# Estimation of Gross Primary Productivity (GPP)
## 1 Introduction
The Normalized Difference Vegetation Index (NDVI) [36] and the Enhanced Vegetation Index (EVI) [37] (referring to Table 1) are the most commonly used VIs for monitoring canopy greenness, development and phenology [38]. Due to its long time-series, NDVI has been widely used as a proxy for GPP [39; 40] and the analysis of ecosystem phenology [28; 41; 42; 43; 44]. Research, however, has shown that both NDVI and EVI can fail to predict canopy phenology and productivity when LAI is high and in specific periods of the year, especially when canopy greenness and physiology are decoupled, e.g., during drought [45; 46] and senescence [47; 48]. Chlorophyll-sensitive VIs appear to be better suited for monitoring the phenology of plants and crops [49], because they are indirect proxies of canopy biochemistry. For example, green NDVI (gNDVI) considers the green band, which is more closely related to chlorophyll (see Table 1) than the red band [50], which is used in NDVI. gNDVI is better correlated with LAI than are NDVI and EVI and improves the modeling of LAI [51]. The Chlorophyll Index (ChlMedEdge) and the MERIS Terrestrial Chlorophyll Index (MTCI) also correlate with chlorophyll content [52; 53; 54] and should, in theory, be good proxies for phenology and GPP seasonality of crops. Pigment Specific Simple Ratio (PSSR) was reported to have a strong relationship with chlorophyll content [29; 55]. Modified Chlorophyll Absorption Ratio (MCARI) is an alternative index that provides a measure of chlorophyll concentration [56; 57] but is also sensitive to nonphotosynthetic components of the canopy, especially at low chlorophyll concentrations [58]. The Structure Insensitive Pigment Index (SIPI) is associated with the ratio of carotenoids to chlorophylls and allows mitigating the effects of foliar structural properties on reflectance, because it considers the NIR band [59; 60; 61]. Thus, a wide suite of RS-based indices can provide information on SRC phenology and possibly productivity. However, to date, the phenology and GPP seasonality of SRC plantations have not yet been widely studied via VIs, probably due to the poor spatial (1 km or larger) and spectral resolution (red and NIR mainly) of satellite sensors (e.g., MODIS/Terra or MODIS/Aqua; SPOT/VGT, NOAA/AVHRR; Landsat) [22]. A wide range of time-series smoothing methods and extracting phenological metrics (SOS, EOS) to reconstruct the seasonal patterns of noisy VI time-series have been proposed [27; 62; 63]. However, there is no single method that always performs better than another for smoothing VI time-series [64]. Large discrepancies in the detection of SOS and EOS have been found by comparing different retrieval methods [65; 66; 67] and no conclusive evidence favors one method over another. Therefore, combining multiple methods should provide better estimates of phenological metrics. The recent advent of high-resolution Sentinel-2 satellite imagery, with a spatial resolution of 10, 20 and 60 m offers a new perspective in monitoring ecosystem phenology. This satellite has two main advantages over other high-resolution satellites such as Landsat. The five-day temporal resolution is an advantage for monitoring plants, and the 10 m spatial resolution is more suitable for ecological, agricultural and phenological studies [71; 72]. Another interesting feature of Sentinel-2 is the availability of additional red-edge bands, which are available from other few space-borne sensors [73]. These red-edge regions play an important role in estimating the biochemical and biophysical traits of plants [74]. In this study we explored for the first time the use of eight canopy structure- and chlorophyll-sensitive VIs, derived from Sentinel-2, for describing the phenology and seasonal variability of GPP, derived from EC, of an SRC poplar plantation in Belgium.