation science. In F. van de Meer. and S.M. de Jong (Eds). Imaging Spectrometry (Kluwer Academic Press: Dordrecht), pp 111-155.
  • Leamer, R. W., Noriega, J. R., and Gerbermann, A. H., 1980, Reflectance of wheat cultivars as related to physiological growth stages. Agronomy Journal, 72, 1029–1032.
  • Leblanc, S.G., J.M. Chen, P. White, J. Cihlar, R. Lacaze, J.L. Roujean and R. Latifovic, 2001, Mapping Vegetation Clumping Index from Directional Satellites Measurements. Proceedings of the 8th International Symposium: Physical Measurements and Signatures in Remote Sensing. Aussois.
  • Lee, T., Y. and Y., J., Kaufman, 1986, Non-lambertian effects on remote sensing of surface reflectance and vegetation index. IEEE Transaction on Geoscience and Remote Sensing, Vol. GE-24, No. 5, 699-708.
  • van Leeuwen, W. J. D., & Huete, A. R., 1996, Effects of standing litter on the biophysical interpretation of plant canopies with spectral indices. Remote Sensing of Environment, 55(2), 123-138.
  • Luo, Y., Trishchenko, A., P., Latifovic, R. and Z. Li , 2003, Surface Bi-Directional Reflectance Properties Over the ARM SGP Area from Satellite Multi-Platform Observations. Thirteenth ARM Science Team Meeting Proceedings, Broomfield, Colorado, March 31-April 4, 2003. Maas, S.J. and Dunlap J.R., 1989, Reflectance, transmittance, and absorptance of light by normal, etiolated, and albino corn leaves, Agronomy Journal, 81:105-110.
  • Martonchik, J., D., Diner, D., Pinty, B., Verstraete, M., M., Myneni, R., Knyazikhin, Y., and H. Godron, 1998, Determination of land and ocean reflective, and biophysical properties using multiangular imaging. IEEE Transaction on Geoscience and Remote Sensing, 36, 1,266-1,281.
  • Myers, V. Ed.,1983, Remote sensing applications in agriculture. In Manual of Remote Sensing, 2nd ed. (R. N. Colwell, Ed.), American Society of Photogrammetry, The Sheridan Press, Falls Church, VA.
  • D.I., Pagano, R.J. and Reilly, T.H., 1989, MISR: A Multiangle Imaging Spectroradiometer for Geophysical and Climatological Research from EOS. I.E.E.E. Transactions on Geoscience and Remote Sensing, 27, 200-214.
  • Pinty, B., Verstraete, M., M. and R., E., Dickinson, 1990, A physical model of the bidirectional reflectance of vegetation canopies 2. Inversion and validation. Journal of Geophysical Research, 95, No. D8, 11,767-11,775.
  • Pinty, B., Gobron, G., Widlowski, J., L., Gerstl, S., A., W., Verstraete, M., M., Antunes, M., Bacour, C., Gascon, F., Gastellu, J., P., Goel, N., Jacquemoud, S., North, P., Qin, W. and R. Thompson, 2001, Radiation transfer model intercomparison (RAMI) exercise. Journal of Geophysical Research, Vol. 196, No. D11, 11,937-11,956.
  • Rahman, H., 2001, Influence of Atmospheric Correction on the Estimation of Biophysical Parameters of Crop Canopy Using Satellite Remote Sensing. International Journal of Remote Sensing, Vol. 22, No. 7, 1245-1268.
  • Rahman, H., Quadir, D.A., Islam, A.Z.Md. and Sukumar Dutta, 1999, Viewing Angle Effect on the Remote Sensing Monitoring of Wheat and Rice Crops. Geocarto International, Vol. 14, No. 1, 75-79.
  • Rahman, H., 1996, Atmospheric optical depth and water vapour effects on the angular characteristics of surface reflectance on NOAA AVHRR channel 1 and channel 2. International Journal of Remote Sensing, 17, 2,981-2,999.
  • Rahman, H. and G. Dedieu, 1994, SMAC: A simplified method for the atmospheric correction of satellite measurements in the solar spectrum. International Journal Remote Sensing, Vol. 15, pp 123-143.
  • Rahman, H., Pinty, B. and M.M. Verstraete. 1993a. Coupled surface-atmosphere reflectance (CSAR) model 1. Model description and inversion on synthetic data. Journal of Geophysical Research, Vol. 98, No. D11, pp 20,779-20,789.
  • Rahman, H., Pinty, B. and M.M. Verstraete, 1993b, Coupled surface-atmosphere reflectance (CSAR) model 2. Semiempirical surface model usable with NOAA Advanced Very High Resolution Radiometer Data. Journal of Geophysical Research, 98, 20,791-20,801.
  • Ranson, K., J., Biehl, L., L. and C.S.T. Daughtry, 1984, Soybean canopy reflectance modeling datasets. Technical Report 07158, 22 pp., Laboratory of Applied Remote Sensing, Purdue University, West Lafayette, Ind.
  • Ranson, K., J., C. S. T. Daughtry, L. L. Biehl, and M. E. Bauer, 1985, Sun-view angle effects on reflectance factors of corn canopies. Remote Sensing Environment, vol. 18, 147- 161.
  • Ranson, K., J., Daughtry, C., S., T. and L. L. Biehl, 1986, Sun angle, view angle and background effects on response of simulated balsam fir canopies. Photogrammetic. Engineering and Remote Sensing, 52, 649-658.
  • Ross, J.,K., 1981, The Radiation Regime and Architecture of Plant Stands. Kluwer, Boston, MA, U.S.A.
  • Sandmeier, S., C. Müller, Hosgood, B. and G. Andreoli, 1998, Physical mechanisms in Hyperspectral BRDF Data of Grass and Watercress. Remote Sensing of Environment, 66: 222-223.
  • Sanger, J.,E, 1971, Quantitative investigations of leaf pigments from their inception in buds through autumn coloration to decomposition in falling leaves. Ecology, 52, 1075–1081.
  • Sellers, P.J., 1985, Canopy reflectance, photosynthesis and transpiration. International Journal of Remote Sensing, 6, 1335-1372.
  • Sellers, P.,J., 1987, Canopy reflectance, photosynthesis, and transpiration II: The role of biophysics in the linearity of their interdependence. Remote Sensing Environment, 21, 143-183.
  • Sinclair, T., R., Hoffer, R., M., and Screiber, M., M., 1971, Reflectance and internal structure of leaves from several crops during a growing season. Agronomy Journal, 63, 864-868. Stricker, N., Hahne, A., Smith, D., Delderfield, J., Oliver, M., and T., Edwards, 1995, ATSR-2: The evolution and its design from ERS-1 to ERS-2, ESA Bulletin, 83, 32-37.
  • Tanré, D., M. Herman, and P. Y. Deschamps, 1983, Influence of the atmosphere on space measurements of directional properties. Applied Optics, 22, 733 741.
  • Tucker, C.J. and P., J., Sellers, 1986, Satellite remote sensing of primary production. International Journal of Remote Sensing, 7, 1,395-1,416.
  • Tucker, C. J., Holben, B. N., Elgin, J. H. J. and McMurtrey, J. E. III, 1981, Remote sensing of total dry-matter accumulation in winter wheat. Remote Sensing of Environment, 11, 171– 189.
  • Weiss, M., Baret, F., Myneni, R.B., Pragnere, A., Knyazikhin, Y., 2000, Investigation of a model inversion technique to estimate canopy biophysical variables from spectral and directional reflectance data. Agronomie, 20, 3–22.
  • Vogelmann, T.C. and Björn L.O., 1986, Plants as light traps, Physiol. Plantarum, 68:704-708.
  • Widlowski, J., L., Pinty, B., Gobron, N., Verstraete, M., M., and A., B., Davis, 2001, Characterization of surface heterogeneity detected at the MISR/TERRA subpixel scale. Geophysical Research Letters, Vol. 28, Number 24, 4,639-4,642.
There are 74 citations in total.

Details

Primary Language English
Subjects Photogrammetry and Remote Sensing
Journal Section Research Articles
Authors

Hafızur Rahman 0000-0003-3366-4076

Publication Date March 6, 2022
Published in Issue Year 2022 Volume: 9 Issue: 1

Cite

APA Rahman, H. (2022). Monitoring Directional Dynamics of Growing Wheat Crop Canopy Using Ground based Time Series Remote Sensing Radiative Measurements. International Journal of Environment and Geoinformatics, 9(1), 25-39. https://doi.org/10.30897/ijegeo.877226