Tracking seasonal changes of leaf and canopy light use efficiency in a Phlomis fruticosa Mediterranean ecosystem using field measurements and multi-angular satellite hyperspectral imagery

Stagakis, Stavros; Markos, Nikos; Sykioti, Olga; Kyparissis, Aris

doi:10.1016/j.isprsjprs.2014.08.012

Cited by 33 publications

(19 citation statements)

References 78 publications

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“…MODIS and CHRIS/PROBA are common operational instruments for studying PRI at ecosystemic and regional scales [9,60,131,132]. Alterations in the angle at which satellites detect seasonal fluctuations of illumination, the shadow fraction detected by the sensor and atmospheric effects were identified as critical influences on PRI signals on a spatial scale [31,71,79,133], with the exception of some relatively uniform and dense canopy structures and a low variability of shadow fractions [71].…”

Section: Ecosystemic Levelmentioning

confidence: 99%

“…Alterations in the angle at which satellites detect seasonal fluctuations of illumination, the shadow fraction detected by the sensor and atmospheric effects were identified as critical influences on PRI signals on a spatial scale [31,71,79,133], with the exception of some relatively uniform and dense canopy structures and a low variability of shadow fractions [71]. PRI obtained from the backscatter direction [25,60,132] nonetheless minimized the effect of shadows, and near-nadir satellite observations [79] that reduced the effects of soil background and atmospheric scattering were also optimal and improved the accuracy of RUE detection. PRI performance was improved in forward-scattering directions after replacing the PRI formulation wavelength, which indicates a possible shift in the signal of xanthophyllic de-epoxidation with the direction of detection.…”

Section: Ecosystemic Levelmentioning

confidence: 99%

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Affecting Factors and Recent Improvements of the Photochemical Reflectance Index (PRI) for Remotely Sensing Foliar, Canopy and Ecosystemic Radiation-Use Efficiencies

et al. 2016

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Accurately assessing terrestrial gross primary productivity (GPP) is crucial for characterizing the climate-carbon cycle. Remotely sensing the photochemical reflectance index (PRI) across vegetation functional types and spatiotemporal scales has received increasing attention for monitoring photosynthetic performance and simulating GPP over the last two decades. The factors confounding PRI variation, especially on long timescales, however, require the improvement of PRI understanding to generalize its use for estimating carbon uptake. In this review, we summarize the most recent publications that have reported the factors affecting PRI variation across diurnal and seasonal scales at foliar, canopy and ecosystemic levels; synthesize the reported correlations between PRI and ecophysiological variables, particularly with radiation-use efficiency (RUE) and net carbon uptake; and analyze the improvements in PRI implementation. Long-term variation of PRI could be attributed to changes in the size of constitutive pigment pools instead of xanthophyll de-epoxidation, which controls the facultative short-term changes in PRI. Structural changes at canopy and ecosystemic levels can also affect PRI variation. Our review of the scientific literature on PRI suggests that PRI is a good proxy of photosynthetic efficiency at different spatial and temporal scales. Correcting PRI by decreasing the influence of physical or physiological factors on PRI greatly strengthens the relationships between PRI and RUE and GPP. Combining PRI with solar-induced fluorescence (SIF) and optical indices for green biomass offers additional prospects.

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Section: Ecosystemic Levelmentioning

confidence: 99%

Section: Ecosystemic Levelmentioning

confidence: 99%

Affecting Factors and Recent Improvements of the Photochemical Reflectance Index (PRI) for Remotely Sensing Foliar, Canopy and Ecosystemic Radiation-Use Efficiencies

et al. 2016

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“…Thus, a best direction with a proper sunlit/shaded foliage ratio, a structure-based parameter, needs to be considered when using the BRDF model to interpret canopy PRI. Furthermore, the contribution of the background to the reflectance of the forest canopy varyies with the changing view angle [31,74], and it is hard to eliminate the influence of the background signal using the semi-empirical kernel-driven model.…”

Section: Uncertainties In the Relationship Between Pri And Luementioning

confidence: 99%

“…However, Nakaji et al [30] exhibited limited sensitivity of the PRI to LUE, while a model with both PRI and VPD as predictors is able to significantly improve LUE estimation for a tropical evergreen rainforest, as there is no clearly defined dry/rainy season cycle. In Mediterranean forests, which often suffer heat and drought stress in summer, PRI is successfully used to detect water stress on LUE and assess LUE across different seasons [31,[88][89][90][91].…”

Section: Unresolved Questionsmentioning

confidence: 99%

“…A number of studies found that LUE is well related to the photochemical reflectance index (PRI = (R 531´R570 )/(R 531 + R 570 ), and R 531 and R 570 are reflectance at wavelengths 531 and 570 nm) [3,[24][25][26][27][28][29][30][31][32][33][34][35][36][37]. However, there are still some uncertainties regarding to the reliability of this relationship as affected by many factors.…”

Section: Introductionmentioning

confidence: 99%

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Ability of the Photochemical Reflectance Index to Track Light Use Efficiency for a Sub-Tropical Planted Coniferous Forest

Zhang

Chen

et al. 2015

Remote Sensing

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Light use efficiency (LUE) models are widely used to estimate gross primary productivity (GPP), a dominant component of the terrestrial carbon cycle. Their outputs are very sensitive to LUE. Proper determination of this parameter is a prerequisite for LUE models to simulate GPP at regional and global scales. This study was devoted to investigating the ability of the photochemical reflectance index (PRI) to track LUE variations for a sub-tropical planted coniferous forest in southern China using tower-based PRI and GPP measurements over the period from day 101 to 275 in 2013. Both half-hourly PRI and LUE exhibited detectable diurnal and seasonal variations, and decreased with increases of vapor pressure deficit (VPD), air temperature (Ta), and photosynthetically active radiation (PAR). Generally, PRI is able to capture diurnal and seasonal changes in LUE. However, correlations of PRI with LUE varied dramatically throughout the growing season. The correlation was the strongest (R 2 = 0.6427, p < 0.001) in July and the poorest in May. Over the entire growing season, PRI relates better to LUE under clear or partially cloudy skies (clearness index, CI > 0.3) with moderate to high VPD (>20 hPa) and high temperatures (>31˝C). Overall, we found that PRI is most sensitive to variations in LUE under stressed conditions, and the sensitivity decreases as the growing conditions become favorable when atmosphere water vapor, temperature and soil moisture are near the optimum conditions.

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Emerging opportunities and challenges in phenology: a review

et al. 2016

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Abstract. Plant phenology research has gained increasing attention because of the sensitivity of phenology to climate change and its consequences for ecosystem function. Recent technological development has made it possible to gather invaluable data at a variety of spatial and ecological scales. Despite our ability to observe phenological change at multiple scales, the mechanistic basis of phenology is still not well understood. Integration of multiple disciplines, including ecology, evolutionary biology, climate science, and remote sensing, with long-term monitoring data across multiple spatial scales is needed to advance understanding of phenology. We review the mechanisms and major drivers of plant phenology, including temperature, photoperiod, and winter chilling, as well as other factors such as competition, resource limitation, and genetics. Shifts in plant phenology have significant consequences on ecosystem productivity, carbon cycling, competition, food webs, and other ecosystem functions and services. We summarize recent advances in observation techniques across multiple spatial scales, including digital repeat photography, other complementary optical measurements, and solar-induced fluorescence, to assess our capability to address the importance of these scale-dependent drivers. Then, we review phenology models as an important component of earth system modeling. We find that the lack of species-level knowledge and observation data leads to difficulties in the development of vegetation phenology models at ecosystem or community scales. Finally, we recommend further research to advance understanding of the mechanisms governing phenology and the standardization of phenology observation methods across networks. With the opportunity for "big data" collection for plant phenology, we envision a breakthrough in processbased phenology modeling.

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Tracking seasonal changes of leaf and canopy light use efficiency in a Phlomis fruticosa Mediterranean ecosystem using field measurements and multi-angular satellite hyperspectral imagery

Cited by 33 publications

References 78 publications

Affecting Factors and Recent Improvements of the Photochemical Reflectance Index (PRI) for Remotely Sensing Foliar, Canopy and Ecosystemic Radiation-Use Efficiencies

Affecting Factors and Recent Improvements of the Photochemical Reflectance Index (PRI) for Remotely Sensing Foliar, Canopy and Ecosystemic Radiation-Use Efficiencies

Ability of the Photochemical Reflectance Index to Track Light Use Efficiency for a Sub-Tropical Planted Coniferous Forest

Emerging opportunities and challenges in phenology: a review

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