A flexible unmanned aerial vehicle for precision agriculture

Precision Agriculture

Volumn 13, Issue 4, 2012, Pages 517-523

  Primicerio, Jacopo ^a   Di Gennaro, Salvatore Filippo ^a   Fiorillo, Edoardo ^a   Genesio, Lorenzo ^a   Lugato, Emanuele ^a   Matese, Alessandro ^a   Vaccari, Francesco Primo ^a  

^a CNR   (Italy)

Author keywords

High resolution images; Multi spectral images; Normalized difference vegetation index; Vigour maps; Vineyard

Indexed keywords

ACCURACY ASSESSMENT; AERIAL SURVEY; CANOPY REFLECTANCE; GROUND-BASED MEASUREMENT; HETEROGENEITY; NDVI; PRECISION AGRICULTURE; SPECTRAL RESOLUTION; UNMANNED VEHICLE; VEGETATION COVER; VINEYARD;

ITALY;

EID: 84863436949     PISSN: 13852256     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11119-012-9257-6     Document Type: Article

References (19)

1. Berni, J., Zarco-Tejada, P. J., Suarez, L., & Fereres, E. (2009). Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on Geoscience and Remote Sensing, 47, 722-738.
2. Bramley, R. G. V., Ouzman, J., & Boss, P. K. (2011). Variation in vine vigour, grape yield and vineyard soils and topography as indicators of variation in the chemical composition of grapes, wine and wine sensory attributes. Australian Journal of Grape and Wine Research, 17, 217-229.
3. Costa-Ferreira, A. M., Germain, C., Homayouni, S., Da Costa, J. P., Grenier, G., Marguerit, E., et al. (2007). Transformation of high resolution aerial images in vine vigour maps at intra-block scale by semi-automatic image processing (pp. 1372-1381). Poreč: Proceedings of XV International Symposium GESCO.
4. Delenne, C., Durrieu, S., Rabatel, G., & Deshayes, M. (2010). From pixel to vine parcel: A complete methodology for vineyard delineation and characterization using remote-sensing data. Computers and Electronics in Agriculture, 70, 78-83.
5. Fiorillo, E., Genesio, L., Maselli, F., De Filippis, T., Gioli, B., & Toscano, P. (2009). Mapping the spatial variability of vineyard canopy using high-resolution airborne multispectral images. Proceedings of 16th International Symposium GiESCO. Group of International Experts of Vitivinicultural Systems for Cooperation (pp. 19-24). Davis, CA: UC Davis.
6. Gay, A. P., Stewart, T. P., Angel, R., Easey, M., Eves, A. J., Thomas, N. J., Pearce, D. A., & Kemp, A. I. 2009. Developing unmanned aerial vehicles for local and a flexible environmental and agricultural monitoring. Proceedings of RSPSoc 2009 Annual Conference. RSPSoc (pp. 471-476) Curran Associates, Inc., Leicester.
7. Goulet, E., & Morlat, R. (2011). The use of surveys among wine growers in vineyards of the middle-Loire Valley (France), in relation to terroir studies. Land Use Policy, 28, 770-782.
8. Goward, S. N., Markham, B., Dye, D. G., Dulaney, W., & Yang, J. L. (1991). Normalized difference vegetation index measurements from the advanced very high-resolution radiometer. Remote Sensing of Environment, 35, 257-277.
9. Herwitz, S. R., Johnson, L. F., Dunagan, S. E., Higgins, R. G., Sullivan, D. V., Zheng, J., et al. (2004). Imaging from an unmanned aerial vehicle: Agricultural surveillance and decision support. Computers and Electronics in Agriculture, 44, 49-61.
10. Huglin, P., & Schneider, C. (1998). Biologie et écologie de la vigne. Paris: Tec & Doc Lavoisier.
11. 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, 557-560.
12. Lamb, D. W., Weedon, M. M., & Bramley, R. G. V. (2004). Using remote sensing to predict grape phenolics and colour at harvest in a Cabernet Sauvignon vineyard: Timing observations against vine phenology and optimising image resolution. Australian Journal of Grape and Wine Research, 10, 46-54.
13. Lelong, C. C. D., Burger, P., Jubelin, G., Roux, B., Labbe, S., & Baret, F. (2008). Assessment of unmanned aerial vehicles imagery for quantitative monitoring of wheat crop in small plots. Sensors, 8, 3557-3585.
14. Liang, C. K., Chang, L. W., & Chen, H. H. (2008). Analysis and compensation of rolling shutter effect. IEEE Transactions on Image Processing, 17, 1323-1330.
15. Matese, A., Di Gennaro, S. F., Zaldei, A., Genesio, L., & Vaccari, F. P. (2009). A wireless sensor network for precision viticulture: The NAV system. Computers and Electronics in Agriculture, 69, 51-58.
16. Moran, M. S., Inoue, Y., & Barnes, E. M. (1997). Opportunities and limitations for image-based remote sensing in precision crop management. Remote Sensing of Environment, 61, 319-346.
17. Oliver, M. A., & Webster, R. (1990). Kriging: A method of interpolation for geographical information systems. International Journal of Geographical Information Systems, 4, 313-332.
18. Rouse, J. W., Haas, R. H., Schell, J. A., & Deering, D. W. (1973). Monitoring vegetation systems in the Great Plains with ERTS. In S. C. Freden & M. A. Becker (Eds.), Third ERTS Symposium (pp. 309-317). Greenbelt, MD: NASA Goddard Space Flight Center.
19. Yang, C., Everitt, J. H., & Bradford, J. M. (2006). Comparison of QuickBird satellite imagery and airborne imagery for mapping grain sorghum yield patterns. Precision Agriculture, 7, 33-44.