Measurement methods and variability assessment of the Norway spruce total leaf area: implications for remote sensing

Estimation of total leaf area (LAT) is important to express biochemical properties in plant ecology and remote sensing studies. A measurement of LAT is easy in broadleaf species, but it remains challenging in coniferous canopies. We proposed a new geometrical model to estimate Norway spruce LAT and compared its accuracy with other five published methods. Further, we assessed variability of the total to projected leaf area conversion factor (CF) within a crown and examined its implications for remotely sensed estimates of leaf chlorophyll content (Cab). We measured morphological and biochemical properties of three most recent needle age classes in three vertical canopy layers of a 30 and 100-year-old spruce stands. Newly introduced geometrical model and the parallelepiped model predicted spruce LAT with an error \u3e5 % of the average needle LAT, whereas two models based on an elliptic approximation of a needle shape underestimated LAT by up to 60 %. The total to projected leaf area conversion factor varied from 2. 5 for shaded to 3. 9 for sun exposed needles and remained invariant with needle age class and forest stand age. Erroneous estimation of an average crown CF by 0. 2 introduced an error of 2-3 μg cm-2 into the crown averaged Cab content. In our study, this error represents 10-15 % of observed crown averaged Cab range (33-53 μg cm-2). Our results demonstrate the importance of accurate LAT estimates for validation of remotely sensed estimates of Cab content in Norway spruce canopies

Measuring solar-induced fluorescence from unmanned aircraft systems for operational use in plant phenotyping and precision farming

Demand for high spatial and temporal resolution measurements has triggered a rapid development of unmanned aircraft systems (UAS) for plant phenotyping and precision farming purposes. Similarly, recent progress in low-altitude remote sensing of solar-induced chlorophyll fluorescence (SIF) resulted in several studies aiming at the development of SIF proximal sensing approaches. Although first experimental results are promising, the requirements for reliable and repeatable measurements in agricultural experiments still constrain applicability of these platforms. In this study, we analyze current capabilities and potentials of SIF measuring UAS for operational use. We highlight existing challenges and outline how UAS SIF sensing could be used more frequently and reliably in precision agriculture applications in the near future.Peer reviewe

Relation of chlorophyll fluorescence sensitive reflectance ratios to carbon flux measurements of Montanne grassland and Norway spruce forest ecosystems in the temperate zone

We explored ability of reflectance vegetation indexes (VIs) related to chlorophyll fluorescence emission (R686/R630, R 740/R800) and de-epoxidation state of xanthophyll cycle pigments (PRI, calculated as (R531 - R570) (R 531 - R570)) to track changes in the CO2 assimilation rate and Light Use Efficiency (LUE) in montane grassland and Norway spruce forest ecosystems, both at leaf and also canopy level. VIs were measured at two research plots using a ground-based high spatial/spectral resolution imaging spectroscopy technique. No significant relationship between VIs and leaf light-saturated CO2 assimilation (AMAX) was detected in instantaneous measurements of grassland under steady-state irradiance conditions. Once the temporal dimension and daily irradiance variation were included into the experimental setup, statistically significant changes in VIs related to tested physiological parameters were revealed. ΔPRI and Δ(R686 R630) of grassland plant leaves under dark-to-full sunlight transition in the scale of minutes were significantly related to AMAX (R2 = 0.51). In the daily course, the variation of VIs measured in one-hour intervals correlated well with the variation of Gross Primary Production (GPP), Net Ecosystem Exchange (NEE), and LUE estimated via the eddy-covariance flux tower. Statistical results were weaker in the case of the grassland ecosystem, with the strongest statistical relation of the index R686 R630 with NEE and GPP

Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science

Remote sensing methods enable detection of solar-induced chlorophyll a fluorescence. However, to unleash the full potential of this signal, intensive cross-disciplinary work is required to harmonize biophysical and ecophysiological studies. For decades, the dynamic nature of chlorophyll a fluorescence (ChlaF) has provided insight into the biophysics and ecophysiology of the light reactions of photosynthesis from the subcellular to leaf scales. Recent advances in remote sensing methods enable detection of ChlaF induced by sunlight across a range of larger scales, from using instruments mounted on towers above plant canopies to Earth-orbiting satellites. This signal is referred to as solar-induced fluorescence (SIF) and its application promises to overcome spatial constraints on studies of photosynthesis, opening new research directions and opportunities in ecology, ecophysiology, biogeochemistry, agriculture and forestry. However, to unleash the full potential of SIF, intensive cross-disciplinary work is required to harmonize these new advances with the rich history of biophysical and ecophysiological studies of ChlaF, fostering the development of next-generation plant physiological and Earth-system models. Here, we introduce the scale-dependent link between SIF and photosynthesis, with an emphasis on seven remaining scientific challenges, and present a roadmap to facilitate future collaborative research towards new applications of SIF.Peer reviewe

Empirical test of the spectral invariants theory using imaging spectroscopy data from a coniferous forest

The spectral invariants theory presents an alternative approach for modeling canopy scattering in remote sensing applications. The theory is particularly appealing in the case of coniferous forests, which typically display grouped structures and require computationally intensive calculation to account for the geometric arrangement of their canopies. However, the validity of the spectral invariants theory should be tested with empirical data sets from different vegetation types. In this paper, we evaluate a method to retrieve two canopy spectral invariants, the recollision probability and the escape factor, for a coniferous forest using imaging spectroscopy data from multiangular CHRIS PROBA and NADIR-view AISA Eagle sensors. Our results indicated that in coniferous canopies the spectral invariants theory performs well in the near infrared spectral range. In the visible range, on the other hand, the spectral invariants theory may not be useful. Secondly, our study suggested that retrieval of the escape factor could be used as a new method to describe the BRDF of a canopy

Near-distance imaging spectroscopy investigating chlorophyll fluorescence and photosynthetic activity of grassland in the daily course

Detection of grassland canopy chlorophyll fluorescence (Chl-F) conducted with an imaging spectroradiometer provided evidence of potential remote sensing estimation of steady-state Chl-F (Chl-Fs). Daily near-nadir views of extremely high spatial resolution hyperspectral images were acquired from a distance of 4m for temperate montane grassland in the Czech Republic. Simultaneously, measurements of Chl-F and total chlorophyll content (Chl a+b) were made on a single leaf at ground level were collected. A specifically designed \u27shade removal\u27 experiment revealed the influence of dynamic physiological plant processes on hyperspectral reflectance of three wavelengths: 532, 686 and 740nm. Based on this information, the vegetation indexes R686/R630, R740/R800 and PRI calculated as (R532R570)/(R532+R 570) were tested for statistical significance with directly measured Chl-F parameters (maximum fluorescence yield, Fv/Fm; steady-state chlorophyll fluorescence, Chl-Fs and actual quantum yield, ΠII). The grassland species under investigation were: Festuca rubra agg. (L.), Hieracium sp., Plantago sp., Nardus stricta (L.) and Jacea pseudophrygia (C.A. Meyer). The coefficients of determination (R 2) for best-fit relationships between PRI-ΠII and PRI-Chl-Fs, measured in the daily course, show a high variability of 0.230.78 and 0.200.65, respectively. Similarly, R2 for the R 686/R630-ΠII and R686/R 630-Chl-Fs relationships varied between 0.200.73 and 0.410.70, respectively. The highest average R2 values were found between PRI and Chla+b (0.63) and R686/R630 and Chla+b (0.72). The ratio R740/R800 did not yield a statistically significant relation with Chl-F parameters

A note on upscaling coniferous needle spectra to shoot spectral albedo

Mutual shading of needles in coniferous shoots and small-scale variations in needle area density both within and between shoots violate conventional assumptions used in the definition of the elementary volume in radiative transfer models. In this paper, we test the hypothesis if it is possible to scale needle spectral albedo up to shoot spectral albedo using only one structural parameter: the spherically averaged shoot silhouette to total area ratio (STAR). To test the hypothesis, we measured both structural and spectral properties of ten Scots pine (Pinus sylvestris) shoots and their needles. Our results indicate that it is possible to upscale from needle to shoot spectral albedo using STAR. The upscaling model performed best in the VIS and SWIR regions, and for shoots with high STAR values. As STAR is linearly related to photon recollision probability, it is also possible to apply the upscaling model as integral part of radiative transfer models

Retrieval of spruce leaf chlorophyll content from airborne image data using continuum removal and radiative transfer

We investigate combined continuum removal and radiative transfer (RT) modeling to retrieve leaf chlorophyll a & b content (Cab) from the AISA Eagle airborne imaging spectrometer data of sub-meter (0.4 m) spatial resolution. Based on coupled PROSPECT-DART RT simulations of a Norway spruce (Picea abies (L.) Karst.) stand, we propose a new Cab sensitive index located between 650 and 720 nm and termed ANCB650-720. The performance of ANCB650-720 was validated against ground-measured Cab of ten spruce crowns and compared with Cab estimated by a conventional artificial neural network (ANN) trained with continuum removed RT simulations and also by three previously published chlorophyll optical indices: normalized difference between reflectance at 925 and 710 nm (ND925&710), simple reflectance ratio between 750 and 710 nm (SR750/710) and the ratio of TCARI/OSAVI indices. Although all retrieval methods produced visually comparable Cab spatial patterns, the ground validation revealed that the ANCB650-720 and ANN retrievals are more accurate than the other three chlorophyll indices (R2 = 0.72 for both methods). ANCB650-720 estimated Cab with an RMSE = 2.27 μg cm− 2 (relative RRMSE = 4.35%) and ANN with an RMSE = 2.18 μg cm− 2 (RRMSE = 4.18%), while SR750/710 with an RMSE = 4.16 μg cm− 2 (RRMSE = 7.97%), ND925&710 with an RMSE = 9.07 μg cm− 2 (RRMSE = 17.38%) and TCARI/OSAVI with an RMSE = 12.30 μg cm− 2 (RRMSE = 23.56%). Also the systematic RMSES was lower than the unsystematic one only for the ANCB650-720 and ANN retrievals. Our results indicate that the newly proposed index can provide the same accuracy as ANN except for Cab values below 30 μg cm− 2, which are slightly overestimated (RMSE = 2.42 μg cm− 2). The computationally efficient ANCB650-720 retrieval provides accurate high spatial resolution airborne Cab maps, considerable as a suitable reference data for validating satellite-based Cab products

Ground-based imaging spectroscopy data for estimation of Antarctic moss relative vigour from remotely sensed chlorophyll content and leaf density at ASPA 135

The ground-based imaging spectroscopy data were acquired with the Headwall Photonics Micro-Hyperspec VNIR scanner (Headwall Inc., USA) attached to a computer-controlled rotating/tilting platform. The sensor unit was placed approximately 2.5 m above the ground on a single pole mounted to a geodetic tripod. The Micro-Hyperspec is a push-broom scanner, which collects light passing through a lens objective with an aperture of f/2.8 (FOV of 49.8 degrees) and through a slit entrance of 25 microns. The spectral wavelengths are split by an aberration-corrected convex holographic diffraction grating and projected onto a charge-coupled device (CCD) matrix with a digital dynamic range of 12-bits and size of 1004 by 1004 pixel units. The CCD registers the captured light split into 324 (full spectral extent, FWHM of 4.12-4.67 nm) or 162 spectral bands (binning of two neighbouring spectral pixels as a single recording unit, FWHM of 4.75-5.25 nm). To ensure a high signal-to-noise ratio and to prevent oversaturation of the CCD dynamic range, the spectral binning (162 bands) combined with an integration time of 40 milliseconds (ms) was applied and oblique hyperspectral images (azimuth viewing angles of 44 degrees and 60 degrees) were collected at two test site

Physically-based retrievals of Norway spruce canopy variables from very high spatial resolution hyperspectral data

This study was conducted to answer two research questions: (1) what is the spatial variability of the leaf optical properties between 400-1600 nm (hemispherical-directional reflectance, transmittance, absorption) within young Norway spruce crowns, and (2) how to design a suitable physically-based approach retrieving the total chlorophyll content of a complex coniferous canopy from very high spatial resolution (0.4 m) hyperspectral data? It was proved that sun-exposed needles of current age-class statistically differ (alpha-level = 0.01) from rest of the needles in reflectance between 510-760 nm. Last four age-classes of sun-exposed needles were also found to be significantly different from almost all age-classes of sun-shaded needles in transmittance from 760-1350 nm. An operational estimation of chlorophyll a+b content (Cab) from an airborne AISA Eagle hyperspectral image was proposed by means of a PROSPECT-DART inversion employing an artificial neural network (ANN). A spatial pattern of estimated Cab was successfully validated against the Cab map produced by a vegetation index ANCB650-720. Coefficients of determination (R2) between ground measured and retrieved Cab were 0.81 and 0.83, respectively, with root mean square errors (RMSE) of 2.72 mug cm-2 for ANN and 3.27 mug cm-2 for ANCB650-720