Potential of Hyperion EO-1 hyperspectral data for wheat crop chlorophyll content estimation

Canadian Journal of Remote Sensing

Volumn 34, Issue , 2008, Pages S139-S157

  Bannari, A ^a   Khurshid, K S ^b   Staenz, K ^c   Schwarz, J ^d  

^a UNIVERSITY OF OTTAWA   (Canada)

^b AGRICULTURE AND AGRI FOOD CANADA   (Canada)

^c UNIVERSITY OF LETHBRIDGE   (Canada)

^d CANADA CENTRE FOR REMOTE SENSING   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL PRODUCTS; AGRICULTURE; ATMOSPHERICS; CROPS; DETECTORS; ESTIMATION; LABORATORIES; PORPHYRINS; REMOTE SENSING; SENSORS; SPACE OPTICS;

AGRICULTURAL FIELDS; CALIBRATION EQUATIONS; CHLOROPHYLL A; CHLOROPHYLL CONTENTS; COEFFICIENT OF DETERMINATION; EARTH OBSERVING 1 (EO-1); FIELD CONDITIONS; GROUND MEASUREMENTS; HYPER-SPECTRAL DATA; HYPERION (CO); HYPERION DATA; IMAGE DATA; LABORATORY ANALYSIS; LABORATORY MEASUREMENTS; LEAF CHLOROPHYLL; REMOTE SENSING (RS) DATA; RESIDUAL ERRORS; SASKATCHEWAN , CANADA; SHORT WAVE INFRA RED (SWIR); SURFACE REFLECTANCES; VISIBLE NEAR-INFRARED (VNIR); WIDE-RANGE;

CHLOROPHYLL;

EID: 47549115232     PISSN: 07038992     EISSN: 17127971     Source Type: Journal    
DOI: 10.5589/m08-001     Document Type: Article

References (83)

1. Araus, J.L., Casadesus, J., and Bort, J. 2001. Recent tools for the screening of physiological traits determining yield. In Application of physiology in wheat breeding. Edited by M.P. Reynolds, J.I. Ortiz-Monasterio, and A. McNab. CIMMYT, International Maize and Wheat Improvement Center, Mexico DF, Mexico. 240 p.
2. Arnon, D.I. 1949. Copper enzymes in isolated chloroplasts. Polyphenoloxidase in Beta vulgaris. Plant Physiology, Vol. 24, pp. 1-15.
3. Bannari, A., Morin, D., Bonn, F., and Huete, A.R. 1995. A review of vegetation indices. Remote Sensing Reviews, Vol. 13, pp. 95-120.
4. Bannari, A., Staenz, K., Haboudane, D., and Khurshid, K.S. 2006. Sensitivity analysis of chlorophyll indices to soil optical proprieties using hyperspectral data. In IGARSS’2006, Proceedings of the International Geoscience and Remote Sensing Symposium and the 27th Canadian Symposium on Remote Sensing, 31 July - 4 August 2006, Denver, Colo. IEEE, Piscatawy, N.J. pp. 120-123.
5. Bannari, A., Staenz, K., and Haboudane, D. 2007a. Analysis of impact of soil backgrounds on chlorophyll indices using field, airborne and satellite hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing. Submitted.
6. Bannari, A., Khurshid, K.S., Staenz, K., and Schwarz, J. 2007b. A comparison of hyperspectral chlorophyll indices for wheat crop chlorophyll content estimation using laboratory reflectance measurements. IEEE Transactions on Geoscience and Remote Sensing, Vol. 45, No. 10, pp. 3063-3074.
7. Baret, F. 2001. L’enjeufrangaisde L’agriculturede . Institut National de la Recherche Agronomique (INRA), Avignon, France. pp. 8-11.
8. Baret, F., Andrieu, B., and Guyot, G. 1988. A simple model for leaf optical properties in visible and near infrared: application to the analysis of spectral shifts determinism. In Applications of chlorophyll fluorescence. Edited by H.K. Lichtenthaler. Kluwer Academic Publishers, Dordrecht, The Netherlands. pp. 345-351.
9. Bavec, F., and Bavec, M. 2001. Chlorophyll meter readings of winter wheat cultivars and grain yield prediction. Communications in Soil Science and Plant Analycic, Vol. 32, No. 17-18, pp. 2709-2719.
10. Beck, R. 2003. EO-1 ncer guide, version 2.3. Available from http://eo1.usgs.gov and http://eo1.gsfc.nasa.gov. 74 pp.
11. Berk, A., Bernstein, L.S., and Robertson, D.C. 1989. MODTRAN: a moderate resolution model for LOWTRAN 7. Air Force Geophysics Laboratory (AFGL), Hanscom Air Force Base (AFB), Md. Final Report GL-TR-89-0122. 42 pp.
12. Blackburn, G.A. 1998a. Spectral indices for estimating photosynthetic pigment concentrations: a test using senescent tree leaves. International Journal of Remote Sensing, Vol. 19, pp. 657-675.
13. Blackburn, G.A. 1998b. Quantifying chlorophylls and carotenoids from leaf to canopy scales: an evaluation of some hyperspectral approaches. Remote Sensing of Environment, Vol. 66, pp. 273-285.
14. Blackburn, G.A. 1999. Relationships between spectral reflectance and pigment concentrations in stacks of deciduous broadleaves. Remote Sensing of Environment, Vol. 70, pp. 224-237.
15. Blackburn, G.A., and Steele, C.M. 1999. Towards the remote sensing of Matorral vegetation physiology: relationships between spectral reflectance, pigment, and biophysical characteristics of semiarid bush land canopies. Remote Sensing of Environment, Vol. 70, pp. 278-292.
16. Blackmer, T.M., Schepers, J.S., and Varel, G.E. 1994. Light reflectance compared with other nitrogen stress measurements in corn leaves. Agronomy Journal, Vol. 86, pp. 934-938.
17. Brisco, B., Brown, R.J., Hirose, T., McNairn, H., and Staenz, K. 1998. Precision agriculture and the role of remote sensing: a review. Canadian Journal of Remote Sensing, Vol. 24, No. 3, pp. 315-327.
18. Brown, R.J., McNairn, H., Wood, D., Staenz, K., and Deguise, J.-C. 1998. Assessing crop vigor from high spatial and high spectral optical imagery. In Proceedings of the 20th Canadian Symposium on Remote Sensing, 1114 May 1998, Calgary, Alta. Canadian Aeronautics and Space Institute (CASI), Ottawa, Ont. pp. 33-35.
19. Carter, G.A. 1994. Ratios of leaf reflectances in narrow wavebands as indicators of plant stress. International Journal of Remote Sensing, Vol. 5, No. 3, pp. 697-703.
20. Champagne, C. 2002. Remote sensing of plant water content for precision agriculture: the potential for hyperspectral modeling. M.A. thesis, Department of Geography, University of Ottawa, Ottawa, Ont. 114 pp.
21. Champagne, C., Staenz, K., Bannari, A., Deguise, J.-C., and McNairn, H. 2003. Validation of a hyperspectral curve-fitting model for the estimation of plant water content of agricultural canopies. Remote Sensing of Environment, Vol. 87, pp. 148-160.
22. Chappelle, E.W., Kim, M.S., and McMurtrey, J.E., III. 1992. Ratio analysis of reflectance spectra (RARS): an algorithm for the remote estimation of the concentrations of chlorophyll A, chlorophyll B, and the carotenoids in soybean leaves. Remote Sensing of Environment, Vol. 39, pp. 239-247.
23. Dash, J., and Curran, PJ. 2004. The MERIS terrestrial chlorophyll index. International Journal ofRemote Sensing, Vol. 25, No. 23, pp. 5403-5413.
24. Daughtry, C.S.T., Walthall, C.L., Kim, M.S., Brown de Colstoun, E., and McMurtrey, J.E., III. 2000. Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sensing of Environment, Vol. 74, pp. 229-239.
25. Draper, N.R., and Smith, H. 1981. Applied regression analysis. 2nd ed. Wiley, New York. 709 pp.
26. Filella, I., Serrano, L., Serra, J., and Penuelas, J. 1995. Evaluating wheat nitrogen status with canopy reflectance indices and discriminant analysis. Crop Science, Vol. 35, pp. 1400-1405.
27. Filella, I., Amaro, T., Araus, J.L., and Penuelas, J. 1996. Relationship between photosynthetic radiation-use efficiency of barley canopies and photochemical reflectance index (PRI). Physiologia Plantarum, Vol. 96, pp. 211-216.
28. Gamon, J.A., Penuelas, J., and Field, C.B. 1992. A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sensing of Environment, Vol. 41, pp. 35-44.
29. Gao, B.C., and Goetz, A.F.H. 1990. Column atmospheric water vapor and vegetation liquid water retrieval from airborne imaging spectrometer data. Journal of Geophysical Research, Vol. 95, pp. 3549-3564.
30. Gitelson, A., Merzyak, M.N., and Lichtenthaler, H.K. 1996. Detection of red-edge position and chlorophyll content by reflectance measurements near 700 nm. Journal of Plant Physiology, Vol. 148, pp. 501-508.
31. Goel, N.S. 1988. Models of vegetation canopy reflectance and their use in estimation of biophysical parameters from reflectance data. Remote Sensing Reviews, Vol. 4, No. 1, pp. 16-25.
32. Green, R.O., Conel, J.E., Margolis, J.S., Brugge, C.J., and Hoover, G.L. 1991. An inversion algorithm for the retrieval of atmospheric and leaf water absorption from AVIRIS radiance with compensation for atmospheric scattering. In Proceedings of the 3rd Annual Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Workshop, 20-21 May 1991, Pasadena, Calif. Jet Propulsion Laboratory (JPL), Pasadena, Calif. JPL Publication JPL-91-28, pp. 51-61.
33. Haboudane, D., Miller, J.R., Tremblay, N., Zarco-Tejada, P.J., and Dextraze, L. 2002. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sensing of Environment, Vol. 81, pp. 416-426.
34. Huang, W., Liu, L., Wang, J., Zhao, C., and Huang, M. 2004. Inversion of winter wheat yellow rust serious degrees by hyperspectral data. In IGAR04’04, Proceedings of the International Geoscience and Remote Sensing Symposium, 20-24 September 2004, Anchorage, Alaska. IEEE, Piscatawy, N.J. Vol. 6, pp. 4011-4014.
35. Jacquemoud, S., Ustin, S.L., Verdebout, J., Schmuck, G., Andreoli, G., and Hosgood, B. 1996. Estimating leaf biochemistry using PROSPECT leaf optical properties model. Remote Sensing ofEnvironment, Vol. 56, pp. 194-202.
36. Karimi, Y., Prasher, S.O., McNairn, H., Bonnell, R.B., Dutilleul, P., and Goel, P.K. 2005a. Discriminant analysis of hyperspectral data for assessing water and nitrogen stresses in corn. Transactions of the ASAE (American Society of Agricultural Engineers), Vol. 48, pp. 805-813.
37. Karimi, Y., Prasher, S.O., McNairn, H., Bonnell, R.B., Dutilleul, P., and Goel, P.K. 2005b. Classification accuracy of discriminant analysis, artificial neural networks and decision trees for weed and nitrogen stress detection in corn. Transactions of the ASAE (American Society of Agricultural Engineers), Vol. 48, pp. 1261-1268.
38. Khurshid, K.S. 2004. Estimation and mapping of wheat crop chlorophyll content using Hyperion hyperspectral data. M.Sc. thesis, Department of Geography, University of Ottawa, Ottawa, Ont. 158 pp.
39. Khurshid, K.S., Staenz, K., Sun, L., Neville, R., White, H.P., Bannari, A., Champagne, C.M., and Hitchcock, R. 2006. Preprocessing of EO-1 Hyperion data. Canadian Journal of Remote Sensing, Vol. 32, No. 2, pp. 84-97.
40. Kim, M.S., Daughtry, C.S.T., Chappelle, E.W., McMurtrey, J.E., III, and Walthall, C.L. 1994. The use of high spectral resolution bands for estimating absorbed photosynthetically active radiation (APAR). In Proceedings of the 6th ISPRS International Symposium on Physical Measurements and Signatures in Remote Sensing, 17-21 January 1994, Val D’Isere, France. pp. 299-306.
41. Kneubuhler, M. 2002. Spectral assessment of crop phenology based on spring wheat and winter barley. Ph.D. thesis, Remote Sensing Laboratory, Department of Geography, University of Zurich, Zurich, Switzerland. 148 pp.
42. Kruse, F.A., Boardman, J.W., and Huntington, J.F. 2003. Comparison of airborne hyperspectral data and EO-1 Hyperion for mineral mapping. IEEE Transactions on Geoscience and Remote Sensing, Vol. 41, pp. 1388-1400.
43. Markwell, J., Osterman, J.C., and Mitchell, J.L. 1995. Calibration of the Minolta SPAD-502 leaf chlorophyll meter. Photosynthesis Research, Vol. 46, pp. 467-472.
44. Martinez, D.E., and Guiamet, J.J. 2004. Distortion of SPAD 502 chlorophyll meter readings by changes in irradiance and leaf water status. Agronomy, Vol. 24, pp. 41-46.
45. McMurtrey, J.E., Chappelle, E., Daughtry, C., Kalshoven, J., Corp, L., and Kim, M. 2000. Field canopy and leaf level fluorescence for distinguishing plant condition differences due to nitrogen fertilization level. In IGARSS’94, Proceedings of the International Geoscience and Remote Sensing Symposium, 8-12 August 1994, Pasadena, Calif. IEEE, New York. pp. 982-985.
46. McNairn, H., and Brown, R.J. 1999. Remote sensing in support of crop management. In Proceedings of the United Nations - China - European Space Agency (ESA) Conference on Space Application for Promoting Sustainable Agriculture, 14-17 September 1999, Beijing. CD-ROM.
47. McNairn, H., Deguise, J.C., Pacheco, A., Shang, J., and Rabe, N. 2001. Estimation of crop cover and chlorophyll from hyperspectral remote sensing. In Proceedings of the 23rd Canadian Symposium on Remote Sensing, 21-24 August 2001, Ste-Foy, Que. 6 pp.
48. Moran, M.S., Vidal, A., Troufleau, D., Inoue, Y., and Mitchell, T. 1997. Combining multi-frequency microwave and optical data for farm management. Remote Sensing of Environment, Vol. 61, pp. 96-109.
49. Murdock, L., Jones, S., Bowley, C., Needham, P., James, J., and Howe, P 1997. Using a chlorophyll meter to make nitrogen recommendations on wheat. Available from www.specmeters.com/info/3.html.
50. Neville, R.A., Sun, L., and Staenz, K. 2004. Detection of keystone in imaging spectrometer data. In Proceedings of the SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X, 12-15 April 2004, Orlando, Fla. Proceedings of SPIE Volume 5425, pp. 208-217.
51. Neville, R.A., Sun, L., and Staenz, K. 2008. Spectral calibration of imaging spectrometers by atmospheric absorption feature matching. Canadian Journal of Remote Sensing, Vol. 34, Suppl. 1, pp. S29-S42.
52. Oppelt, N., and Mauser, W. 2001. The chlorophyll content of maize (Zea mays) derived with the airborne imaging spectrometer AVIS. In Proceedings of the 8th International Symposium on Physical Measurements & Signatures in Remote Sensing, 8-12 January 2001, Aussois, France. pp. 407-412.
53. Oppelt, N., and Mauser, W. 2004. Hyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data. International Journal of Remote Sensing, Vol. 25, pp. 145-159.
54. Oppelt, N., and Mauser, W. 2007. Characterization of sun and shade chlorophyll in wheat using angular CHRIS/PROBA data. In Proceedings of the Envisat Symposium 2007, 23-27 April 2007, Montreux, Switzerland. ESA SP-636. 6 pp.
55. Pacheco, A., Bannari, A., and McNairn, H. 2001. LAI measurements in beans and corn canopies with two optical instruments. In Proceedings of the 8th International Symposium on Physical Measurements & Signatures in Remote Sensing, 8-12 January 2001, Aussois, France. Centre National d’Études Spatiales (CNES) Publications, Toulouse, France. pp. 374-379.
56. Pacheco, A., Bannari, A., Staenz, K., McNairn, H., and Deguise, J.-C. 2002. Validating LAI using hyperspectral imagery over agricultural canopies. In Proceedings of the 1st International Symposium on Recent Advances in Quantitative Remote Sensing, 16-20 September 2002, Torrent, Valencia, Spain. pp. 210-215.
57. Pacheco, A., Bannari, A., Staenz, K., and McNairn, H. 2008. Deriving percent crop cover over agriculture canopies using hyperspectral remote sensing. Canadian Journal of Remote Sensing, Vol. 34, Suppl. 1, pp. 110-123.
58. PCI Geomatics. 2003. Using PCI software. PCI Geomatics, Richmond Hill, Ont. 551 pp.
59. Penuelas, J., Filella, I., Biel, C., Serrano, L., and Save, R. 1993. The reflectance at the 950-970 nm region as an indicator of plant water status. International Journal of Remote Sensing, Vol. 14, pp. 1887-1905.
60. Penuelas, J., Gamon, J., Freeden, A., Merino, J., and Field, C. 1994. Reflectance indices associated with physiological changes in nitrogen and water limited sunflower leaves. Remote Sensing of Environment, Vol. 48, pp. 135-146.
61. Penuelas, J., Baret, F., and Filella, I. 1995. Semi-empirical indices to assess carotenoids/chlorophyll a ratio from leaf spectral reflectance. Photosynthetica, Vol. 31, pp. 221-230.
62. Penuelas, J., Pinol, J., Ogaya, R., and Filella, I. 1997. Estimation of plant water concentration by the reflectance water index WI (R900/R970). International Journal of Remote Sensing, Vol. 18, pp. 2869-2875.
63. Peterson, T.A., Blackmer, T.M., Francis, D.D., and Schepers, J.S. 1993. Using a chlorophyll meter to improve N management. University of Nebraska, Lincoln, Nebr. Nebguide G93-1171A. Available from www.specmeters.com/info/3.html.
64. Richter, N. 2004. Delineation of the Kam Kotia mine tailings areas (Ontario, Canada) using hyperspectral TRWIS III data. M.Sc. thesis, Faculty of Mathematics and Natural Sciences, Institute for Geoecology, University of Potsdam, Potsdam, Germany. 98 pp.
65. Riedell, W.E., and Blackmer, TM. 1999. Leaf reflectance spectra of cereal aphid-damaged wheat. Crop Science, Vol. 39, pp. 1835-1840.
66. Rollin, E.M., and Milton, E.J. 1998. Processing of high spectral resolution reflectance data for the retrieval of canopy water content information. Remote Sensing of Environment, Vol. 65, pp. 86-92.
67. Rondeaux, G., Steven, M., and Baret, F. 1996. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment, Vol. 55, pp. 95-107.
68. Rouse, J.W., Hass, R.W., Schell, J.A., Deering, D.W., and Harlan, J.C. 1974. Monitoring the vernal advancement and retrogradation (greenwave effect) of natural vegetation. NASA/GSFC, Greenbelt, Md. Type III Final Report. 371 pp.
69. Spectrum Technologies Inc. 2001. Minolta meter. Spectrum Technologies Inc., East-Plainfield, III. Available from www.specmeters.com/Plant_Chlorophyll_meters/Minolta_SPAD_502_Meter.html.
70. Staenz, K., and Williams, D.J. 1997. Retrieval of surface reflectance from hyperspectral data using a look-up-table approach. Canadian Journal of Remote Sensing, Vol. 23, No. 4, pp. 354-368.
71. Staenz, K., Szeredi, T., and Schwarz, J. 1998. ISDAS — A system for processing/analyzing hyperspectral data. Canadian Journal of Remote of Sensing, Vol. 24, No. 2, pp. 99-113.
72. Staenz, K., Neville, R.A., Levesque, J., Szeredi, T., Singhroy, V., Borstad, G.A., and Hauff, P. 1999. Evaluation of casi and SFSI hyperspectral data for environmental and geological applications — two case studies. Canadian Journal of Remote Sensing, Vol. 25, pp. 311-322.
73. StatSoft, Inc. 1994. STATISTICA for Windows, release 5.0, user's manual. StatSoft, Inc., Tulsa, Okla. 1098 pp.
74. Sun L., Neville R.A., Staenz, K., and White, H.P. 2008. Automatic destriping of Hyperion imagery based on spectral moment matching. Canadian Journal of Remote Sensing, Vol. 34, Suppl. 1, pp. S68-S81.
75. Thie, J. 2006. CLI land capability of the Regina map sheet area, 72 I. Ecoinformatics International Inc., Ottawa, Ont. Available from www.geostrategis.com/c_cli-regina.htm#e.
76. Verstraete, M.M., Pinty, B., and Curran, P.J. 1999. MERIS potential for land application. International Journal of Remote Sensing, Vol. 20, No. 9, pp. 1747-1756.
77. Willmott, C.J. 1982. Some comments on the evaluation of model performance. Bulletin oftheAmericanMeteorologicalSociety, Vol. 63, No. 11, pp. 1309-1313.
78. Wood, C.W., Reeves, D.W., and Himelrick, D.G. 1993. Relationship between chlorophyll meter reading and leaf chlorophyll concentration, N status, and crop yield: a review. Proceedings ofthe Agronomy Society of New Zealand, Vol. 23, pp. 1-9.
79. Yoder, B.J., and Pettigrew-Crosby, R.E. 1995. Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (4002500 nm) at leaf and canopy scales. Remote Sensing of Environment, Vol. 53, pp. 199-211.
80. Young, A., and Britton, G. 1990. Carotenoids and stress. In stress responses in plants: adaptation and acclimation mechanisms. Edited by R.G. Alscher and J.R. Cumming. Wiley-Liss, New York. pp. 87-112.
81. Zarco-Tejada, P.J. 2000. Hyperspectral remote sensing of closed forest canopies: estimation of chlorophyll fluorescence and pigment content. Ph.D. thesis, York University, Toronto, Ont. 233 pp.
82. Zarco-Tejada, P.J., Miller, J.R., Noland, T.L., Mohammed, G.H., and Sampson, P.H. 2001. Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing, Vol. 39, pp. 1491-1507.
83. Zarco-Tejada, P.J., Berjón, A., López-Lozano, R., Miller, J.R., Martín, P., Cachorro, V., González, M.R., and de-Frutos, A. 2005. Assessing vineyard condition with hyperspectral indices: leaf and canopy reflectance simulation in a row-structured discontinuous canopy. Remote Sensing of Environment, Vol. 99, No. 3, pp. 271-287.