Spatial variability of crop water stress in an olive grove with high-spatial thermal remote sensing imagery
In: Precision Agriculture ‘05gsepulcre@ias.csic.es
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3Dpto. de Agronomía, Universidad de Córdoba, Spain
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The Airborne Hyperspectral Scanner (AHS) was used to acquire images with a 2.5 m spatial resolution in the visible, near infrared and thermal spectral regions over an olive orchard in southern Spain to study the spatial variability of water stress. The AHS sensor was equipped with 20 channels of 20 nm bandwidth in the visible and near infrared region, 1 channel of 200 nm bandwidth, 42 channels of 13 nm bandwidth in the mid infrared, 7 channels of 300nm bandwidth for short-wave infrared, and 10 channels of 400nm in the long-wave infrared spectral region. Aircraft flights were scheduled at 7:30, 9:30 and 12:30 GMT in July 2004 to study the spatial and temporal variation of orchard tree temperatures as a function of the diurnal variation of water stress. Water and bare soil temperatures were measured simultaneously to the airborne sensor overflights to calibrate the thermal AHS imagery, acquiring atmospheric optical thickness at the time of image collection. Imagery was processed applying geometric, radiometric and atmospheric corrections. The high spatial resolution AHS data enabled the temperature of the top of the tree to be targeted, minimizing structural mixed pixel effects. Olive tree emissivities were measured in the field with a CIMEL instrument, and the soil emissivity was measured using a bottomless box. Water potential, photosynthesis, and stomatal conductance were measured weekly in olive trees under 3 different water stress treatments from June to November 2004 to track the effects of water stress on the trees’ condition and functioning. Infrared sensors were placed on top of the trees for diurnal thermal data collection and validation of the thermal imagery collected. Results of the remote sensing thermal analysis show that this methodology allows mapping of the spatial variability of water stress with a potential applicability in precision agriculture for management of controlled deficit irrigation methods.