2020
DOI: 10.1016/j.srs.2020.100009
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Estimating maize GPP using near-infrared radiance of vegetation

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Cited by 24 publications
(20 citation statements)
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“…S8b) cannot be easily explained by invoking SIF retrieval noise and therefore other potential reasons for these differences should be investigated. Our results on the direct comparison of SIF and NIRVP for GPP estimation confirm and considerably extend previous findings from site-level studies 22,40,41 . Among other things, we confirmed that previous site-level results showing better GPP estimation performance of NIRVP compared to SIF in crops 22,40 also held in a Mediterranean grassland site which experiences drought (Fig.…”
Section: Discussionsupporting
confidence: 89%
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“…S8b) cannot be easily explained by invoking SIF retrieval noise and therefore other potential reasons for these differences should be investigated. Our results on the direct comparison of SIF and NIRVP for GPP estimation confirm and considerably extend previous findings from site-level studies 22,40,41 . Among other things, we confirmed that previous site-level results showing better GPP estimation performance of NIRVP compared to SIF in crops 22,40 also held in a Mediterranean grassland site which experiences drought (Fig.…”
Section: Discussionsupporting
confidence: 89%
“…NIRVP was estimated from FLUO at-sensor radiance data to ensure minimal differences compared to SIF retrievals in terms of sensor and processing aspects. The approach of using NIR radiance as proxy for the product of NIR reflectance times PAR was previously introduced as NIRVR 22 and was found to show good performance in terms of correlation to SIF and GPP at the site level 22,40,41 . Those results included observations in cloudy conditions where the largest differences between PAR and NIR radiance are expected, the discrepancies between the two variables should be even smaller in the clear sky conditions under which the airborne campaign was conducted.…”
Section: Data Sets and Processingmentioning
confidence: 99%
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“…PAR and , to eventually obtain (often referred to as SIF yield) is considered important to estimate the photosynthetic light use efficiency (LUE) ( Mohammed et al, 2019 , Wieneke et al, 2018 ). Although recent studies have reported moderate to high correlations in the seasonal dynamics of f esc and LUE ( Dechant et al, 2020 ; Liu et al, 2020 ) and that f esc partially captures the response of LUE to diffuse light and therefore both parameters have a temporal correlation ( Kim et al, 2021 ), normalizing with PAR or is a well-accepted approach to relate larger scale SIF measurements to the mechanistic regulation of photosynthesis, which is normally parameterized on the leaf level. The now accessible relationship between available light energy and the emission efficiency shows a diurnal dynamic dependent on other photon pathways, including NPQ and photosynthetic activity ( Pinto et al, 2016 ; Porcar-Castell et al, 2014 ; van der Tol et al, 2009 ).…”
Section: Discussionmentioning
confidence: 99%
“…Some studies reported a high correlation between LUE and SIF yield using daily instantaneous measurement data, but whether a stress factor influenced this relationship and the extent of such an influence were unknown, and much of the correlation was likely due to phenology and leaf aging (Campbell et al, 2019; Li et al, 2018; Verma et al, 2017). Furthermore, the power of using SIF to estimate GPP seems not the most outstanding in all cases as near‐infrared (NIR) radiance of vegetation (NIRv, rad), defined as the product of incident NIR radiance, NIR reflectance, and Normalized Difference Vegetation Index (NDVI), provided a better GPP estimate than SIF (Badgley et al, 2017; Liu et al, 2020; Wu et al, 2019). The aforementioned findings cast questions on the quantity and quality of unique information of SIF in quantifying GPP and plant physiological stress beyond canopy structural variability.…”
Section: Introductionmentioning
confidence: 99%