scholarly journals Global‐scale consistency of spaceborne vegetation indices, chlorophyll fluorescence, and photosynthesis

2021 ◽  
Author(s):  
Russell Doughty ◽  
Xiangming Xiao ◽  
Philipp Köhler ◽  
Christian Frankenberg ◽  
Yuanwei Qin ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Vegetation Indices ◽  
Global Scale

scholarly journals Rapid Quantification of Microalgae Growth with Hyperspectral Camera and Vegetation Indices

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 341
Author(s):  
Pauliina Salmi ◽  
Matti A. Eskelinen ◽  
Matti T. Leppänen ◽  
Ilkka Pölönen
Keyword(s):  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Hyperspectral Data ◽  
Strong Correlations ◽  
Algae Biomass ◽  
Chlorophyll A Concentration ◽  
Cost Efficient ◽  
Hyperspectral Camera

Spectral cameras are traditionally used in remote sensing of microalgae, but increasingly also in laboratory-scale applications, to study and monitor algae biomass in cultures. Practical and cost-efficient protocols for collecting and analyzing hyperspectral data are currently needed. The purpose of this study was to test a commercial, easy-to-use hyperspectral camera to monitor the growth of different algae strains in liquid samples. Indices calculated from wavebands from transmission imaging were compared against algae abundance and wet biomass obtained from an electronic cell counter, chlorophyll a concentration, and chlorophyll fluorescence. A ratio of selected wavebands containing near-infrared and red turned out to be a powerful index because it was simple to calculate and interpret, yet it yielded strong correlations to abundances strain-specifically (0.85 < r < 0.96, p < 0.001). When all the indices formulated as A/B, A/(A + B) or (A − B)/(A + B), where A and B were wavebands of the spectral camera, were scrutinized, good correlations were found amongst them for biomass of each strain (0.66 < r < 0.98, p < 0.001). Comparison of near-infrared/red index to chlorophyll a concentration demonstrated that small-celled strains had higher chlorophyll absorbance compared to strains with larger cells. The comparison of spectral imaging to chlorophyll fluorescence was done for one strain of green algae and yielded strong correlations (near-infrared/red, r = 0.97, p < 0.001). Consequently, we described a simple imaging setup and information extraction based on vegetation indices that could be used to monitor algae cultures.

Early stress detection in grapevine – can remotely-sensed sun-induced chlorophyll fluorescence do the job?

2021 ◽  
Author(s):  
Georg Wohlfahrt ◽  
Albin Hammerle ◽  
Barbara Rainer ◽  
Florian Haas
Keyword(s):  
Chlorophyll Fluorescence ◽  
Vegetation Index ◽  
Near Infrared ◽  
Census Data ◽  
Meteorological Data ◽  
Vegetation Indices ◽  
Wavelength Region ◽  
Remote Sensing Data ◽  
Warning Signs ◽  
Mitigation Measures

&lt;p&gt;Ongoing changes in climate (both in the means and the extremes) are increasingly challenging grapevine production in the province of South Tyrol (Italy). Here we ask the question whether sun-induced chlorophyll fluorescence (SIF) observed remotely from space can detect early warning signs of stress in grapevine and thus help guide mitigation measures.&lt;/p&gt;&lt;p&gt;Chlorophyll fluorescence refers to light absorbed by chlorophyll molecules that is re-emitted in the red to far-red wavelength region. Previous research at leaf and canopy scale indicated that SIF correlates with the plant photosynthetic uptake of carbon dioxide as it competes for the same energy pool.&lt;/p&gt;&lt;p&gt;To address this question, we use time series of two down-scaled SIF products (GOME-2 and OCO-2, 2007/14-2018) as well as the original OCO-2 data (2014-2019). As a benchmark, we use several vegetation indices related to canopy greenness, as well as a novel near-infrared radiation-based vegetation index (2000-2019). Meteorological data fields are used to explore possible weather-related causes for observed deviations in remote sensing data. Regional DOC grapevine census data (2000-2019) are used as a reference for the analyses.&lt;/p&gt;

scholarly journals Evaluation of a Global Vegetation Model using time series of satellite vegetation indices

2011 ◽  
Vol 4 (4) ◽  
pp. 1103-1114 ◽  
Author(s):  
F. Maignan ◽  
F.-M. Bréon ◽  
F. Chevallier ◽  
N. Viovy ◽  
P. Ciais ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Global Scale ◽  
Vegetation Dynamic ◽  
Rate Of Increase ◽  
Vegetation Models ◽  
Global Vegetation ◽  
The Impact

Abstract. Atmospheric CO2 drives most of the greenhouse effect increase. One major uncertainty on the future rate of increase of CO2 in the atmosphere is the impact of the anticipated climate change on the vegetation. Dynamic Global Vegetation Models (DGVM) are used to address this question. ORCHIDEE is such a DGVM that has proven useful for climate change studies. However, there is no objective and methodological way to accurately assess each new available version on the global scale. In this paper, we submit a methodological evaluation of ORCHIDEE by correlating satellite-derived Vegetation Index time series against those of the modeled Fraction of absorbed Photosynthetically Active Radiation (FPAR). A perfect correlation between the two is not expected, however an improvement of the model should lead to an increase of the overall performance. We detail two case studies in which model improvements are demonstrated, using our methodology. In the first one, a new phenology version in ORCHIDEE is shown to bring a significant impact on the simulated annual cycles, in particular for C3 Grasses and C3 Crops. In the second case study, we compare the simulations when using two different weather fields to drive ORCHIDEE. The ERA-Interim forcing leads to a better description of the FPAR interannual anomalies than the simulation forced by a mixed CRU-NCEP dataset. This work shows that long time series of satellite observations, despite their uncertainties, can identify weaknesses in global vegetation models, a necessary first step to improving them.

scholarly journals The Solar-Induced Chlorophyll Fluorescence Imaging Spectrometer (SIFIS) Onboard the First Terrestrial Ecosystem Carbon Inventory Satellite (TECIS-1): Specifications and Prospects

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 815 ◽  
Author(s):  
Shanshan Du ◽  
Liangyun Liu ◽  
Xinjie Liu ◽  
Xinwei Zhang ◽  
Xianlian Gao ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Signal To Noise Ratio ◽  
Simulated Data ◽  
Terrestrial Ecosystem ◽  
Global Scale ◽  
Terrestrial Vegetation ◽  
Atmospheric Transmission ◽  
Imaging Spectrometer ◽  
Ecosystem Carbon ◽  
Carbon Inventory

The global monitoring of solar-induced chlorophyll fluorescence (SIF) using satellite-based observations provides a new way of monitoring the status of terrestrial vegetation photosynthesis on a global scale. Several global SIF products that make use of atmospheric satellite data have been successfully developed in recent decades. The Terrestrial Ecosystem Carbon Inventory Satellite (TECIS-1), the first Chinese terrestrial ecosystem carbon inventory satellite, which is due to be launched in 2021, will carry an imaging spectrometer specifically designed for SIF monitoring. Here, we use an extensive set of simulated data derived from the MODerate resolution atmospheric TRANsmission 5 (MODTRAN 5) and Soil Canopy Observation Photosynthesis and Energy (SCOPE) models to evaluate and optimize the specifications of the SIF Imaging Spectrometer (SIFIS) onboard TECIS for accurate SIF retrievals. The wide spectral range of 670−780 nm was recommended to obtain the SIF at both the red and far-red bands. The results illustrate that the combination of a spectral resolution (SR) of 0.1 nm and a signal-to-noise ratio (SNR) of 127 performs better than an SR of 0.3 nm and SNR of 322 or an SR of 0.5 nm and SNR of 472 nm. The resulting SIF retrievals have a root-mean-squared (RMS) diff* value of 0.15 mW m−2 sr−1 nm−1 at the far-red band and 0.43 mW m−2 sr−1 nm−1 at the red band. This compares with 0.20 and 0.26 mW m−2 sr−1 nm−1 at the far-red band and 0.62 and 1.30 mW m−2 sr−1 nm−1 at the red band for the other two configurations described above. Given an SR of 0.3 nm, the increase in the SNR can also improve the SIF retrieval at both bands. If the SNR is improved to 450, the RMS diff* will be 0.17 mW m−2 sr−1 nm−1 at the far-red band and 0.47 mW m−2 sr−1 nm−1 at the red band. Therefore, the SIFIS onboard TECIS-1 will provide another set of observations dedicated to monitoring SIF at the global scale, which will benefit investigations of terrestrial vegetation photosynthesis from space.

scholarly journals Wide discrepancies in the magnitude and direction of modeled solar-induced chlorophyll fluorescence in response to light conditions

2020 ◽  
Vol 17 (13) ◽  
pp. 3733-3755 ◽  
Author(s):  
Nicholas C. Parazoo ◽  
Troy Magney ◽  
Alex Norton ◽  
Brett Raczka ◽  
Cédric Bacour ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Canopy Structure ◽  
Fluorescence Emission ◽  
Light Response ◽  
Global Scale ◽  
Primary Objective ◽  
Mechanistic Modeling ◽  
Quantum Yields ◽  
Fluorescence Quantum Yields ◽  
Community Land Model

Abstract. Recent successes in passive remote sensing of far-red solar-induced chlorophyll fluorescence (SIF) have spurred the development and integration of canopy-level fluorescence models in global terrestrial biosphere models (TBMs) for climate and carbon cycle research. The interaction of fluorescence with photochemistry at the leaf and canopy scales provides opportunities to diagnose and constrain model simulations of photosynthesis and related processes, through direct comparison to and assimilation of tower, airborne, and satellite data. TBMs describe key processes related to the absorption of sunlight, leaf-level fluorescence emission, scattering, and reabsorption throughout the canopy. Here, we analyze simulations from an ensemble of process-based TBM–SIF models (SiB3 – Simple Biosphere Model, SiB4, CLM4.5 – Community Land Model, CLM5.0, BETHY – Biosphere Energy Transfer Hydrology, ORCHIDEE – Organizing Carbon and Hydrology In Dynamic Ecosystems, and BEPS – Boreal Ecosystems Productivity Simulator) and the SCOPE (Soil Canopy Observation Photosynthesis Energy) canopy radiation and vegetation model at a subalpine evergreen needleleaf forest near Niwot Ridge, Colorado. These models are forced with local meteorology and analyzed against tower-based continuous far-red SIF and gross-primary-productivity-partitioned (GPP) eddy covariance data at diurnal and synoptic scales during the growing season (July–August 2017). Our primary objective is to summarize the site-level state of the art in TBM–SIF modeling over a relatively short time period (summer) when light, canopy structure, and pigments are similar, setting the stage for regional- to global-scale analyses. We find that these models are generally well constrained in simulating photosynthetic yield but show strongly divergent patterns in the simulation of absorbed photosynthetic active radiation (PAR), absolute GPP and fluorescence, quantum yields, and light response at the leaf and canopy scales. This study highlights the need for mechanistic modeling of nonphotochemical quenching in stressed and unstressed environments and improved the representation of light absorption (APAR), distribution of light across sunlit and shaded leaves, and radiative transfer from the leaf to the canopy scale.

scholarly journals The Ongoing Greening in Southwest China despite Severe Droughts and Drying Trends

2021 ◽  
Vol 13 (17) ◽  
pp. 3374
Author(s):  
Xin Chen ◽  
Tiexi Chen ◽  
Qingyun Yan ◽  
Jiangtao Cai ◽  
Renjie Guo ◽  
...  
Keyword(s):  
Vegetation Change ◽  
Vegetation Index ◽  
Southwest China ◽  
Vegetation Indices ◽  
Climate Extremes ◽  
Global Scale ◽  
Area Index ◽  
Huge Impact ◽  
Increasing Trends

Vegetation greening, which refers to the interannual increasing trends of vegetation greenness, has been widely found on the regional to global scale. Meanwhile, climate extremes, especially several drought, significantly damage vegetation. The Southwest China (SWC) region experienced massive drought from 2009 to 2012, which severely damaged vegetation and had a huge impact on agricultural systems and life. However, whether these extremes have significantly influenced long-term (multiple decades) vegetation change is unclear. Using the latest remote sensing-based records, including leaf area index (LAI) and gross primary productivity (GPP) for 1982–2016 and enhanced vegetation index (EVI) for 2001–2019, drought events of 2009–2012 only leveled off the greening (increasing in vegetation indices and GPP) temporally and long-term greening was maintained. Meanwhile, drying trends were found to unexpectedly coexist with greening.

scholarly journals On the impact of canopy model complexity on simulated carbon, water, and solar-induced chlorophyll fluorescence fluxes

2021 ◽  
Author(s):  
Yujie Wang ◽  
Christian Frankenberg
Keyword(s):  
Chlorophyll Fluorescence ◽  
Land Surface ◽  
Climate Modeling ◽  
Global Scale ◽  
Model Complexity ◽  
Transfer Scheme ◽  
Sun Sensor ◽  
Sensor Geometry ◽  
The Impact ◽  
Canopy Model

Abstract. Lack of direct carbon, water, and energy flux observations at global scales makes it difficult to calibrate land surface models (LSMs). The increasing number of remote sensing based products provide an alternative way to verify or constrain land models given its global coverage and satisfactory spatial and temporal resolutions. However, these products and LSMs often differ in their assumptions and model setups, for example, the canopy model complexity. The disagreements hamper the fusion of global scale datasets with LSMs. To evaluate how much the canopy complexity affects predicted canopy fluxes, we simulated and compared the carbon, water, and solar-induced chlorophyll fluorescence (SIF) fluxes using five different canopy complexity setups from a one-layered big-leaf canopy to a multi-layered canopy with leaf angular distributions. We modeled the canopy fluxes using a recently developed Land model by the Climate Modeling Alliance. Our model results suggested that (1) when using the same model inputs, model predicted carbon, water, and SIF fluxes were all higher for simpler canopy setups; (2) when accounting for vertical photosynthetic capacity heterogeneity, differences among canopy complexity levels increased compared to the scenario of a uniform canopy; (3) SIF fluxes modeled with different canopy complexity levels changed with sun-sensor geometry. Given the different modeled canopy fluxes with different canopy complexities, we recommend (1) not misusing parameters inverted with different canopy complexities or assumptions to avoid biases in model outputs, and (2) using complex canopy model with angular distribution and hyperspectral radiation transfer scheme when linking land processes to remotely sensed spectra.

scholarly journals Chlorophyll fluorescence remote sensing from space in scattering atmospheres: implications for its retrieval and interferences with atmospheric CO<sub>2</sub> retrievals

2012 ◽  
Vol 5 (2) ◽  
pp. 2487-2527 ◽  
Author(s):  
C. Frankenberg ◽  
C. O'Dell ◽  
L. Guanter ◽  
J. McDuffie
Keyword(s):  
Chlorophyll Fluorescence ◽  
Greenhouse Gas ◽  
Global Scale ◽  
Oxygen Absorption ◽  
Random Errors ◽  
Solar Absorption ◽  
Systematic Biases ◽  
Gas Space ◽  
Spectral Ranges ◽  
Absorption Features

Abstract. With the advent of dedicated greenhouse-gas space-borne spectrometers sporting high resolution spectra in the O2 A-band spectral region (755–774 nm), the retrieval of chlorophyll fluorescence has become feasible on a global scale. If unaccounted for, however, fluorescence can indirectly perturb the greenhouse gas retrievals as it perturbs the oxygen absorption features. As atmospheric CO2 measurements are used to invert net fluxes at the land-atmosphere interface, a bias caused by fluorescence can be crucial as it will spatially correlate with the fluxes to be inverted. Avoiding a bias and retrieving fluorescence accurately will provide additional constraints on both the net and gross fluxes in the global carbon cycle. We show that chlorophyll fluorescence, if neglected, systematically interferes with full-physics multi-band XCO2 retrievals using the O2 A-band. Systematic biases in XCO2 can amount to +1 ppm if fluorescence constitutes 1% to the continuum level radiance. We show that this bias can be largely eliminated by simultaneously fitting fluorescence in a full-physics based retrieval. If fluorescence is the primary target, a dedicated but very simple retrieval based purely on Fraunhofer lines is shown to be more accurate and very robust even in the presence of large scattering optical depths. We find that about 80% of the surface fluorescence is retained at the top-of-atmosphere even for cloud optical thicknesses around 2–5. We further show that small instrument modifications to future O2 A-band spectrometer spectral ranges can result in largely reduced random errors in chlorophyll fluorescence, paving the way towards a more dedicated instrument exploiting solar absorption features only.

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