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Vegetation Stress Detection through Chlorophyll a + b Estimation and Fluorescence Effects on Hyperspectral Imagery

^a Centre for Research in Earth and Space Science (CRESS), Toronto, ON, Canada M3J 1P3
^b Dep. of Physics and Astronomy, York University, 4700 Keele Street, Toronto, ON, Canada M3J 1P3
^c P&M Technologies, 66 Millwood St., Sault Ste. Marie, ON, Canada P6A 6S7
^d Ontario Forest Research Institute (OFRI), Ontario Ministry of Natural Resources (OMNR), Sault Ste. Marie, ON, Canada P6A 2E5
^e Provincial Geomatics Service Centre, Ontario Ministry of Natural Resources, 300 Water St, Peterborough, ON, Canada K9J 8M5

* Corresponding author (zarco{at}terra.phys.yorku.ca)

Received for publication January 24, 2001. Physical principles applied to remote sensing data are key to successfully quantifying vegetation physiological condition from the study of the light interaction with the canopy under observation. We used the fluorescence–reflectance–transmittance (FRT) and PROSPECT leaf models to simulate reflectance as a function of leaf biochemical and fluorescence variables. A series of laboratory measurements of spectral reflectance at leaf and canopy levels and a modeling study were conducted, demonstrating that effects of chlorophyll fluorescence (CF) can be detected by remote sensing. The coupled FRT and PROSPECT model enabled CF and chlorophyll a + b (C_a+b) content to be estimated by inversion. Laboratory measurements of leaf reflectance (r) and transmittance (t) from leaves with constant C_a+b allowed the study of CF effects on specific fluorescence-sensitive indices calculated in the Photosystem I (PS-I) and Photosystem II (PS-II) optical region, such as the curvature index [CUR; /R²₆₈₃]. Dark-adapted and steady-state fluorescence measurements, such as the ratio of variable to maximal fluorescence (F_v/F_m), steady state maximal fluorescence (F^'_m), steady state fluorescence (F_t), and the effective quantum yield (F/F^'_m) are accurately estimated by inverting the FRT–PROSPECT model. A double peak in the derivative reflectance (DR) was related to increased CF and C_a+b concentration. These results were consistent with imagery collected with a compact airborne spectrographic imager (CASI) sensor from sites of sugar maple (Acer saccharum Marshall) of high and low stress conditions, showing a double peak on canopy derivative reflectance in the red-edge spectral region. We developed a derivative chlorophyll index (DCI; calculated as D₇₀₅/D₇₂₂), a function of the combined effects of CF and C_a+b content, and used it to detect vegetation stress.

Abbreviations: CASI, compact airborne spectrographic imager • CF, chlorophyll fluorescence • C_a+b, chlorophyll a + b • CUR, reflectance curvature index • DCI, derivative chlorophyll index • D_x, value of the derivative reflectance at wavelength X in nanometers • FRT, fluorescence–reflectance–transmittance model • F^'_m, steady state maximal fluorescence • F_t, steady state fluorescence • F_v/F_m, ratio of variable to maximal fluorescence • F/F^'_m, effective quantum yield • PAM, pulse amplitude modulation • PS-I, Photosystem I • PS-II, Photosystem II • RMSE, root mean square error • RT, radiative transfer • R_x, value of the reflectance at wavelength X in nanometers

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