Linking remotely sensed growth-related canopy attributes to interannual tree-ring width variations: A species-specific study using Sentinel optical and SAR time series

Abstract

Tree ring width (TRW) is crucial for assessing biomass increments, carbon uptake, forest productivity, and forest health. Due to the limitations involved in measuring TRW, utilizing canopy attributes based on vegetation indices (VIs) offers a promising alternative. This study investigated the species-specific relationship between the VIs derived from the Sentinel optical (Sentinel-2) and SAR (Sentinel-1) time series and TRW. For each of the seven dominant Central European tree species, we aimed to identify the most suitable VI that shows the strongest relationship with the interannual variation in TRW. We also developed species-specific models using the random forest (RF) approach and a variety of VIs to predict TRW. Additionally, the impact of detrending TRW on its correlation with VIs and on the accuracy of TRW modeling was assessed. The results showed that the VIs that had the strongest correlation with TRW differed among the analyzed tree species. The results confirmed our hypothesis that the use of novel VIs, such as the green normalized difference vegetation index (GNDVI), or red-edge-based VIs can increase our ability to detect growth-related canopy attributes. Among all the models constructed based on raw and detrended TRWs, 12–39 % of the annual variance in TRW was explained by the integrated optical and SAR-based features. Comparing the raw and detrended TRWs indicated that detrending is necessary for certain species, even in short-term studies (i.e., less than 6 years). We concluded that Sentinel-based VIs can be used to improve the understanding of species-specific variation in forest growth over large areas. These results are useful for modeling and upscaling forest growth, as well as for assessing the effect of extreme climate events, such as droughts, on forest productivity.