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Detection of water stress in an olive orchard with thermal remote sensing imagery
Institution:1. Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC), Alameda del Obispo, s/n, 14004 Córdoba, Spain;2. Universidad de Valencia, Valencia, Spain;3. Laboratorio de Teledetección, Instituto Nacional de Técnica Aeroespacial (INTA), Madrid, Spain;4. Dpto. de Agronomía, Universidad de Córdoba, Spain;1. Department of Agroecology, Environmental Science Research Institute, Shahid Beheshti University (G.C.), Tehran, Iran;2. Institute of Environmental Spatial Analysis, University of North Georgia, Gainesville State College, 3820 Mundy Mill Road, Oakwood, GA 30566, USA;1. Department of Agricultural and Forest Sciences (SAF), Università degli Studi di Palermo, Viale delle Scienze Ed. 4, 90128, Palermo, Italy;2. Department of Civil, Environmental and Aerospace Engineering (DICAM), Università degli Studi di Palermo, Viale delle Scienze Ed. 8, 90128, Palermo, Italy;1. UC Cooperative Extension, USA;2. Olivos Irrigation, Chile;3. Pontificia Universidad Católica de Valparaíso, Chile;4. UC Davis, USA;1. Linking Landscape, Environment, Agriculture and Food, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, Lisboa 1349-017, Portugal;2. Geo-Space Sciences Research Centre, (CICGE), Rua do Campo Alegre, Porto 4169-007, Portugal;3. InBIO/CIBIO, Research Centre in Biodiversity and Genetic Resources, University of Porto, Campus Agrário de Vairão, Rua Padre Armando Quintas, nr. 7, 4485-661 Vairão, Portugal;4. Faculdade de Ciências da Universidade do Porto, Rua do Campo Alegre, Porto 4169-007, Portugal;5. Associação para o Desenvolvimento da Viticultura Duriense, Edifício Centro de Excelência da Vinha e do Vinho Parque de Ciência e Tecnologia de Vila Real, Régia Douro Park, Portugal;1. Water Management and Systems Research Unit, USDA-ARS. 2150 Centre Avenue, Bldg. D, Suite 320 Fort Collins, CO, 80526, United States;2. Department of Civil and Environment Engineering, Colorado State University, CO 80526, United States
Abstract:An investigation of the detection of water stress in non-homogeneous crop canopies such as orchards using high-spatial resolution remote sensing thermal imagery is presented. An airborne campaign was conducted with the Airborne Hyperspectral Scanner (AHS) acquiring imagery in 38 spectral bands in the 0.43–12.5 μm spectral range at 2.5 m spatial resolution. The AHS sensor was flown at 7:30, 9:30 and 12:30 GMT in 25 July 2004 over an olive orchard with three different water-deficit irrigation treatments to study the spatial and diurnal variability of temperature as a function of water stress. A total of 10 AHS bands located within the thermal-infrared region were assessed for the retrieval of the land surface temperature using the split-window algorithm, separating pure crowns from shadows and sunlit soil pixels using the reflectance bands. Ground truth validation was conducted with infrared thermal sensors placed on top of the trees for continuous thermal data acquisition. Crown temperature (Tc), crown minus air temperature (Tc ? Ta), and relative temperature difference to well-irrigated trees (Tc ? TR, where TR is the mean temperature of the well-irrigated trees) were calculated from the ground sensors and from the AHS imagery at the crown spatial resolution. Correlation coefficients for Tc ? TR between ground IRT sensors and airborne image-based AHS estimations were R2 = 0.50 (7:30 GMT), R2 = 0.45 (9:30 GMT) and R2 = 0.57 (12:30 GMT). Relationships between leaf water potential and crown Tc ? Ta measured with the airborne sensor obtained determination coefficients of R2 = 0.62 (7:30 GMT), R2 = 0.35 (9:30 GMT) and R2 = 0.25 (12:30 GMT). Images of Tc ? Ta and Tc ? TR for the entire field were obtained at the three times during the day of the overflight, showing the spatial and temporal distribution of the thermal variability as a function of the water deficit irrigation schemes.
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