Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements

Sanders, Abram F. J.; Verstraeten, Willem; Kooreman, Maurits L.; Leth, Thomas C. van; Beringer, Jason; Joiner, Joanna

doi:10.3390/rs8110895

Cited by 54 publications

(68 citation statements)

References 84 publications

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“…This finding is supported by the 2016 GPP anomaly at the VCP site, for which both SIF GOME2 and SIF OCO2 time series were found to capture early season photosynthetic activity, whereas EVI and PRI did not ( Figure S6). Our results are consistent with previous studies that have demonstrated similar potential for SIF as an improved GPP proxy (Manish Verma et al, 2017;Perez-Priego et al, 2015;Sanders et al, 2016;Wood et al, 2016;Yang et al, 2017;Zarco-Tejada et al, 2016;Zhang et al, 2014), although few to our knowledge have evaluated dryland, water-limited ecosystems such as these.…”

Section: Seasonal Gpp Dynamicssupporting

confidence: 93%

Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America

Smith

Biederman

Scott

et al. 2018

Geophysical Research Letters

128

100

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Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet understanding of the relationship between GPP and remote sensing observations and how it changes with factors such as scale, biophysical constraint, and vegetation type remains limited. This knowledge gap is especially apparent for dryland ecosystems, which have characteristic high spatiotemporal variability and are under‐represented by long‐term field measurements. Here we utilize an eddy covariance (EC) data synthesis for southwestern North America in an assessment of how accurately satellite‐derived vegetation proxies capture seasonal to interannual GPP dynamics across dryland gradients. We evaluate the enhanced vegetation index, solar‐induced fluorescence (SIF), and the photochemical reflectivity index. We find evidence that SIF is more accurately capturing seasonal GPP dynamics particularly for evergreen‐dominated EC sites and more accurately estimating the full magnitude of interannual GPP dynamics for all dryland EC sites. These results suggest that incorporation of SIF could significantly improve satellite‐based GPP estimates.

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Section: Seasonal Gpp Dynamicssupporting

confidence: 93%

Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America

Smith

Biederman

Scott

et al. 2018

Geophysical Research Letters

128

100

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“…[42,43]. Previous studies have discussed the effect of the fit window, the numbers of PCs, and the reference area for PC determination on the retrieval outcome [42,43,55]. Köhler et al depicted the standard error of the mean of GOME-2 SIF composites for January 2011, and the results showed that the standard error of the mean was generally low (<0.15 mW/m 2 /sr/nm) for GOME-2 SIF in Australia [42].…”

Section: Discussionmentioning

confidence: 99%

Monitoring Drought Effects on Vegetation Productivity Using Satellite Solar-Induced Chlorophyll Fluorescence

et al. 2019

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Around the world, the increasing drought, which is exacerbated by climate change, has significant impacts on vegetation carbon assimilation. Identifying how short-term climate anomalies influence vegetation productivity in a timely and accurate manner at the satellite scale is crucial to monitoring drought. Satellite solar-induced chlorophyll fluorescence (SIF) has recently been reported as a direct proxy of actual vegetation photosynthesis and has more advantages than traditional vegetation indices (e.g., the Normalized Difference Vegetation Index, NDVI and the Enhanced Vegetation Index, EVI) in monitoring vegetation vitality. This study aims to evaluate the feasibility of SIF in interpreting drought effects on vegetation productivity in Victoria, Australia, where heat stress and drought are often reported. Drought-induced variations in SIF and absorbed photosynthetically active radiation (APAR) estimations based on NDVI and EVI were investigated and validated against results indicated by gross primary production (GPP). We first compared drought responses of GPP and vegetation proxies (SIF and APAR) during the 2009 drought event, considering potential biome-dependency. Results showed that SIF exhibited more consistent declines with GPP losses induced by drought than did APAR estimations during the 2009 drought period in space and time, where APAR had obvious lagged responses compared with SIF, especially in evergreen broadleaf forest land. We then estimated the sensitivities of the aforementioned variables to meteorology anomalies using the ARx model, where memory effects were considered, and compared the correlations of GPP anomaly with the anomalies of vegetation proxies during a relatively long period (2007)(2008)(2009)(2010)(2011)(2012)(2013). Compared with APAR, GPP and SIF are more sensitive to temperature anomalies for the general Victoria region. For crop land, GPP and vegetation proxies showed similar sensitivities to temperature and water availability. For evergreen broadleaf forest land, SIF anomaly was explained better by meteorology anomalies than APAR anomalies. GPP anomaly showed a stronger linear relationship with SIF anomaly than with APAR anomalies, especially for evergreen broadleaf forest land. We showed that SIF might be a promising tool for effectively evaluating short-term drought impacts on vegetation productivity, especially in drought-vulnerable areas, such as Victoria.

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“…Recent advances in satellite sensors and retrieval techniques have enabled remote sensing of solar-induced chlorophyll fluorescence (SIF), the natural emission of photons from the light-harvesting structures of sunlit plants, which is a biophysical consequence of light absorption. Previous work has shown that space-based SIF observations correlate significantly with GPP derived from ground-based eddy covariance, reliably predicting the monthly or average seasonal pattern of GPP for a range of biomes (Frankenberg et al, 2011;Guanter et al, 2014;Joiner et al, 2014;Sanders et al, 2015). SIF appears promising as a more physiologically meaningful proxy to photosynthesis (e.g., Yang et al, 2015) than do traditional remote sensing-based vegetation indices, such as the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI; Myneni & Williams, 1994;Rahman et al, 2005;Shi et al, 2017;Sims et al, 2006;Xiao et al, 2004).…”

Section: Citationmentioning

confidence: 99%

“…Recent studies suggest that SIF provides information on LUE in coniferous forests (Walther et al, ; Yao Zhang et al, ), underscoring its possible advantage over traditional remote sensing indices (i.e., NDVI and EVI), which do not provide information about LUE. The slope of the GPP‐SIF relationship has shown to be biome‐specific (Damm et al, ; Guanter et al, , ; Parazoo et al, ; Sanders et al, ), but recent work with OCO‐2 SIF data suggests there may be a universal relationship (Sun et al, ). However, due to physiological and phenological differences between plant species and functional types, as well as structural complexities of vegetation canopies across the landscape, a universal relationship may prove elusive (see reviews by Gamon () and Porcar‐Castell et al ()).…”

Section: Introductionmentioning

confidence: 99%

Solar‐Induced Fluorescence Detects Interannual Variation in Gross Primary Production of Coniferous Forests in the Western United States

Zuromski

Bowling

Köhler

et al. 2018

Geophysical Research Letters

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Quantifying gross primary production (GPP), the largest flux of the terrestrial carbon cycle, remains difficult at the landscape scale. Evergreen needleleaf (coniferous) forests in the western United States constitute an important carbon reservoir whose annual GPP varies from year‐to‐year due to drought, mortality, and other ecosystem disturbances. Evergreen forest productivity is challenging to determine via traditional remote sensing indices (i.e., NDVI and EVI), because detecting environmental stress conditions is difficult. We investigated the utility of solar‐induced chlorophyll fluorescence (SIF) to detect year‐to‐year variation in GPP in four coniferous forests varying in species composition in the western United States (Sierra Nevada, Cascade, and Rocky Mountains). We show that annually averaged, satellite‐based observations of SIF (retrieved from GOME‐2) were significantly correlated with annual GPP observed at eddy covariance towers over several years. Further, SIF responded quantitatively to drought‐induced mortality, suggesting that SIF may be capable of detecting ecosystem disturbance in coniferous forests.

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Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements

Abstract: A global, monthly averaged time series of Sun-induced Fluorescence (SiF), spanning

Cited by 54 publications

References 84 publications

Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America

Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America

Monitoring Drought Effects on Vegetation Productivity Using Satellite Solar-Induced Chlorophyll Fluorescence

Solar‐Induced Fluorescence Detects Interannual Variation in Gross Primary Production of Coniferous Forests in the Western United States

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