Rapid mapping of the leaf area index in agricultural crops

Agronomy Journal

Volumn 103, Issue 5, 2011, Pages 1532-1541

  Gebbers, Robin ^a   Ehlert, Detlef ^a   Adamek, Rolf ^a  

^a LEIBNIZ INSTITUTE FOR AGRICULTURAL ENGINEERING AND BIOECONOMY ATB   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BRASSICA NAPUS; SECALE CEREALE; TRITICUM AESTIVUM;

EID: 80052594966     PISSN: 00021962     EISSN: 14350645     Source Type: Journal    
DOI: 10.2134/agronj2011.0201     Document Type: Article

References (54)

1. Agricon. 2011. The tool for plant nutrition. Available at http://www.agricon.de/en/products/yara-n-sensor/ (verified 30 July 2011). AgriCon GmbH, Ostrau, Germany.
2. Aparicio, N., D. Villegas, J. Casadesus, J.L. Araus, and C. Royo. 2000. Spectral vegetation indices as nondestructive tools for determining durum wheat yield. Agron. J. 92:83-91. doi:10.2134/agronj2000.92183x
3. 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. Agron. J. 76:300-306. doi:10.2134/agronj1984.00021962007600020029x
4. Boegh, E., H. Soegaard, N. Broge, C.B. Hasager, N.O. Jensen, K. Schelde, and A. Thomsen. 2002. Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture. Remote Sens. Environ. 81:179-193. doi:10.1016/S0034-4257(01)00342-X
5. Bréda, N.J.J. 2003. Ground-based measurement of leaf area index: A review of methods, instruments and current controversies. J. Exp. Bot. 54:2403-2417. doi:10.1093/jxb/erg263
6. Bunce, J.A. 1989. GrowThrate, photosynthesis and respiration in relation to leaf area index. Ann. Bot. (London) 63:459-463.
7. Campbell, J.B. 1996. Introduction to remote sensing. 2nd ed. Taylor & Francis, London.
8. Cockayne, L. 1926. Tussock grassland investigation in New Zealand. p. 349-365. In A.G. Tansley and T.F. Chipp (ed.) Aims and methods in the study of vegetation. Crown Agents for the Colonies, London.
9. Dammer, K.-H., and D. Ehlert. 2006. Variable fungicide spraying in cereals using a plant cover sensor. Precis. Agric. 7:137-148. doi:10.1007/s11119-006-9005-x
10. Darvishzadeh, R., A. Skidmore, M. Schlerf, C. Atzberger, F. Corsi, and M. Cho. 2008. LAI and chlorophyll estimation for heterogeneous grassland using hyperspectral measurements. ISPRS J. Photogramm. Remote Sens. 63:409-426. doi:10.1016/j.isprsjprs.2008.01.001
11. Ehlert, D., and R. Adamek. 2007. Messeigenschaft en von Laser-Abstandssensoren. J. Agric. Eng. Res. 13:119-128.
12. Ehlert, D., H.J. Horn, and R. Adamek. 2008. Measuring crop biomass density by laser triangulation. Comput. Electron. Agric. 61:117-125. doi:10.1016/j.compag.2007.09.013
13. Ehlert, D., S. Kraatz, and R. Adamek. 2006. Henfrung Laser-Abstandssensoren. J. Agric. Eng. Res. 12:85-92.
14. Ewald, A., and V. Willhoeft. 2000. Laser scanners for obstacle detection in automotive applications. p. 682-687. In Intelligent Vehicles Symp., 2000. IV 2000. Proc. IEEE, Dearborn, MI. 3-5 Oct. 2000. Inst. of Electrical and Electronics Eng., Piscataway, NJ.
15. Falkowski, M.J., J.S. Evans, S. Martinuzzi, P.E. Gessler, and A.T. Hudak. 2009. Characterizing forest succession wiThlidar data: An evaluation for the Inland Northwest, USA. Remote Sens. Environ. 113:946-956. doi:10.1016/j.rse.2009.01.003
16. Ganguli, A.C., L.T. Vermeire, R.B. Mitchel, and M.C. Wallace. 2000. Comparison of four nondestructive techniques for estimating standing crop in shortgrass plains. Agron. J. 92:1211-1215. doi:10.2134/agronj2000.9261211x
17. Gebbers, R., and V.I. Adamchuk. 2010. Precision agriculture and food security. Science (Washington, DC) 327:828-831. doi:10.1126/science.1183899
18. Gentle, J.E. 2002. Elements of computational statistics. Springer-Verlag, New York.
19. Goodall, D.W. 1952. Some considerations in the use of point quadrats for the analysis of vegetation. Aust. J. Sci. Res. Ser. B 5:1-41.
20. Guan, J., and F.W. Nutter. 2002. Relationships between defoliation, leaf area index, canopy reflectance and forage yield in the alfalfa-leaf spot pathosystem. Comput. Electron. Agric. 37:97-112. doi:10.1016/S0168-1699(02)00113-8
21. Heege, H.J., and S. Reusch. 1996. Sensor for on the-go-control of site-specific nitrogen top dressing. ASAE Paper no. 961018. ASAE, St. Josephs, MI.
22. Heege, H.J., S. Reusch, and E. Thiessen. 2008. Prospects and results for optical systems for site-specific on-the-go control of nitrogen-top-dressing in Germany. Precis. Agric. 9:115-131. doi:10.1007/s11119-008-9055-3
23. Hodgson, M.E., J.R. Jensen, L. Schmidt, S. Schill, and B. Davis. 2003. An evaluation of LIDAR- and IFSAR-derived digital elevation models in leaf-on conditions wiThUSGS Level 1 and Level 2 DEMs. Remote Sens. Environ. 84:295-308. doi:10.1016/S0034-4257(02)00114-1
24. Hong, S.-D., J.S. Schepers, D.D. Francis, and M.R. Schlemmer. 2007. Comparison of ground-based remote sensors for evaluation of corn biomass affected by nitrogen stress. Commun. Soil Sci. Plant Anal. 38:2209-2226. doi:10.1080/00103620701549157
25. Hosoi, F., and K. Omasa. 2009. Estimating vertical plant area density profile and growThparameters of a wheat canopy at different growThstages using three-dimensional portable lidar imaging. ISPRS J. Photogramm. Remote Sens. 64:151-158. doi:10.1016/j.isprsjprs.2008.09.003
26. Houborg, R., M. Anderson, and C. Daughtry. 2009. Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at the field scale. Remote Sens. Environ. 113:259-274. doi:10.1016/j.rse.2008.09.014
27. Huete, A.R., and R.D. Jackson. 1988. Soil and atmosphere influences on the spectra of partial canopies. Remote Sens. Environ. 25:89-105. doi:10.1016/0034-4257(88)90043-0
28. Jensen, J.L.R., K.S. Humes, L.A. Vierling, and A.T. Hudak. 2008. Discrete return lidar-based prediction of leaf area index in two conifer forests. Remote Sens. Environ. 112:3947-3957. doi:10.1016/j.rse.2008.07.001
29. Jonckheere, I., S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret. 2004. Methods for leaf area index determination. Part I: Theories, techniques and instruments. Agric. For. Meteorol. 121:19-35. doi:10.1016/j.agrformet.2003.08.027
30. Johnson, L.F., D.E. Roczen, S.K. Youkhana, R.R. Nemani, and D.F. Bosch. 2003. Mapping vineyard leaf area wiThmultispectral satellite imagery. Comput. Electron. Agric. 38:33-44. doi:10.1016/S0168-1699(02)00106-0
31. Jones, K.L., G.C. Poole, S.J. O'Daniel, L.A.K. Mertes, and J.A. Stanford. 2008. Surface hydrology of low-relief landscapes: Assessing surface water flow impedance using LIDAR-derived digital elevation models. Remote Sens. Environ. 112:4148-4158. doi:10.1016/j.rse.2008.01.024
32. Jones, W.D. 2001. Keeping cars from crashing. IEEE Spectr. 38:40-45. doi:10.1109/6.946636
33. Jongschaap, R.E.E. 2006. Integrating crop grow Thsimulation and remote sensing to improve resource use efficiency in farming systems. Ph.D. thesis. Available at http://edepot.wur.nl/121791 (verified 30 July 2011). Wageningen Univ., Wageningen.
34. Kennedy, C.W., and R.L. Hutchinson. 2001. Cotton growThand development under different tillage systems. Crop Sci. 41:1162-1168. doi:10.2135/cropsci2001.4141162x
35. Kraus, K. 2004. Photogrammetrie. Band 1. Geometrische Informationen aus Photogrammetrie und Laserscanneraufnahmen. 7Thed. Walter de Gruyter, Berlin.
36. Larcher, W. 1980. Physiological plant ecology. Springer-Verlag, New York.
37. Li, Y., D. Chen, C.N. Walker, and J.F. Angus. 2010. Estimating the nitrogen status of crops using a digital camera. Field Crops Res. 118:221-227. doi:10.1016/j.fcr.2010.05.011
38. Machado, S., E.D. Bynum, T.L. Archer, R.J. Lascano, L.T. Wilson, J. Bordovsky, E. Segarra, K. Bronson, D.M. Nesmith, and W. Xu. 2002. Spatial and temporal variability of corn growThand grain yield: Implications for site-specific farming. Crop Sci. 42:1564-1576. doi:10.2135/cropsci2002.1564
39. Meier, U. 1997. GrowThstages of mono- and dicotyledonous plants. Blackwell, Berlin.
40. Palacin, J., T. Palleja, M. Tresanchez, R. Sanz, J. Llorens, M. Ribes-Dasi, J. Masip, J. Arno, A. Escola, and J.R. Rosell. 2007. Real-time tree-foliage surface estimation using a ground laser scanner. IEEE Trans. Instrum. Meas. 56:1377-1383. doi:10.1109/TIM.2007.900126
41. Potter, E., J. Wood, and C. Nicholl. 1996. SunScan canopy analysis system. Users manual SS1-UM-1.05. Delta-T Devices, Cambridge, UK.
42. Running, S.W. 1990. Estimating terrestrial primary productivity by combining remote sensing and ecosystem simulation. p. 65-86. In R.J. Hobbs and H.A. Mooney (ed.) Remote sensing of the biosphere functioning. Springer-Verlag, New York.
43. Sachs, L., and J. Hedderich. 2006. Angewandte Statistik. Methodensammlung mit R. 12Thed. Springer, Berlin.
44. Scotford, I.M., and P.C.H. Miller. 2004. Estimating tiller density and leaf area index of winter wheat using spectral reflectance and ultrasonic sensing techniques. Biosystems Eng. 89:395-408. doi:10.1016/j.biosystemseng.2004.08.019
45. Scotford, I.M., and P.C.H. Miller. 2005. Applications of spectral reflectance techniques in Northern European cereal production: A review. Biosystems Eng. 90:235-250.
46. Teruel, D.A., V. Barbieri, and L.A. Ferraro. 1997. Sugarcane leaf area index modeling under different soil water conditions. Sci. Agric. 54:39-44. doi:10.1590/S0103-90161997000300008
47. Thomsen, A., and K. Schelde. 2007. Mobile measurement of canopy development and nitrogen status. p. 389-395. In J.V. Stafford (ed.) Precision agriculture '07. Wageningen Academic Publ., Wageningen.
48. Velupillai, S., and L. Guvenc. 2009. Laser scanners for driver-assistance systems in intelligent vehicles. IEEE Contr. Syst. Mag. 29:17-19. doi:10.1109/MSP.2008.931716
49. Wallach, D., B. Goffinet, J.-E. Bergez, P. Debaek, D. Leenhardt, and J.-N. Aubertot. 2001. Parameter estimation for crop models: A new approach and application to a corn model. Agron. J. 93:757-766. doi:10.2134/agronj2001.934757x
50. Warren Wilson, J. 1959. Analysis of the distribution of foliage area in grassland. p. 51-61. In J.D. Ivins (ed.) The measurement of grassland productivity. Butterwor Th Sci. Publ., London.
51. Watson, D.J. 1947. Comparative physiological studies on the growThof field crops: I. Variation in net assimilation rate and leaf area between species and varieties, and wiThand between years. Ann. Bot. (London) 1:41-76.
52. Wilhelm, W.W., K. Ruwe, and M.R. Schlemmer. 2000. Comparison of three leaf area index meters in a corn canopy. Crop Sci. 40:1179-1183. doi:10.2135/cropsci2000.4041179x
53. Yang, C., and G.L. Anderson. 1999. Airborne videography to identify spatial variability for grain sorghum. Precis. Agric. 1:67-79. doi:10.1023/A:1009917617316
54. Zhao, K., S. Popescu, and R. Nelson. 2009. Lidar remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers. Remote Sens. Environ. 113:182-196. doi:10.1016/j.rse.2008.09.009