Unmanned aerial vehicle used for remote sensing on an apulian farm in southern Italy

Engineering for Rural Development

Volumn 17, Issue , 2018, Pages 149-154

  Pascuzzi, Simone ^a   Anifantis, Alexandros Sotirios ^a   Cimino, Vincenzo ^a   Santoro, Francesco ^a  

^a UNIVERSITY OF BARI   (Italy)

Author keywords

Maize crop; Multispectral sensor; Thermal sensor; Unmanned aerial vehicle

Indexed keywords

ANTENNAS; CROPS; ELECTROMAGNETIC WAVE EMISSION; ELECTROMAGNETIC WAVES; IMAGE ACQUISITION; REGIONAL PLANNING; REMOTE SENSING; THERMOANALYSIS; VEGETATION;

EXPERIMENTAL EVALUATION; IRRIGATION SYSTEMS; MULTISPECTRAL SENSORS; NORMALIZED DIFFERENCE VEGETATION INDEX; PHYSIOLOGICAL STATUS; REMOTE SENSING APPLICATIONS; TEMPORAL VARIABILITY; THERMAL SENSORS;

UNMANNED AERIAL VEHICLES (UAV);

EID: 85048950521     PISSN: 16913043     EISSN: 16915976     Source Type: Conference Proceeding    
DOI: 10.22616/ERDev2018.17.N175     Document Type: Conference Paper

References (20)

1. McBratney A. B., Whelan B. M., Shatar T. Variability and uncertainty in spatial, temporal and spatio-temporal crop yield and related data. In Precision agriculture: Spatial and temporal variability of environmental quality. Chichester: Wiley, 1997, pp. 141-160.
2. Brisco B., Brown R. J., Hirose T., Mcnairn H., Staenz K. Precision agriculture and the role of remote sensing: a review. Canadian Journal of Remote Sensing, vol. 24, 1998, pp. 315-327.
3. Moran M. S., Inoue Y., Barnes, E. M. Opportunities and limitations for image-based remote sensing in precision crop management. Remote Sensing of Environment, vol. 61,1997, pp. 319-346.
4. Pascuzzi S. The effects of the forward speed and air volume of an air-assisted sprayer on spray deposition in “tendone” trained vineyards. J. Agr. Eng., vol. 3, 2013, pp. 125-132. http://dx.doi.org/10.4081/jae.2013.e18
5. Pascuzzi S., Santoro F. Analysis of the almond harvesting and hulling mechanization process: A case study. Agriculture (Switzerland), 7(12), 2017, 100 p. http://dx.doi.org/10.3390/agriculture7120100
6. Baldoin C., Balsari P., Cerruto E., Pascuzzi S., Raffaelli M. Improvement in pesticide application on greenhouse crops: Results of a survey about greenhouse structures in Italy. Acta Hort. vol. 801, 2008, pp. 609-614.
7. Seelan S. K., Laguette S., Casady G. M., Seielstad G. A.. Remote sensing applications for precision agriculture: a learning community approach. Remote Sensing of Environment, vol. 88, 2003, pp. 157-169.
8. Lan Y., Thomson S. J., Huang Y., Hoffmann W. C., Zhang H. Current status and future directions of precision aerial application for site-specific cropmanagement in the USA. Computers and Electronics in Agriculture, vol. 74, 2010, pp. 34-38.
9. Xiang H., Tian L. Method for automatic georeferencing aerial remote sensing (RS) images from an unmanned aerial vehicle (UAV) platform. Biosystems Engineering, vol.108, 2011, pp. 104-113.
10. Pena-Barragan J. M., Lopez-Granados F., Jurado-Exposito M., Garcia-Torres L. Sunflower yield related to multitemporal aerial photography, land elevation and weed infestation. Precision Agriculture, vol. 11, 2010, pp. 568-585.
11. Yang C., Bradford J. M., Wiegand C. L. Airborne multispectral imagery for mapping variable growing conditions and yields of cotton, grain sorghum, and corn. Transaction of ASAE, vol. 44, 2001, pp.1983-1994.
12. Zhang C., Kovacs J. M. The application of small aerial systems for precision agriculture: a review. Precision Agriculture, vol. 13, 2012, pp. 693-712.
13. Berni J.A.J., Zarco-Tejada P.J., Suarez L., Fereres E. Thermal and narrowband multispectral remote sensing for vegetation monitoring from unmanned aerial vehicle. IEEE Transactions on Geoscience and Remote Sensing, vol. 47, 2009, pp. 722-738.
14. Corcoles J.I., Ortega J.F., Hernandez D., Moreno M.A.Estimation of leaf area index in onion (Allium cepa L.) using an unmanned aerial vehicle. Biosystems Engineering, vol. 115, 2013, pp. 31-42.
15. Vega F.A., Ramírez F.C., Saiz M.P.,Rosúa F.O. Multitemporal imaging using an unmanned aerial vehicle for monitoring a sunflower crop. Biosystems Engineering, vol. 132, 2015, pp. 19-27.
16. Baluja J., Diago M. P., Balda P., Zorer R., Meggio F., Morales F., Tardaguila J. Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV). Irrigation Science, vol. 30, 2012, pp. 511-522.
17. Manetto G., Cerruto E., Pascuzzi S., Santoro F. Improvements in citrus packing lines to reduce the mechanical damage to fruit. Chem. Eng. Trans. 58, 2017, pp. 391-396, http://dx.doi.org/10.3303/CET1758066
18. Garcia-Ruiz F., Sankaran S., Maja J. M., Lee W. S., Rasmussen J., & Ehsani R. Comparison of two aerial imaging platforms for identification of Huanglongbing-infected citrus trees. Computers and Electronics in Agriculture, vol. 91, 2013, pp. 106-115.
19. Zarco-Tejada P. J., Ustin S. L., Whiting M. L. Temporal and spatial relationships between within-field yield variability in cotton and high-spatial hyperspectral remote sensing imagery. Agronomy Journal, 97, 2005, pp. 641-653.
20. Pascuzzi S. A multibody approach applied to the study of driver injuries due to a narrow-track wheeled tractor rollover. J. Agr. Eng., vol. 46, 2015, pp. 105-114. http://dx.doi.org/10.4081/jae.2015.466