Synergy between TROPOMI sun-induced chlorophyll fluorescence and MODIS spectral reflectance for understanding the dynamics of gross primary productivity at Integrated Carbon Observatory System (ICOS) ecosystem flux sites

An accurate estimation of vegetation gross primary productivity (GPP), which is the amount of carbon taken up by vegetation through photosynthesis for a given time and area, is critical for understanding terrestrial–atmosphere CO2 exchange processes and ecosystem functioning, as well as ecosystem responses and adaptations to climate change. Prior studies, based on ground, airborne, and satellite sun-induced chlorophyll fluorescence (SIF) observations, have recently revealed close relationships with GPP at different spatial and temporal scales and across different plant functional types (PFTs). However, questions remain regarding whether there is a unique relationship between SIF and GPP across different sites and PFTs and how we can improve GPP estimates using solely remotely sensed data. Using concurrent measurements of daily TROPOspheric Monitoring Instrument (TROPOMI) SIF (daily SIFd); daily MODIS Terra and Aqua spectral reflectance; vegetation indices (VIs, notably normalized difference vegetation index (NDVI), near-infrared reflectance of vegetation (NIRv), and photochemical reflectance index (PRI)); and daily tower-based GPP across eight major different PFTs, including mixed forests, deciduous broadleaf forests, croplands, evergreen broadleaf forests, evergreen needleleaf forests, grasslands, open shrubland, and wetlands, the strength of the relationships between tower-based GPP and SIFd at 40 Integrated Carbon Observation System (ICOS) flux sites was investigated. The synergy between SIFd and MODIS-based reflectance (R) and VIs to improve GPP estimates using a data-driven modeling approach was also evaluated. The results revealed that the strength of the hyperbolic relationship between GPP and SIFd was strongly site-specific and PFT-dependent. Furthermore, the generalized linear model (GLM), fitted between SIFd, GPP, and site and vegetation type as categorical variables, further supported this site- and PFT-dependent relationship between GPP and SIFd. Using random forest (RF) regression models with GPP as output and the aforementioned variables as predictors (R, SIFd, and VIs), this study also showed that the spectral reflectance bands (RF-R) and SIFd plus spectral reflectance (RF-SIF-R) models explained over 80 % of the seasonal and interannual variations in GPP, whereas the SIFd plus VI (RF-SIF-VI) model reproduced only 75 % of the tower-based GPP variance. In addition, the relative variable importance of predictors of GPP demonstrated that the spectral reflectance bands in the near-infrared, red, and SIFd appeared as the most influential and dominant factors determining GPP predictions, indicating the importance of canopy structure, biochemical properties, and vegetation functioning on GPP estimates. Overall, this study provides insights into understanding the strength of the relationships between GPP and SIF and the use of spectral reflectance and SIFd to improve estimates of GPP across sites and PFTs.</p

Linking phytoplankton pigment composition and optical properties: A framework for developing remote-sensing metrics for monitoring cyanobacteria

International audienceThis study has been performed in the framework of a research program aiming to develop a low-cost aerial sensor for the monitoring of cyanobacteria in freshwater ecosystems that could be used for early detection. Several empirical and mechanistic remote-sensing tools have been already developed and tested at large scales and have proven useful in monitoring cyanobacterial blooms. However, the effectiveness of these tools for early detection is hard to assess because such work requires the detection of low concentrations of characteristic pigments amid complex ecosystems exhibiting several confounding factors (turbidity, blooms of other species, etc.). We developed a framework for performing high-throughput measurements of the absorbance and reflectance of small volumes (~= 20 mL) of controlled mixtures of phytoplankton species and studied the potential of this framework to validate remote-sensing proxies of cyanobacteria concentration. The absorption and reflectance spectra of single and multiple cultures carried a specific signal that allowed for the quantitative analysis of culture mixes. This specific signal was shown to be related to known pigment absorbance spectra. The concentrations of chlorophyll-a and -b, phycocyanin and phycoerythrin could be obtained from direct absorbance measurements and were correlated with the concentration obtained after pigment extraction (R2 ≥ 0.96 for all pigments). A systematic test of every possible two-band and three-band normalized difference between optical indices was then performed, and the coincidental correlation with chlorophyll-b (absent in cyanobacteria) was used as an indicator of non-specificity. Two-band indices were shown to suffer from non-specificity issues and could not yield strong and specific relationships with phycocyanin or phycoerythrin (maximum R2  0.8)

Potential of proximal teledetection and modeling as a way to assess canopy structure and functioning

L’anticipation des effets des changements climatiques nécessite une bonne compréhension dufonctionnement carboné des écosystèmes continentaux. L’une des principales contraintes liées àl’étude de ces écosystèmes est la forte variabilité à la fois spatiale et temporelle de leurs flux decarbone et de leurs réponses aux contraintes abiotiques. L’usage de méthodes de télédétectionoptiques pourrait permettre de suivre de façon spatialisée le fonctionnement des couverts végétaux.Ce travail vise à évaluer le potentiel de méthodes de télédétection pour décrire la structure et lefonctionnement de couverts végétaux à des échelles spatiales et temporelles variées. Pour ce faire,les relations entre indices optiques et phénomènes biologiques ont été étudiées en suivant unedémarche de transfert d’échelle, des échelles les plus fines aux plus larges. Il a été montré que le PRI(Photochemical Reflectance Index), utilisé en tant qu’indicateur du LUE (Light Use Efficiency), est parnature un signal composite qui reflète principalement la régulation du rendement de laphotosynthèse sur des échelles de temps fines, et la structure et composition biochimique ducouvert à l’échelle de la saison. L’analyse de courbes de réponse du PRI au PAR (PhotosyntheticallyActive Radiation) a permis de déconvoluer ces deux sources de variabilité, via l’introduction duconcept de PRI0 ou PRI d’une feuille idéalement adaptée à l’obscurité. Ce PRI0, capturant la variabilitédu PRI indépendante du LUE, a pu être mesuré à l’échelle de la feuille, et estimé à l’échelle de jeunescouverts végétaux et de la parcelle. Cette variabilité a pu être expliquée à l’échelle de la feuille et dejeunes couverts végétaux par les variations du contenu en pigment des feuilles. A l’échelle depeuplements adultes et de l’année, elle résulte cependant d’effets combinés de la compositionbiochimique et de la structure des couverts qui n’ont pu être séparés. Ces effets sont susceptiblesaux échelles larges de masquer en bonne partie, voire de biaiser la relation entre PRI et LUE. Il a enoutre été montré que la représentativité du PRI est limitée aux strates supérieures des canopées etdépend de la structure du couvert et du climat lumineux, ce qui peut limiter son intérêt en tantqu’estimateur du LUE à l’échelle de l’écosystème. Ces résultats soulignent la nécessité de prendre encompte la structure et la composition biochimique des couverts végétaux dans le cadre d’uneutilisation du PRI en tant que proxy du LUE de l’écosystème.In order to assess the effect of global warming, a good understanding of carbon functioning ofterrestrial ecosystems is needed. The study of terrestrial ecosystem carbon fluxes and responses toabiotic stress remain challenging due to their high spatial and temporal variability. The use of remotesensing may help us to describe those sources of variability. The aim of this work is to assess thepotential of remote sensing as a way to describe canopy structure and functioning over a broadrange of temporal and spatial scales. The relationships between optical indices and biologicalphenomenon were investigated over a range of increasing scales. The PRI (PhotochemicalReflectance Index), used as a proxy of the LUE (Light Use Efficiency) was shown to be a compositesignal, mainly impacted by the regulation of the LUE at short time scales, and by canopy structureand pigment content at seasonal scale. The analysis of PRI response to PAR (PhotosyntheticallyActive Radiation) allowed us to deconvolve those two sources of variability thanks to theintroduction of the PRI0 defined as the PRI of ideally dark adapted leaves. The PRI0 was shown toefficiently describe the LUE unrelated PRI variability, and could be measured at leaf scale, andestimated at the leaf, canopy and stand scales. This variability could be explained by changes in leafpigment content over the growing season at leaf and canopy scales. At the stand scale and over theyear, this LUE independent PRI variability resulted from combined effects of canopy structure andpigment content, which could not be separated. These effects may result in biased or masked PRIversus LUE relationships at larges scales. Moreover, it was shown that the in-situ PRI measurementsmainly responded to the LUE of sunlit leaves, depending on canopy structure and sky conditions. Thismay considerably hamper the use of the PRI as a proxy of the whole ecosystem LUE. These resultsillustrate the need to take canopy structure and pigment content into account while using the PRI asa proxy of the ecosystem LUE

Apports de la télédétection rapprochée et de la modélisation à l’étude de la structure et du fonctionnement des couverts végétaux

In order to assess the effect of global warming, a good understanding of carbon functioning ofterrestrial ecosystems is needed. The study of terrestrial ecosystem carbon fluxes and responses toabiotic stress remain challenging due to their high spatial and temporal variability. The use of remotesensing may help us to describe those sources of variability. The aim of this work is to assess thepotential of remote sensing as a way to describe canopy structure and functioning over a broadrange of temporal and spatial scales. The relationships between optical indices and biologicalphenomenon were investigated over a range of increasing scales. The PRI (PhotochemicalReflectance Index), used as a proxy of the LUE (Light Use Efficiency) was shown to be a compositesignal, mainly impacted by the regulation of the LUE at short time scales, and by canopy structureand pigment content at seasonal scale. The analysis of PRI response to PAR (PhotosyntheticallyActive Radiation) allowed us to deconvolve those two sources of variability thanks to theintroduction of the PRI0 defined as the PRI of ideally dark adapted leaves. The PRI0 was shown toefficiently describe the LUE unrelated PRI variability, and could be measured at leaf scale, andestimated at the leaf, canopy and stand scales. This variability could be explained by changes in leafpigment content over the growing season at leaf and canopy scales. At the stand scale and over theyear, this LUE independent PRI variability resulted from combined effects of canopy structure andpigment content, which could not be separated. These effects may result in biased or masked PRIversus LUE relationships at larges scales. Moreover, it was shown that the in-situ PRI measurementsmainly responded to the LUE of sunlit leaves, depending on canopy structure and sky conditions. Thismay considerably hamper the use of the PRI as a proxy of the whole ecosystem LUE. These resultsillustrate the need to take canopy structure and pigment content into account while using the PRI asa proxy of the ecosystem LUE.L’anticipation des effets des changements climatiques nécessite une bonne compréhension dufonctionnement carboné des écosystèmes continentaux. L’une des principales contraintes liées àl’étude de ces écosystèmes est la forte variabilité à la fois spatiale et temporelle de leurs flux decarbone et de leurs réponses aux contraintes abiotiques. L’usage de méthodes de télédétectionoptiques pourrait permettre de suivre de façon spatialisée le fonctionnement des couverts végétaux.Ce travail vise à évaluer le potentiel de méthodes de télédétection pour décrire la structure et lefonctionnement de couverts végétaux à des échelles spatiales et temporelles variées. Pour ce faire,les relations entre indices optiques et phénomènes biologiques ont été étudiées en suivant unedémarche de transfert d’échelle, des échelles les plus fines aux plus larges. Il a été montré que le PRI(Photochemical Reflectance Index), utilisé en tant qu’indicateur du LUE (Light Use Efficiency), est parnature un signal composite qui reflète principalement la régulation du rendement de laphotosynthèse sur des échelles de temps fines, et la structure et composition biochimique ducouvert à l’échelle de la saison. L’analyse de courbes de réponse du PRI au PAR (PhotosyntheticallyActive Radiation) a permis de déconvoluer ces deux sources de variabilité, via l’introduction duconcept de PRI0 ou PRI d’une feuille idéalement adaptée à l’obscurité. Ce PRI0, capturant la variabilitédu PRI indépendante du LUE, a pu être mesuré à l’échelle de la feuille, et estimé à l’échelle de jeunescouverts végétaux et de la parcelle. Cette variabilité a pu être expliquée à l’échelle de la feuille et dejeunes couverts végétaux par les variations du contenu en pigment des feuilles. A l’échelle depeuplements adultes et de l’année, elle résulte cependant d’effets combinés de la compositionbiochimique et de la structure des couverts qui n’ont pu être séparés. Ces effets sont susceptiblesaux échelles larges de masquer en bonne partie, voire de biaiser la relation entre PRI et LUE. Il a enoutre été montré que la représentativité du PRI est limitée aux strates supérieures des canopées etdépend de la structure du couvert et du climat lumineux, ce qui peut limiter son intérêt en tantqu’estimateur du LUE à l’échelle de l’écosystème. Ces résultats soulignent la nécessité de prendre encompte la structure et la composition biochimique des couverts végétaux dans le cadre d’uneutilisation du PRI en tant que proxy du LUE de l’écosystème

Potential of proximal teledetection and modeling as a way to assess canopy structure and functioning

L anticipation des effets des changements climatiques nécessite une bonne compréhension dufonctionnement carboné des écosystèmes continentaux. L une des principales contraintes liées àl étude de ces écosystèmes est la forte variabilité à la fois spatiale et temporelle de leurs flux decarbone et de leurs réponses aux contraintes abiotiques. L usage de méthodes de télédétectionoptiques pourrait permettre de suivre de façon spatialisée le fonctionnement des couverts végétaux.Ce travail vise à évaluer le potentiel de méthodes de télédétection pour décrire la structure et lefonctionnement de couverts végétaux à des échelles spatiales et temporelles variées. Pour ce faire,les relations entre indices optiques et phénomènes biologiques ont été étudiées en suivant unedémarche de transfert d échelle, des échelles les plus fines aux plus larges. Il a été montré que le PRI(Photochemical Reflectance Index), utilisé en tant qu indicateur du LUE (Light Use Efficiency), est parnature un signal composite qui reflète principalement la régulation du rendement de laphotosynthèse sur des échelles de temps fines, et la structure et composition biochimique ducouvert à l échelle de la saison. L analyse de courbes de réponse du PRI au PAR (PhotosyntheticallyActive Radiation) a permis de déconvoluer ces deux sources de variabilité, via l introduction duconcept de PRI0 ou PRI d une feuille idéalement adaptée à l obscurité. Ce PRI0, capturant la variabilitédu PRI indépendante du LUE, a pu être mesuré à l échelle de la feuille, et estimé à l échelle de jeunescouverts végétaux et de la parcelle. Cette variabilité a pu être expliquée à l échelle de la feuille et dejeunes couverts végétaux par les variations du contenu en pigment des feuilles. A l échelle depeuplements adultes et de l année, elle résulte cependant d effets combinés de la compositionbiochimique et de la structure des couverts qui n ont pu être séparés. Ces effets sont susceptiblesaux échelles larges de masquer en bonne partie, voire de biaiser la relation entre PRI et LUE. Il a enoutre été montré que la représentativité du PRI est limitée aux strates supérieures des canopées etdépend de la structure du couvert et du climat lumineux, ce qui peut limiter son intérêt en tantqu estimateur du LUE à l échelle de l écosystème. Ces résultats soulignent la nécessité de prendre encompte la structure et la composition biochimique des couverts végétaux dans le cadre d uneutilisation du PRI en tant que proxy du LUE de l écosystème.In order to assess the effect of global warming, a good understanding of carbon functioning ofterrestrial ecosystems is needed. The study of terrestrial ecosystem carbon fluxes and responses toabiotic stress remain challenging due to their high spatial and temporal variability. The use of remotesensing may help us to describe those sources of variability. The aim of this work is to assess thepotential of remote sensing as a way to describe canopy structure and functioning over a broadrange of temporal and spatial scales. The relationships between optical indices and biologicalphenomenon were investigated over a range of increasing scales. The PRI (PhotochemicalReflectance Index), used as a proxy of the LUE (Light Use Efficiency) was shown to be a compositesignal, mainly impacted by the regulation of the LUE at short time scales, and by canopy structureand pigment content at seasonal scale. The analysis of PRI response to PAR (PhotosyntheticallyActive Radiation) allowed us to deconvolve those two sources of variability thanks to theintroduction of the PRI0 defined as the PRI of ideally dark adapted leaves. The PRI0 was shown toefficiently describe the LUE unrelated PRI variability, and could be measured at leaf scale, andestimated at the leaf, canopy and stand scales. This variability could be explained by changes in leafpigment content over the growing season at leaf and canopy scales. At the stand scale and over theyear, this LUE independent PRI variability resulted from combined effects of canopy structure andpigment content, which could not be separated. These effects may result in biased or masked PRIversus LUE relationships at larges scales. Moreover, it was shown that the in-situ PRI measurementsmainly responded to the LUE of sunlit leaves, depending on canopy structure and sky conditions. Thismay considerably hamper the use of the PRI as a proxy of the whole ecosystem LUE. These resultsillustrate the need to take canopy structure and pigment content into account while using the PRI asa proxy of the ecosystem LUE.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

Explaining the variability of the photochemical reflectance index (PRI) at the canopy-scale: Disentangling the effects of phenological and physiological changes

International audienc

Monitoring Spatial and Temporal Variabilities of Gross Primary Production Using MAIAC MODIS Data

Remotely sensed vegetation indices (RSVIs) can be used to efficiently estimate terrestrial primary productivity across space and time. Terrestrial productivity, however, has many facets (e.g., spatial and temporal variability, including seasonality, interannual variability, and trends), and different vegetation indices may not be equally good at predicting them. Their accuracy in monitoring productivity has been mostly tested in single-ecosystem studies, but their performance in different ecosystems distributed over large areas still needs to be fully explored. To fill this gap, we identified the facets of terrestrial gross primary production (GPP) that could be monitored using RSVIs. We compared the temporal and spatial patterns of four vegetation indices (NDVI, EVI, NIRV, and CCI), derived from the MODIS MAIAC data set and of GPP derived from data from 58 eddy-flux towers in eight ecosystems with different plant functional types (evergreen needle-leaved forest, evergreen broad-leaved forest, deciduous broad-leaved forest, mixed forest, open shrubland, grassland, cropland, and wetland) distributed throughout Europe, covering Mediterranean, temperate, and boreal regions. The RSVIs monitored temporal variability well in most of the ecosystem types, with grasslands and evergreen broad-leaved forests most strongly and weakly correlated with weekly and monthly RSVI data, respectively. The performance of the RSVIs monitoring temporal variability decreased sharply, however, when the seasonal component of the time serieswas removed, suggesting that the seasonal cycles of both the GPP and RSVI time series were the dominant drivers of their relationships. Removing winter values from the analyses did not affect the results. NDVI and CCI identified the spatial variability of average annual GPP, and all RSVIs identified GPP seasonality well. The RSVI estimates, however, could not estimate the interannual variability of GPP across sites or monitor the trends of GPP. Overall, our results indicate that RSVIs are suitable to track different facets of GPP variability at the local scale, therefore they are reliable sources of GPP monitoring at larger geographical scales

Data-based investigation of the effects of canopy structure and shadows on chlorophyll fluorescence in a deciduous oak forest

International audienceAbstract. Data from satellite, aircraft, drone, and ground-based measurements have already shown that canopy-scale sun-induced chlorophyll fluorescence (SIF) is tightly related to photosynthesis, which is linked to vegetation carbon assimilation. However, our ability to effectively use those findings are hindered by confounding factors, including canopy structure, fluctuations in solar radiation, and sun–canopy geometry that highly affect the SIF signal. Thus, disentangling these factors has become paramount in order to use SIF for monitoring vegetation functioning at the canopy scale and beyond. Active chlorophyll fluorescence measurements (FyieldLIF), which directly measures the apparent fluorescence yield, have been widely used to detect physiological variation of the vegetation at the leaf scale. Recently, the measurement of FyieldLIF has become feasible at the canopy scale, opening up new opportunities to decouple structural, biophysical, and physiological components of SIF at the canopy scale. In this study, based on top-of-canopy measurements above a mature deciduous forest, reflectance (R), SIF, SIF normalized by incoming photosynthetically active radiation (SIFy), FyieldLIF, and the ratio between SIFy and FyieldLIF (named Φk) were used to investigate the effects of canopy structure and shadows on the diurnal and seasonal dynamics of SIF. Further, random forest (RF) models were also used to not only predict FyieldLIF and Φk, but also provide an interpretation framework by considering additional variables, including the R in the blue, red, green, red-edge, and near-infrared bands; SIF; SIFy; and solar zenith angle (SZA) and solar azimuth angle (SAA). Results revealed that the SIF signal is highly affected by the canopy structure and sun–canopy geometry effects compared to FyieldLIF. This was evidenced by the weak correlations obtained between SIFy and FyieldLIF at the diurnal timescale. Furthermore, the daily mean SIF‾y captured the seasonal dynamics of daily mean F‾yieldLIF and explained 58 % of its variability. The findings also revealed that reflectance in the near-infrared (R-NIR) and the NIRv (the product of R-NIR and normalized difference vegetation index (NDVI)) are good proxies of Φk at the diurnal timescale, while their correlations with Φk decrease at the seasonal timescale. With FyieldLIF and Φk as outputs and the abovementioned variables as predictors, this study also showed that the RF models can explain between 86 % and 90 % of FyieldLIF, as well as 60 % and 70 % of Φk variations under clear-sky conditions. In addition, the predictor importance estimates for FyieldLIF RF models revealed that R at 410, 665, 740, and 830 nm; SIF; SIFy; SZA; and SAA emerged as the most useful and influential factors for predicting FyieldLIF, while R at 410, 665, 705, and 740 nm; SZA; and SAA are crucial for predicting Φk. This study highlighted the complexity of interpreting diurnal and seasonal dynamics of SIF in forest canopies. These dynamics are highly dependent on the complex interactions between the structure of the canopy, the vegetation biochemical properties, the illumination angles (SZA and SAA), and the light conditions (ratio of diffuse to direct solar radiation). However, such measurements are necessary to better separate the variability in SIF attributable to radiation and measurement conditions from the subtler variability attributable to plant physiological processes

Potential of C-band Synthetic Aperture Radar Sentinel-1 time-series for the monitoring of phenological cycles in a deciduous forest

International audienceAnnual time-series of the two satellites C-band SAR (Synthetic Aperture Radar) Sentinel-1A and 1B data over five years were used to characterize the phenological cycle of a temperate deciduous forest. Six phenological metrics of the start (SOS), middle (MOS) and end (EOS) of budburst and leaf expansion stage in spring, and the start (SOF), middle (MOF) and end (EOF) of leaf senescence in autumn were extracted using an asymmetric double sigmoid function (ADS) fitted to the time-series of the ratio (VV/VH) of backscattering at co-polarization VV (vertical-vertical) and at cross polarization VH (vertical-horizontal). Phenological metrics were also derived from other four vegetation proxies (Normalized Difference Vegetation Index NDVI time-series from Sentinel-2A and 2B images, and in situ measurements of NDVI measurements, Leaf Area Index LAI and litterfall temporal dynamics). These estimated phenological metrics were compared to phenological observations obtained by visual observations from the ground, achieved using binoculars by three inter-calibrated observers, on a biweekly basis during the budburst and weekly during the senescence. We observe a decrease in the backscattering coefficient (σ 0) at VH cross polarization during the leaf development and the expansion phase in spring and an increase during the senescence phase, contrary to what is usually observed on various types of crops. In vertical polarization, σ 0 VV shows very little variation throughout the year. S-1 time-series of VV/VH ratio provide a good description of the seasonal vegetation cycle allowing the estimation of spring and autumn phenological metrics. Estimates provided by VV/VH of budburst dates using MOS criterion differ by approximately 8 days on average (mean average deviation) from phenological observations. During senescence phase, estimates using MOF criterion are later and deviate by about 20 days from phenological observations of leaf senescence while the differences are of the order of 2 to 4 days between the phenological observations and estimates based on in situ NDVI and LAI time-series, respectively. A deviation of about 7 days, comparable to that observed during budburst, is obtained between the estimates of senescence (MOF) from S-1 and those determined from the in situ monitoring of litterfall. While in spring, leaf emergence and expansion described by LAI or NDVI explain the increase of VV/VH (or the decrease of σ 0 VH), during senescence, S-1 VV/VH is decorrelated from LAI or NDVI and is better explained by litterfall temporal dynamics. This behavior resulted in a hysteresis phenomenon observed on the relationships between VV/VH and NDVI or LAI. For the same LAI or NDVI, the response of VV/ VH is different depending on the phenological phase considered. This study shows the high potential offered by Sentinel-1 SAR C-band time-series for the detection of forest phenology, thus overcoming the limitations caused by cloud cover in optical remote sensing of vegetation phenology