Stress Detection in Crops with Hyperspectral Remote Sensing and Physical Simulation Models

Progress made on the detection of stress in heterog eneous crop canopies with hyperspectral remote sensing imagery is presented. High-spatial resolution multispectral remote sensing imagery was collected in 2002, 2003 and 2004 over vineyard and olive orchards in Spain. Imagery acquired with the Compact Airborne Spectrographic Imager (CASI) and the Reflective Optics System Imaging Spectrometer (ROSIS) in the visible and near infrared wavelengt h regions 400-950 nm at 1 m resolution, and with the Airborne Hyperspectral Scanner (AHS) in the reflective and thermal regions at 2 m resolution enabled the study of narrow-band vegetation indices and model simula tion for estimation of chlorophyll content for chlorosis det ection at the tree and vine level, as well as deriv ing thermal information function of the stress status. Ground d ata collection consisted of measurements of crown t ransmittance with a PCA LAI-2000 and geometrical measurements of crown projected area, height, crown cross-section, and biochemical constituents such as chlorophyll a+b and carotenoids, enabling the estimation of crown leaf area index, crown leaf density, biophysical variables related t o the crown intercepted radiation, such as crop yie ld and canopy fractional cover, as well as crop functioning throu gh chlorophyll content estimation. Leaf and canopy simulation models, such as PROSPECT, SAILH, FLIM, and rowMCRM were used and the scaling up methodology presented.

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