Precision Agriculture

, Volume 14, Issue 3, pp 290–306 | Cite as

Leaf area index estimation in vineyards using a ground-based LiDAR scanner

  • Jaume Arnó
  • Alexandre Escolà
  • Josep M. Vallès
  • Jordi Llorens
  • Ricardo Sanz
  • Joan Masip
  • Jordi Palacín
  • Joan R. Rosell-Polo
Article

Abstract

Estimation of grapevine vigour using mobile proximal sensors can provide an indirect method for determining grape yield and quality. Of the various indexes related to the characteristics of grapevine foliage, the leaf area index (LAI) is probably the most widely used in viticulture. To assess the feasibility of using light detection and ranging (LiDAR) sensors for predicting the LAI, several field trials were performed using a tractor-mounted LiDAR system. This system measured the crop in a transverse direction along the rows of vines and geometric and structural parameters were computed. The parameters evaluated were the height of the vines (H), the cross-sectional area (A), the canopy volume (V) and the tree area index (TAI). This last parameter was formulated as the ratio of the crop estimated area per unit ground area, using a local Poisson distribution to approximate the laser beam transmission probability within vines. In order to compare the calculated indexes with the actual values of LAI, the scanned vines were defoliated to obtain LAI values for different row sections. Linear regression analysis showed a good correlation (R2 = 0.81) between canopy volume and the measured values of LAI for 1 m long sections. Nevertheless, the best estimation of the LAI was given by the TAI (R2 = 0.92) for the same length, confirming LiDAR sensors as an interesting option for foliage characterization of grapevines. However, current limitations exist related to the complexity of data process and to the need to accumulate a sufficient number of scans to adequately estimate the LAI.

Keywords

LAI Precision viticulture Proximal sensing Terrestrial laser scanner Vine vigour 

References

  1. Arnó, J., Vallès, J. M., Llorens, J., Blanco, R., Palacín, J., & Sanz, R., et al. (2006). Ground laser scanner data analysis for leaf area index (LAI) prediction in orchards and vineyards. In Book of Abstracts of the AgEng 2006 Conference (pp. 311–312). Bonn, Germany: VDI Verlag GmbH.Google Scholar
  2. Drissi, R., Goutouly, J. P., Forget, D., & Gaudillere, J. P. (2009). Nondestructive measurement of grapevine leaf area by ground normalized difference vegetation index. Agronomy Journal, 101(1), 226–231.CrossRefGoogle Scholar
  3. Ehlert, D., Heisig, M., & Adamek, R. (2010). Suitability of a laser rangefinder to characterize winter wheat. Precision Agriculture, 11(6), 650–663.CrossRefGoogle Scholar
  4. Ehlert, D., Horn, H. J., & Adamek, R. (2008). Measuring crop biomass density by laser triangulation. Computers and Electronics in Agriculture, 61(2), 117–125.CrossRefGoogle Scholar
  5. Escolà, A., Planas, S., Rosell, J. R., Pomar, J., Camp, F., Solanelles, F., et al. (2011). Performance of an ultrasonic ranging sensor in apple tree canopies. Sensors, 11(3), 2459–2477.PubMedCrossRefGoogle Scholar
  6. Gebbers, R., Ehlert, D., & Adamek, R. (2011). Rapid mapping of the leaf area index in agricultural crops. Agronomy Journal, 103(5), 1532–1541.CrossRefGoogle Scholar
  7. Gil, E., Escolà, A., Rosell, J. R., Planas, S., & Val, L. (2007). Variable rate application of plant protection products in vineyard using ultrasonic sensors. Crop Protection, 26(8), 1287–1297.CrossRefGoogle Scholar
  8. Giles, D. K., Delwiche, M. J., & Dodd, R. B. (1988). Electronic measurement of tree canopy volume. Transactions of the ASAE, 31(1), 264–272.Google Scholar
  9. Goutouly, J. P., Drissi, R., Forget, D., & Gaudillère, J. P. (2006). Characterization of vine vigour by ground based NDVI measurements. In Proceedings of the VI International Terroir Congress (pp. 237–241). Bordeaux, France.Google Scholar
  10. Grantz, D. A., & Williams, L. E. (1993). An empirical protocol for indirect measurement of leaf area index in grape (Vitis vinifera L.). HortScience, 28(8), 777–779.Google Scholar
  11. Hall, A., Lamb, D. W., Holzapfel, B., & Louis, J. (2002). Optical remote sensing applications in viticulture—a review. Australian Journal of Grape and Wine Research, 8, 36–47.CrossRefGoogle Scholar
  12. Hidalgo, J. (2006). La calidad del vino desde el viñedo (The quality of wine from the vineyard). Madrid: Mundi-Prensa.Google Scholar
  13. Johnson, L. F., Bosch, D. F., Williams, D. C., & Lobitz, B. M. (2001). Remote sensing of vineyard management zones: Implications for wine quality. Applied Engineering in Agriculture, 17(4), 557–560.Google Scholar
  14. Johnson, L. F., & Pierce, L. L. (2004). Indirect measurements of leaf area index in California north coast vineyards. HortScience, 39(2), 236–238.Google Scholar
  15. Johnson, L. F., Roczen, D. E., Youkhana, S. K., Nemani, R. R., & Bosch, D. F. (2003). Mapping vineyard leaf area with multispectral satellite imagery. Computers and Electronics in Agriculture, 38(1), 33–44.CrossRefGoogle Scholar
  16. Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M., et al. (2004). Review of methods for in situ leaf area index determination: Part I. Theories, sensors, and hemispherical photography. Agricultural and Forest Meteorology, 121(1–2), 19–35.CrossRefGoogle Scholar
  17. Keightley, K. E., & Bawden, G. W. (2010). 3D volumetric modelling of grapevine biomass using Tripod LiDAR. Computers and Electronics in Agriculture, 74(2), 305–312.CrossRefGoogle Scholar
  18. Lee, K. H., & Ehsani, R. (2008). Comparison of two 2D laser scanners for sensing object distances, shapes, and surface patterns. Computers and Electronics in Agriculture, 60(2), 250–262.CrossRefGoogle Scholar
  19. Lee, K. H., & Ehsani, R. (2009). A laser scanner based measurement system for quantification of citrus tree geometric characteristics. Applied Engineering in Agriculture, 25(5), 777–788.Google Scholar
  20. Llorens, J., Gil, E., Llop, J., & Escolà, A. (2011). Ultrasonic and LiDAR sensors for electronic canopy characterization in vineyards: Advances to improve pesticide application methods. Sensors, 11(2), 2177–2194.PubMedCrossRefGoogle Scholar
  21. López-Lozano, R., Baret, F., García de Cortázar-Atauri, I., Bertrand, N., & Casterad, M. A. (2009). Optimal geometric configuration and algorithms for LAI indirect estimates under row canopies: The case of vineyards. Agricultural and Forest Meteorology, 149(8), 1307–1316.CrossRefGoogle Scholar
  22. Mazzetto, F., Calcante, A., Mena, A., & Vercesi, A. (2010). Integration of optical and analogue sensors for monitoring canopy health and vigour in precision agriculture. Precision Agriculture, 11(6), 636–649.CrossRefGoogle Scholar
  23. Moorthy, I., Miller, J. R., Jimenez Berni, J. A., Zarco-Tejada, P., Hu, B., & Chen, J. (2011). Field characterization of olive (Olea europaea L.) tree crown architecture using terrestrial laser scanning data. Agricultural and Forest Meteorology, 151(2), 204–214.Google Scholar
  24. Palacín, J., Pallejà, T., Tresánchez, M., Sanz, R., Llorens, J., Ribes-Dasi, M., et al. (2007). Real-time tree-foliage surface estimation using a ground laser scanner. IEEE Transactions on Instrumentation and Measurement, 56(4), 1377–1383.CrossRefGoogle Scholar
  25. Palleja, T., Tresanchez, M., Teixido, M., Sanz, R., Rosell, J. R., & Palacin, J. (2010). Sensitivity of tree volume measurement to trajectory errors from a terrestrial LiDAR scanner. Agricultural and Forest Meteorology, 150(11), 1420–1427.CrossRefGoogle Scholar
  26. Rosell, J. R., Llorens, J., Sanz, R., Arnó, J., Ribes-Dasi, M., Masip, J., et al. (2009a). Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LiDAR scanning. Agricultural and Forest Meteorology, 149(9), 1505–1515.CrossRefGoogle Scholar
  27. Rosell, J. R., Sanz, R., Llorens, J., Arnó, J., Escolà, A., Ribes-Dasi, M., et al. (2009b). A tractor-mounted scanning LiDAR for the non-destructive measurement of vegetative volume and surface area of tree-row plantations: A comparison with conventional destructive measurements. Biosystems Engineering, 102(2), 128–134.CrossRefGoogle Scholar
  28. Saeys, W., Lenaerts, B., Craessaerts, G., & De Baerdemaeker, J. (2009). Estimation of the crop density of small grains using LiDAR sensors. Biosystems Engineering, 102(1), 22–30.CrossRefGoogle Scholar
  29. Sanchez-de-Miguel, P., Junquera, P., de la Fuente, M., Jimenez, L., Linares, R., Baeza, P., et al. (2011). Estimation of vineyard leaf area by linear regression. Spanish Journal of Agricultural Research, 9(1), 202–212.Google Scholar
  30. Sanz, R., Llorens, J., Escolà, A., Arnó, J., Ribes-Dasi, M., Masip, J., et al. (2011). Innovative LiDAR 3D dynamic measurement system to estimate fruit-tree leaf area. Sensors, 11(6), 5769–5791.CrossRefGoogle Scholar
  31. Schumann, A. W., & Zaman, Q. U. (2005). Software development for real-time ultrasonic mapping of tree canopy size. Computers and Electronics in Agriculture, 47(1), 25–40.CrossRefGoogle Scholar
  32. Scotford, I. M., & Miller, P. C. H. (2004). Estimating tiller density and leaf area index of winter wheat using spectral reflectance and ultrasonic sensing techniques. Biosystems Engineering, 89(4), 395–408.CrossRefGoogle Scholar
  33. Smart, R. E. (1985). Principles of grapevine canopy microclimate manipulation with implications for yield and quality: A review. American Journal of Enology and Viticulture, 36(3), 230–239.Google Scholar
  34. Solanelles, F., Escolà, A., Planas, S., Rosell, J. R., Camp, F., & Gràcia, F. (2006). An electronic control system for pesticide application proportional to the canopy width of tree crops. Biosystems Engineering, 95(4), 473–481.CrossRefGoogle Scholar
  35. Stamatiadis, S., Taskos, D., Tsadila, E., Christofides, C., Tsadilas, C., & Schepers, J. S. (2010). Comparison of passive and active canopy sensors for the estimation of vine biomass production. Precision Agriculture, 11(3), 306–315.CrossRefGoogle Scholar
  36. Tisseyre, B., Mazzoni, C., Ardoin, N., & Clipet, C. (2001). Yield and harvest quality measurement in precision viticulture—application for a selective vintage. In G. Grenier & S. Blackmore (Eds.), Proceedings of the 3rd European conference on precision agriculture (pp. 133–138). Montpellier: Agro.Google Scholar
  37. Tregoat, O., Ollat, N., Grenier, G., & Van Leeuwen, C. (2001). Etude comparative de la précision et de la rapidité de mise en œuvre de différentes méthodes d’estimation de la surface foliaire de la vigne. Journal International des Sciences de la Vigne et du Vin, 35(1), 31–39. (in French).Google Scholar
  38. Tumbo, S. D., Salyani, M., Whitney, J. D., Wheaton, T. A., & Miller, W. M. (2002). Investigation of laser and ultrasonic ranging sensors for measurements of citrus canopy volume. Applied Engineering in Agriculture, 18(3), 367–372.Google Scholar
  39. Walklate, P. J. (1989). A laser scanning instrument for measuring crop geometry. Agricultural and Forest Meteorology, 46(4), 275–284.CrossRefGoogle Scholar
  40. Walklate, P. J., Cross, J. V., Richardson, G. M., Murray, R. A., & Baker, D. E. (2002). Comparison of different spray volume deposition models using LiDAR measurements of apple orchards. Biosystems Engineering, 82(3), 253–267.CrossRefGoogle Scholar
  41. Wei, J., & Salyani, M. (2004). Development of a laser scanner for measuring tree canopy characteristics: Phase 1. Prototype development. Transactions of the ASABE, 47(6), 2101–2107.Google Scholar
  42. Wei, J., & Salyani, M. (2005). Development of a laser scanner for measuring tree canopy characteristics: Phase 2. Foliage density measurement. Transactions of the ASABE, 48(4), 1595–1601.Google Scholar
  43. Weiss, M., Baret, F., Smith, G. J., Jonckheere, I., & Coppin, P. (2004). Review of methods for in situ leaf area index (LAI) determination. Part II. Estimation of LAI, errors and sampling. Agricultural and Forest Meteorology, 121(1–2), 37–53.CrossRefGoogle Scholar
  44. Zaman, Q. U., & Schumann, A. W. (2005). Performance of an ultrasonic tree volume measurement system in commercial citrus groves. Precision Agriculture, 6(5), 467–480.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Jaume Arnó
    • 1
  • Alexandre Escolà
    • 1
  • Josep M. Vallès
    • 1
  • Jordi Llorens
    • 2
  • Ricardo Sanz
    • 1
  • Joan Masip
    • 1
  • Jordi Palacín
    • 3
  • Joan R. Rosell-Polo
    • 1
  1. 1.Department of Agricultural and Forest EngineeringResearch Group on AgroICT and Precision Agriculture, University of LleidaLleidaSpain
  2. 2.Department of Agri Food Engineering and BiotechnologyPolitechnical University of CatalunyaCastelldefelsSpain
  3. 3.Department of Computer Science and Industrial EngineeringUniversity of LleidaLleidaSpain

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