Antarctic moss stress assessment based on chlorophyll content and leaf density retrieved from imaging spectroscopy data

Malenovský, Zbyněk; Turnbull, Johanna D.; Lucieer, Arko; Robinson, Sharon A.

doi:10.1111/nph.13524

Cited by 53 publications

(46 citation statements)

References 71 publications

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“…The original digital number ( DN ) values were converted to relative reflectance. The calibration equation was as follows [27]:

R e f_{target} = \frac{D N_{target} - D N_{noise}}{D N_{panel} - D N_{noise}} \times R e f_{panel}

where DN target , DN noise and DN panel refer to the DN value of target, electronic noise and reference panel, respectively. Ref target and Ref panel refer to the reflectance value of target and reference panel, respectively.…”

Section: Methodsmentioning

confidence: 99%

Assessing the Spectral Properties of Sunlit and Shaded Components in Rice Canopies with Near-Ground Imaging Spectroscopy Data

Zhou

Deng

Yao

et al. 2017

Sensors

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Monitoring the components of crop canopies with remote sensing can help us understand the within-canopy variation in spectral properties and resolve the sources of uncertainties in the spectroscopic estimation of crop foliar chemistry. To date, the spectral properties of leaves and panicles in crop canopies and the shadow effects on their spectral variation remain poorly understood due to the insufficient spatial resolution of traditional spectroscopy data. To address this issue, we used a near-ground imaging spectroscopy system with high spatial and spectral resolutions to examine the spectral properties of rice leaves and panicles in sunlit and shaded portions of canopies and evaluate the effect of shadows on the relationships between spectral indices of leaves and foliar chlorophyll content. The results demonstrated that the shaded components exhibited lower reflectance amplitude but stronger absorption features than their sunlit counterparts. Specifically, the reflectance spectra of panicles had unique double-peak absorption features in the blue region. Among the examined vegetation indices (VIs), significant differences were found in the photochemical reflectance index (PRI) between leaves and panicles and further differences in the transformed chlorophyll absorption reflectance index (TCARI) between sunlit and shaded components. After an image-level separation of canopy components with these two indices, statistical analyses revealed much higher correlations between canopy chlorophyll content and both PRI and TCARI of shaded leaves than for those of sunlit leaves. In contrast, the red edge chlorophyll index (CIRed-edge) exhibited the strongest correlations with canopy chlorophyll content among all vegetation indices examined regardless of shadows on leaves. These findings represent significant advances in the understanding of rice leaf and panicle spectral properties under natural light conditions and demonstrate the significance of commonly overlooked shaded leaves in the canopy when correlated to canopy chlorophyll content.

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“…The original digital number ( DN ) values were converted to relative reflectance. The calibration equation was as follows [27]:

R e f_{target} = \frac{D N_{target} - D N_{noise}}{D N_{panel} - D N_{noise}} \times R e f_{panel}

Section: Methodsmentioning

confidence: 99%

Assessing the Spectral Properties of Sunlit and Shaded Components in Rice Canopies with Near-Ground Imaging Spectroscopy Data

Zhou

Deng

Yao

et al. 2017

Sensors

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“…As many recent studies have proved, laboratory measurements of leaf optical properties in the visible and infrared regions are a valuable technique for understanding different plant physiological processes and stress detection [1,2,3,4,5], as well as photosynthesis efficiency evaluation, energy balance calculation, global terrestrial net primary productivity modelling [6,7,8,9] or vegetation stress detection [10,11,12,13,14]. Despite its wide applications, significant measurement uncertainties and knowledge gaps exist.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Reflectance Measurements Acquired with a Contact Probe and an Integration Sphere: Implications for the Spectral Properties of Vegetation at a Leaf Level

Potůčková

Červená

Kupková

et al. 2016

Sensors

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Laboratory spectroscopy in visible and infrared regions is an important tool for studies dealing with plant ecophysiology and early recognition of plant stress due to changing environmental conditions. Leaf optical properties are typically acquired with a spectroradiometer coupled with an integration sphere (IS) in a laboratory or with a contact probe (CP), which has the advantage of operating flexibility and the provision of repetitive in-situ reflectance measurements. Experiments comparing reflectance spectra measured with different devices and device settings are rarely reported in literature. Thus, in our study we focused on a comparison of spectra collected with two ISs on identical samples ranging from a Spectralon and coloured papers as reference standards to vegetation samples with broadleaved (Nicotiana Rustica L.) and coniferous (Picea abies L. Karst.) leaf types. First, statistical measures such as mean absolute difference, median of differences, standard deviation and paired-sample t-test were applied in order to evaluate differences between collected reflectance values. The possibility of linear transformation between spectra was also tested. Moreover, correlation between normalised differential indexes (NDI) derived for each device and all combinations of wavelengths between 450 nm and 1800 nm were assessed. Finally, relationships between laboratory measured leaf compounds (total chlorophyll, carotenoids and water content), NDI and selected spectral indices often used in remote sensing were studied. The results showed differences between spectra acquired with different devices. While differences were negligible in the case of the Spectralon and they were possible to be modelled with a linear transformation in the case of coloured papers, the spectra collected with the CP and the ISs differed significantly in the case of vegetation samples. Regarding the spectral indices calculated from the reflectance data collected with the three devices, their mean values were in the range of the corresponding standard deviations in the case of broadleaved leaf type. Larger differences in optical leaf properties of spruce needles collected with the CP and ISs are implicated from the different measurement procedure due to needle-like leaf where shoots with spatially oriented needles were measured with the CP and individual needles with the IS. The study shows that a direct comparison between the spectra collected with two devices is not advisable as spectrally dependent offsets may likely exist. We propose that the future studies shall focus on standardisation of measurement procedures so that open access spectral libraries could serve as a reliable input for modelling of optical properties on a leaf level.

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“…Malenovský et al. () demonstrated that this approach is transferable from standardized laboratory spectral measurements to ground‐based Antarctic moss hyperspectral images of matching wavelengths acquired at different field locations. This study scales the approach further to airborne (UAS) and WorldView‐2 (WV2) satellite spectral imagery.…”

Section: Methodsmentioning

confidence: 99%

“…We used the epsilon‐SVR training optimization technique with the nonlinear Gaussian radial basis function (RBF) kernel to estimate Cab and ELD as described in Malenovský et al. (). The laboratory reflectance measurements of moss canopies, acquired in 2013 and 1999 with a sampling interval of 1 nm, were first convolved in bandwidths and spectral sampling intervals of WV2 and micro‐Hyperspec sensors in accordance with their specific spectral response functions.…”

Section: Methodsmentioning

confidence: 99%

“…In the long-term, a range of environmental pressures may reduce stem elongation and increase leaf density (Clarke et al, 2012;Potters, Pasternak, Guisez, & Jansen, 2009;Waite & Sack, 2010). In the short-term, ELD can increase rapidly as a result of sudden reversible leaf shrinking and curling due to water loss (for more details see Malenovský, Turnbull, Lucieer, & Robinson, 2015).…”

Section: Study Sites Species and Plant Characteristicsmentioning

confidence: 99%

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Unmanned aircraft system advances health mapping of fragile polar vegetation

et al. 2017

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Plants like mosses can be sensitive stress markers of subtle shifts in Arctic and Antarctic environmental conditions, including climate change. Traditional ground‐based monitoring of fragile polar vegetation is, however, invasive, labour intensive and physically demanding. High‐resolution multispectral satellite observations are an alternative, but even their recent highest achievable spatial resolution is still inadequate, resulting in a significant underestimation of plant health due to spectral mixing and associated reflectance impurities. To resolve these obstacles, we have developed a new method that uses low‐altitude unmanned aircraft system (UAS) hyperspectral images of sub‐decimeter spatial resolution. Machine‐learning support vector regressions (SVR) were employed to infer Antarctic moss vigour from quantitative remote sensing maps of plant canopy chlorophyll content and leaf density. The same maps were derived for comparison purposes from the WorldView‐2 high spatial resolution (2.2 m) multispectral satellite data. We found SVR algorithms to be highly efficient in estimating plant health indicators with acceptable root mean square errors (RMSE). The systematic RMSEs for chlorophyll content and leaf density were 3.5–6.0 and 1.3–2.0 times smaller, respectively, than the unsystematic errors. However, application of correctly trained SVR machines on space‐borne multispectral images considerably underestimated moss chlorophyll content, while stress indicators retrieved from UAS data were found to be comparable with independent field measurements, providing statistically significant regression coefficients of determination (median r2 = .50, pt test = .0072). This study demonstrates the superior performance of a cost‐efficient UAS mapping platform, which can be deployed even under the continuous cloud cover that often obscures optical high‐altitude airborne and satellite observations. Antarctic moss vigour maps of appropriate resolution could provide timely and spatially explicit warnings of environmental stress events, including those triggered by climate change. Since our polar vegetation health assessment method is based on physical principles of quantitative spectroscopy, it could be adapted to other short‐stature and fragmented plant communities (e.g. tundra grasslands), including alpine and desert regions. It therefore shows potential to become an operational component of any ecological monitoring sensor network.

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Antarctic moss stress assessment based on chlorophyll content and leaf density retrieved from imaging spectroscopy data

Cited by 53 publications

References 71 publications

Assessing the Spectral Properties of Sunlit and Shaded Components in Rice Canopies with Near-Ground Imaging Spectroscopy Data

Assessing the Spectral Properties of Sunlit and Shaded Components in Rice Canopies with Near-Ground Imaging Spectroscopy Data

Comparison of Reflectance Measurements Acquired with a Contact Probe and an Integration Sphere: Implications for the Spectral Properties of Vegetation at a Leaf Level

Unmanned aircraft system advances health mapping of fragile polar vegetation

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