Comparing harmonic regression and GLAD Phenology metrics for estimation of forest community types and aboveground live biomass within forest inventory and analysis plots

•Harmonic regression coefficients derived from a Landsat time series using three harmonics generally outperform Global Land Analysis & Discovery (GLAD) Phenology metrics.•Difference between metric sets were more pronounced for differentiating forest community types in comparison to estimating total or species-specific aboveground live biomass (AGLBM)•Including digital terrain variables derived from digital terrain models (DTMs) improved the prediction of forest community types but had less of an impact for estimating AGLBM.•This research suggests that harmonic regression is an effective means to summarize seasonal and phenological patterns in a multispectral timeseries.