Spectral discrimination and reflectance properties of various vine varieties from satellite, UAV and proximate sensors

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 40, Issue 7W3, 2015, Pages 31-37

  Karakizi, C ^a   Oikonomou, M ^a   Karantzalos, K ^a  

^a NATIONAL TECHNICAL UNIVERSITY OF ATHENS   (Greece)

Author keywords

Classification; Precision agriculture; Spectral signatures; Viticulture

Indexed keywords

ANTENNAS; CULTIVATION; HYPERSPECTRAL IMAGING; PRECISION AGRICULTURE; RADIOMETERS; REMOTE SENSING; SATELLITE IMAGERY; SPECTROMETERS; SPECTROSCOPY; UNMANNED AERIAL VEHICLES (UAV);

HYPERSPECTRAL; HYPERSPECTRAL DATA; PRECISION AGRICULTURE; REFLECTANCE PROPERTIES; SATELLITE DATA; SAUVIGNON BLANC; SPECTRAL BAND; SPECTRAL SIGNATURE; SPECTRO-RADIOMETERS; VITICULTURE;

REFLECTION;

EID: 84930406894     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5194/isprsarchives-XL-7-W3-31-2015     Document Type: Conference Paper

References (13)

1. Blaschke, T., 2010. Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 65(1), 2-16.
2. Bramley, R.G.V. & Proffitt, A.P.B., 1999. Managing variability in viticultural production. Grapegrower and Winemaker, 427, 11-16.
3. Clarke, O. & Rand, M., 2010. Grapes Wines: A Comprehensive Guide to Varieties and Flavours. Sterling Epicure, New York, USA.
4. Diago, P.D., Fernandes, A.M., Millan, B., Tardaguila, J. & Melo-Pinto, P., 2013. Identification of grapevine varieties usingleaf spectroscopy and partial least squares. Computers and Electronics in Agriculture, 99, 7-13.
5. Ferreiro-Armán, M., Alba-Castro, J. L., Homayouni, S., Da Costa, J. P. & Martín-Herrero, J., 2007. Vine variety discrimination with airborne imaging spectroscopy. Proc. SPIE Remote Sensing and Modeling of Ecosystems for Sustainability IV, 667909.
6. Ferreiro-Armán, M., Da Costa, J. P., Homayouni, S. & Martín-Herrero, J., 2006. Hyperspectral image analysis for precision viticulture. Lecture Notes in Computer Science, 4142, 730-741.
7. Galet, P., 1979. A practical ampelography: grapevine identification. A practical ampelography: grapevine identification, Ithaca, N.Y., Comstock Pub. Associates.
8. 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.
9. 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, 33-44.
10. Lacar, F.M., Lewis, M. M. & Grierson, I.T., 2001. Use of hyperspectral imagery for mapping grape varieties in the Barossa Valley, South Australia. Proceedings of the Int. Geoscience and Remote Sensing Symposium, Sydney Australia, 6, 2875-2877.
11. Sánchez, M.T., De la Haba, J.M., Benítez-López, M., Fernández-Novales, J., Garrido-Varo, A. & Pérez-Marín, D., 2012. Non-destructive characterization and quality control of intact strawberries based on NIR spectral data. Journal of Food Engineering, 110, 102-108.
12. Sefc, K.M., Lefort, F., Grando, M.S., Scott, K.D., Steinkellner, H. & Thomas, M.R., 2001. Microsatellite markers for grapevine: a state of the art. In: RoubelakisAngelakis, K.A. (Ed.), Molecular Biology Biotechnology of Grapevine. Kluwer Academic Publishers.
13. Tzotsos A., Karantzalos K., & Argialas D., 2014. Multiscale Segmentation and Classification of Remote Sensing Imagery with Advanced Edge and Scale-Space Features, in Scale Issues in Remote Sensing (ed Q. Weng), John Wiley & Sons, Inc., Hoboken, New Jersey. doi: 10.1002/9781118801628.ch09.