Abstract
BackgroundVegetation indices (VIs) by remote sensing are widely used as simple proxies of the gross primary production (GPP) of vegetation, but their performances in capturing the inter-annual variation (IAV) in GPP remain uncertain.MethodsWe evaluated the performances of various VIs in tracking the IAV in GPP estimated by eddy covariance in a temperate deciduous forest of Northeast China. The VIs assessed included the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), and the near-infrared reflectance of vegetation (NIRv) obtained from tower-radiometers (broadband) and the Moderate Resolution Imaging Spectroradiometer (MODIS), respectively.ResultsWe found that 25%–35% amplitude of the broadband EVI tracked the start of growing season derived by GPP (R2: 0.56–0.60, bias < 4 d), while 45% (or 50%) amplitudes of broadband (or MODIS) NDVI represented the end of growing season estimated by GPP (R2: 0.58–0.67, bias < 3 d). However, all the VIs failed to characterize the summer peaks of GPP. The growing-season integrals but not averaged values of the broadband NDVI, MODIS NIRv and EVI were robust surrogates of the IAV in GPP (R2: 0.40–0.67).ConclusionThese findings illustrate that specific VIs are effective only to capture the GPP phenology but not the GPP peak, while the integral VIs have the potential to mirror the IAV in GPP.
Highlights
Gross primary production (GPP), i.e. total carbon (C) fixed by vegetation photosynthesis, is the largest component of the global C cycle (Beer et al 2010)
The integral NDVIB defined by the nine thresholds explained 44%–60% of the inter-annual variation (IAV) in gross primary production (GPP), and the relationships between integral NDVIB defined from 30% to 50% threshold and annual GPP were highly conservative (R2 = 0.58–0.60)
Tracking the variation in annual GPP by vegetation index Our results indicated that the integral NIRvM was a robust proxy of the IAV of GPP among the six tested Vegetation index (VI), which was inaccordance with previous studies (Baldocchi et al 2020; Wang et al 2021)
Summary
Gross primary production (GPP), i.e. total carbon (C) fixed by vegetation photosynthesis, is the largest component of the global C cycle (Beer et al 2010). The annual mean VIs only explained the variations in GPP for deciduous broadleaved forests by 9–50%, with a slightly better performance of NIRv than NDVI and EVI (Huang et al 2019). When using the VI during growing season, the integral NDVI was tightly correlated with GPP across vegetation types (R2 = 0.80) (Park et al 2016). It is essential to comprehensively evaluate the relationships between annual GPP and different types of integrated or averaged VIs with various definitions of growing-season. Vegetation indices (VIs) by remote sensing are widely used as simple proxies of the gross primary production (GPP) of vegetation, but their performances in capturing the inter-annual variation (IAV) in GPP remain uncertain
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