Linking physiological responses, chlorophyll fluorescence and hyperspectral imagery to detect salinity stress using the physiological reflectance index in the coastal shrub, Myrica cerifera

Department of Biology, Virginia Commonwealth University, Richmond, Virginia 23284, USA; US Army ERDC, Fluorescence Spectroscopy Lab, 7701 Telegraph Road, Alexandria, VA 22315, USA
Remote Sensing of Environment (Impact Factor: 5.1). 06/2008; 112(10):3865-3875. DOI: 10.1016/j.rse.2008.06.004

ABSTRACT Measurements of physiology, chlorophyll fluorescence and hyperspectral reflectance were used to detect salinity stress in the evergreen coastal shrub, Myrica cerifera on Hog Island, Virginia. Two experimental sites were used in our study, the oceanside of a M. cerifera thicket, which is exposed to sea spray, and the protected, leeside of the thicket. Using the physiological reflectance index (PRI), we were able to detect stress at both the canopy and landscape level. Monthly variations in stomatal conductance, photosynthesis, and relative water content indicated a strong summer drought response that was not apparent in chlorophyll fluorescence or in the water band index (WBI) derived from canopy and airborne reflectance measurements. In contrast, there were significant differences in both physiological measurements and tissue chlorides between the two sites used in the study, indicating salinity stress. This was reflected in measurements of PRI. There was a positive relationship between PRI measured at the canopy-level and light-adapted fluorescence (ΔF/F′m; r2 = 0.69). PRI was significantly lower on the oceanside of the Myrica cerifera thicket. PRI was not significantly related to NDVI (r2 = 0.01) at the canopy-level and only weakly related (r2 = 0.04) at the landscape-level, suggesting that the indices are independent. The chlorophyll index (CI) did not show any significant changes between the two sites. Frequency histograms of pixels sampled from airborne hyperspectral imagery revealed that the distribution of PRI was shifted to the right on the backside of the thicket relative to the oceanside and there was a significant difference between sites. These results suggest that PRI may be used for early identification of salt-stress and to identify areas across the landscape where community structure may change due to sea-level rise.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Traditional remote sensing techniques allow the assessment of green plant biomass, and therefore plant photosynthetic capacity. However, detecting how much of this capacity is actually realized is a more challenging goal. Is it possible to remotely assess actual carbon fluxes? Can this be done at leaf, canopy and ecosystem scales and at different temporal scales? Different approaches can be used to answer these questions. Among them, the Photochemical Reflectance Index (PRI) derived from narrow-band spectroradiometers is a spectral index increasingly being used as an indicator of photosynthetic efficiency. We examined and synthesized the scientific literature on the relationships between PRI and several ecophysiological variables across a range of plant functional types and ecosystems at the leaf, canopy and ecosystem levels and at the daily and seasonal time scales. Our analysis shows that although the strength of these relationships varied across vegetation types, levels of organization and temporal scales, in most reviewed articles PRI was a good predictor of photosynthetic efficiency or related variables with performances at least as good as the widely used NDVI as indicator of green biomass. There are possible confounding factors related to the intensity of the physiological processes linked to the PRI signals, to the structure of the canopies and to the illumination and viewing angles that warrant further studies, and it is expected that the utility of PRI will vary with the ecosystem in question due to contrasting environmental constraints, evolutionary strategies, and radiation use efficiency (RUE; the ratio between carbon uptake and light absorbed by vegetation) variability. Clearly, more research comparing ecosystem responses is warranted. Additionally, like any 2-band index that is affected by multiple factors, the interpretation of PRI can be readily confounded by multiple environmental variables, and further work is needed to understand and constrain these effects. Despite these limitations, this review shows an emerging consistency of the RUE–PRI relationship that suggests a surprising degree of functional convergence of biochemical, physiological and structural components affecting leaf, canopy and ecosystem carbon uptake efficiencies. PRI accounted for 42%, 59% and 62% of the variability of RUE at the leaf, canopy and ecosystem respective levels in unique exponential relationships for all the vegetation types studied. It seems thus that by complementing the estimations of the fraction of photosynthetically active radiation intercepted by the vegetation (FPAR), estimated with NDVI-like indices, PRI enables improved assessment of carbon fluxes in leaves, canopies and many of the ecosystems of the world from ground, airborne and satellite sensors.
    Remote Sensing of Environment. 01/2011;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The purpose of this investigation was to determine the feasibility of using the chlorophyll content index (cci) from a ccm-200 unit as an estimator of the seasonal variation of leaf pigment [chlorophyll a (chla), chlorophyll b (chlb), and total chlorophyll (tchl = chla + chlb)] content for a range of mangrove species within a degraded environment of the mexican pacific. two seasons (dry and rainy) of measurements were made on six mangrove classes: healthy and dwarf Avicennia germinans (linnaeus) linnaeus, healthy and poor condition Rhizophora mangle linnaeus, and healthy and poor condition Laguncularia racemosa (linnaeus) c.f. gaertn. tests of leaf pigment contents from 360 cci readings (30 per class) indicated that each equation was a valid predictor of chla and tchl for all six mangrove classes during both seasons. however, there was a poorer fit (lower R2) for the three species in poor/dwarf condition during the rainy season. chla and tchl were statistically well correlated with all of the cci data; however, the correlating chlb were lower (R2 < 0.68) for all classes except dwarf condition A. germinans (R2 = 0.80). The strong relationship observed between the readings from the portable ccm-200 and the pigment content suggest that the handheld ccm-200 can be a portable cost-effective tool for quickly predicting chla and tchl content for a range of mangrove forests.
    Bulletin of Marine Science -Miami- 01/2013; 89(2):621-633. · 1.30 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a method for mapping water stress in a maize field using hyperspectral remote sensing imagery. An airborne survey using AISA (Specim, Finland) was performed in July 2008 over an experimental farm in Italy. Hyperspectral data were acquired over a maize field with three different irrigation regimes. An intensive field campaign was also conducted concurrently with imagery acquisition to measure relative leaf water content (RWC), active chlorophyll fluorescence (ΔF/Fm′), leaf temperature (Tl) and Leaf Area Index (LAI). The analysis of the field data showed that at the time of the airborne overpass the maize plots with irrigation deficits were experiencing a moderate water stress, affecting the plant physiological status (ΔF/Fm′, difference between Tl and air temperature (Tair), and RWC) but not the canopy structure (LAI). Among the different Vegetation Indices (VIs) computed from the airborne imagery the Photochemical Reflectance Index computed using the reflectance at 570 nm as the reference band (PRI570) showed the strongest relationships with ΔF/Fm′ (r2 = 0.76), Tl − Tair (r2 = 0.82) and RWC (r2 = 0.64) and the red-edge Chlorophyll Index (CIred-edge) with LAI (r2 = 0.64). Thus PRI has been proven to be related to water stress at early stages, before structural changes occurred. A method based on an ordinal logit regression model was proposed to map water stress classes based on airborne hyperspectral imagery. PRI570 showed the highest performances when fitted against water stress classes, identified by the irrigation amounts applied in the field, and was therefore used to map water stress in the maize field. This study proves the feasibility of mapping stress classes using hyperspectral indices and demonstrates the potential applicability of remote sensing data in precision agriculture for optimizing irrigation management.
    ISPRS Journal of Photogrammetry and Remote Sensing 01/2013; 86:168–177. · 3.31 Impact Factor


Available from
May 22, 2014