Mapping crop water stress index in a ‘Pinot-noir’ vineyard: comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle

• DOI: 10.1007/s11119-013-9334-5
• Publication Date: 2013-11-07T06:39:49Z
• Authors: J. Bellvert; P. J. Zarco-Tejada; J. Girona; E. Fereres
• Keywords: 2. Zero hunger; CWSI; Thermal imagery; Water stress; 0207 environmental engineering; Grapevine; 02 engineering and technology; Canopy temperature; Leaf water potential; 15. Life on land; 6. Clean water

Peer Reviewed<br/>This work received partial financial support from SUDOE for the European project Telerieg SOE1/P2/E082 and the Spanish Ministry of Science and Innovation (MCI) for the project CONSOLIDER CSD2006-00067 and AGL2009-13105.<br/>Characterizing the spatial variability in water status across vineyards is a prerequisite for precision irrigation. The crop water stress index (CWSI) indicator was used to map the spatial variability in water deficits across an 11-ha ‘Pinot noir’ vineyard. CWSI was determined based on canopy temperatures measured with infrared temperature sensors placed on top of well-watered and water-stressed grapevines in 2009 and 2010. CWSI was correlated with leaf water potential (ΨL) (R2 = 0.83). This correlation was also tested with results from high resolution airborne thermal imagery. An unmanned aerial vehicle equipped with a thermal camera was flown over the vineyard at 07:30, 09:30, and 12:30 h (solar time) on 31 July 2009. At about the same time, ΨL was measured in 184 grapevines. The image obtained at 07:30 was not useful because it was not possible to separate soil from canopy temperatures. Using the airborne data, the correlation between CWSI and ΨL had an R2 value of 0.46 at 09:30 h and of 0.71 at 12:30 h, suggesting that the latter was the more favorable time for obtaining thermal images that were linked with ΨL values. A sensitivity analysis of varying pixel size showed that a 0.3 m pixel was needed for precise CWSI mapping. The CWSI maps thus obtained by airborne thermal imagery were effective in assessing the spatial variability of water stress across the vineyard.<br/>