Remote estimation of nitrogen and chlorophyll contents in maize at leaf and canopy levels

International Journal of Applied Earth Observation and Geoinformation

Volumn 25, Issue 1, 2013, Pages 47-54

  Schlemmera, M ^a   Gitelson, A ^b   Schepersa, J ^a   Fergusona, R ^a   Peng, Y ^b   Shanahana, J ^b   Rundquist, D ^b  

^a UNIVERSITY OF NEBRASKA LINCOLN   (United States)

^b UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

Chlorophyll; Nitrogen; Reflectance; Remote sensing; Vegetation index

Indexed keywords

CANOPY; CHLOROPHYLL; ESTIMATION METHOD; LEAF; MAIZE; NITROGEN; REFLECTANCE; REMOTE SENSING; SPECTRAL ANALYSIS; VEGETATION INDEX;

ZEA MAYS;

EID: 84888220912     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2013.04.003     Document Type: Article

References (49)

1. Arnold, S.L., Schepers, J.S., 2004. A simple roller-miller grinding procedure for plant and soil samples. Communications in Soil Science and Plant Analysis 35, 537-545.
2. Baret, F., Houlès, V., Guérif, M., 2007. Quantification of plant stress using remote sensing observations and crop models: the case of nitrogen management. Journal of Experimental Botany 58, 869-880.
3. Blackburn, G.A., 2006. Hyperspectral remote sensing of plant pigments. Journal of Experimental Botany 58, 855-867.
4. Ciganda, V., Gitelson, A., Schepers, J., 2009. Non-destructive determination of maize leaf and canopy chlorophyll content. Journal Plant Physiology 166, 157-167.
5. Ciganda, V.S., Gitelson, A.A., Schepers, J., 2012. How deep does a remote sensor sense? Expression of chlorophyll content in a maize canopy. Remote Sensing of Environment 126, 240-247.
6. Clevers, J.G.P.W., de Jong, S.M., Epema, G.F., van der Meer, F., Bakker, W.H., Skidmore, A.K., Addink, E.A., 2001. MERIS and the red-edge position. International Journal of Applied Earth Observation and Geoinformation 3, 313-320.
7. Clevers, J.G.P.W., Gitelson, A.A., 2013. Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3. International Journal of Applied Earth Observation and Geoinformation 23, 344-351.
8. Clevers, J.G.P.W., Kooistra, L., 2012. Using hyperspectral remote sensing data for retrieving canopy chlorophyll and nitrogen content. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5, 574-583.
9. Dash, J., Curran, P.J., 2004. The MERIS terrestrial chlorophyll index. International Journal of Remote Sensing 25, 5403-5413.
10. Evans, J.R., 1983. Nitrogen and photosynthesis in the flag leaf of wheat (Triticum aestivum L.). Plant Physiology 72, 297-302.
11. Evans, J.R., 1989. Photosynthesis and nitrogen relationships in leaves of C3 plants. Oecologia 78, 9-19.
12. Féret, J-B., François, C., Gitelson, A.A., Barry, K.M., Panigada, C., Richardson, A.D., Jacquemoud, S., 2011. Optimizing spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling. Remote Sensing of Environment 115, 2742-2750.
13. Field, C.B., Mooney, H.A., 1986. The photosynthesisp-nitrogen relationship in wild plants. In: Givnish, T.J. (Ed.), On the eEconomy of Plant Form and Function. Cambridge University Press, Cambridge, pp. 25-55.
14. Gitelson, A.A., Verma, S.B., Vina, A., Rundquist, D.C., Keydan, G., Leavitt, B., Arkebauer, T.J., Burba, G.G., Suyker, A.E., 2003a. Novel technique for remote estimation of CO2 flux in maize. Geophysical Research Letters 30 (9), 1486, http://dx.doi.org/10.1029/2002GL016543.
15. Gitelson, A.A., Gritz, Y., Merzlyak, M.N., 2003b. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. Journal Plant Physiology 160, 271-282.
16. Gitelson, A.A., Viñ;a, A., Ciganda, V., Rundquist, D.C., Arkebauer, T.J., 2005. Remote estimation of canopy chlorophyll content in crops. Geophysical Research Letters 32, L08403, http://dx.doi.org/10.1029/2005GL022688.
17. Gitelson, A.A., Viñ;a, A., Verma, S.B., Rundquist, D.C., Arkebauer, T.J., Keydan, G., Leavitt, B., Ciganda, V., Burba, G.G., Suyker, A.E., 2006a. Relationship between gross primary production and chlorophyll content in crops: implications for the synoptic monitoring of vegetation productivity. Journal of Geophysical Research 111, D08S11, http://dx.doi.org/10.1029/2005JD006017.
18. Gitelson, A.A., Keydan, G.P., Merzlyak, M.N., 2006b. Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves. Geophysical Research Letters 33, L11402, http://dx.doi.org/10.1029/2006GL026457.
19. Gitelson, A.A., 2011a. Non-destructive estimation of foliar pigment (chlorophylls, carotenoids and anthocyanins) contents: espousing a semi-analytical threeband model. In: Thenkabail, P.S., Lyon, J.G., Huete, A. (Eds.), Chapter 6 in Hyperspectral Remote Sensing of Vegetation. Taylor and Francis, CRC Press-Taylor and Francis group, Boca Raton, London, New York, pp. 141-165.
20. Gitelson, A.A., 2011b. Remote Sensing estimation of crop biophysical characteristics at various scales. In: Thenkabail, P.S., Lyon, J.G., Huete, A. (Eds.), Chapter 15 in Hyperspectral Remote Sensing of Vegetation. Taylor and Francis, CRC Press-Taylor and Francis group, Boca Raton, London, New York, pp. 329-358.
21. Guyot, G., Baret, F., 1988. Utilisation de la haute resolution spectrale pour suivre l'etat des couverts vegetaux. In: Proceedings 4th International Colloquium 'Spectral Signatures of Objects in Remote Sensing', Aussois, France, pp. 279-286 (ESA, Paris).
22. Hatfield, J.L., Gitelson, A.A., Schepers, J.S., Walthall, C.L., 2008. Application of spectral remote sensing for agronomic decisions. Agronomy Journal 100, S-131-S-117.
23. Huete, A.R., Liu, H.Q., Batchily, K., van Leeuwen, W., 1997. A comparison of vegetation indices global set of TM images for EOS-MODIS. Remote Sensing of Environment 59, 440-451.
24. Inoue, Y., Sakaiy, E., Zhu, Y., Takahashi, W., 2012. Diagnostic mapping of canopy nitrogen content in rice based on hyperspectral measurements. Remote Sensing of Environment 126, 210-221.
25. Jiang, Z., Huete, A.R., Didan, K., Miura, T., 2008. Development of a two-band enhanced vegetation index without a blue band. Remote Sensing of Environment 112, 3833-3845.
26. Kergoat, L., Lafont, S., Arneth, A., Le Dantec, V., Saugier, B., 2008. Nitrogen controls plant canopy light-use-efficiency in temperate and boreal ecosystems. Journal of Geophysical Research 113, http://dx.doi.org/10.1029/2007JG000676, G04017, 1-19.
27. le Maire, G., François, C., Dufréne, E., 2004. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sensing of Environment 89, 1-28.
28. Lichtenthaler, H.K., 1987. Chlorophyll and carotenoids: Pigments of photosynthetic biomembranes. Methods in Enzymology 148, 331-382.
29. Lee, Y., Yang, C., Chang, K., Shen, Y., 2008. A simple spectral index using reflectance of 735 nm to assess nitrogen status of rice canopy. Agronomy Journal 100, 205-212.
30. McMaster, G.S., Wilhelm, W.W., 1997. Growing degree-days: one equation, two 6 interpretations. Agricultural and Forest Meteorology 87, 291-300.
31. Merzlyak, M., Gitelson, A., 1995. Why and what for the leaves are yellow in autumn? On the interpretation of optical spectra of senescing leaves (Acer platanoides L.). Journal Plant Physiology 145 (3), 315-320.
32. Peng, Y., Gitelson, A.A., 2011. Remote estimation of gross primary productivity in soybean and maize based on total crop chlorophyll content. Remote Sensing of Environment 117, 440-448.
33. Richardson, A.D., Duigan, S.P., Berlyn, G.P., 2002. An evaluation of noninvasive methods to estimate foliar chlorophyll content. New Phytologist 153, 185-194.
34. Rouse, J.W., Haas Jr., R.H., Schell, J.A., Deering, D.W., 1974. Monitoring vegetation systems in the Great Plains with ERTS. In: Third ERTS-1 Symposium, NASA, Washington, DC, pp. 309-317.
35. Schepers, J.S., Francis, D.D., Thompson, M.T., 1989. Simultaneous determination of total C, total N, and 15N on soil and plant material. Communications in Soil Science and Plant Analysis 20, 949-959.
36. Sripada, R.P., Schmidt, J.P., Dellinger, A.E., Beegle, D.B., 2008. Evaluating multiple indices from a canopy reflectance sensor to estimate corn N requirements. Agronomy Journal 100, 1553-1561.
37. Stone, M., 1974. Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society: Series B 36 (2), 111-147.
38. Takahashi, W., Nguyen-Cong, V., Kawaguchi, S., Minamiyama, M., 2000. Statistical models for prediction of dry weight and nitrogen accumulation based on visible and near-infrared hyper-spectral reflectance of rice canopies. Plant Production Science 3, 377-386.
39. Tian, Y.C., Yao, X., Yang, J., Cao, W.X., Hannaway, D.B., Zhu, Y., 2011. Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance. Field Crops Research 120, 299-310.
40. Ustin, S.L., Gitelson, A.A., Jacquemoud, S., Schaepman, M., Asner, G.P., Gamon, J.A., Zarco-Tejada, P., 2009. Retrieval of foliar information about plant pigment systems from high resolution spectroscopy. Remote Sensing of Environment 113, S67-S77.
41. Viñ;a, A., Gitelson, A.A., 2005. New developments in the remote estimation of the fraction of absorbed photosynthetically active radiation in crops. Geophysical Research Letters 32, L17403, http://dx.doi.org/10.1029/2005GL023647.
42. Viñ;a, A., Gitelson, A.A., Nguy-Robertson, A.L., Peng, Y., 2011. Comparison of different vegetation indices for the remote assessment of green leaf area index of crops. Remote Sensing of Environment 115, 3468-3478, http://dx.doi.org/10.1016/j.rse.2011.08.010.
43. Walters, D.T., 2003. Diagnosis of nitrogen deficiency in maize and the influence of hybrid and plant density. In: North central Extension-Industry Soil Fertility Conference, 2003. Vol. 19, Des Moines, IA.
44. Wellburn, A.R., 1994. The spectral determination of chlorophylls a and b, as well as total carotenoids, using various solvents with spectrophotometers of different resolution. Journal Plant Physiology 144, 307-313.
45. Wullschleger, S.D., 1993. Biochemical limitations to carbon assimilation in C3 plants-a retrospective analysis of the A/Ci curves from 109 species. Journal of Experimental Botany 44, 907-920.
46. Wu, C., Niu, Z., Gao, S., 2010. Gross primary production estimation from MODIS data with vegetation index and photosynthetically active radiation in maize. Journal of Geophysical Research 115, D12127 http://dx.doi.org/10.1029/2009JD013023
47. Wu, C., Niu, Z., Tang, Q., Huang, W., Rivard, B., Feng, J., 2009. Remote estimation of gross primary production in wheat using chlorophyll-related vegetation indices. Agricultural and Forest Meteorology 149, 1015-1021.
48. Xue, L., Cao, W., Luo, W., Dai, T., Zhu, Y., 2004. Monitoring leaf nitrogen status in rice with canopy spectral reflectance. Agronomy Journal 96, 135-142.
49. Zhu, Y., Yao, X., Tian, Y., Liu, X., Cao, W., 2008. Analysis of common canopy vegetation indices for indicating leaf nitrogen accumulations in wheat and rice. International Journal of Applied Earth Observation and Geoinformation 10, 1-10.