Novel Long-Term Global Indicators of Plant Productivity from Microwave Satellites

Satellite observations from microwave sensors contain information about the vegetation covering the Earth and thus bare large potential to monitor its dynamics at the global scale. Yet, individual satellite missions are too short to allow for a consistent monitoring over long periods. In this study, we present a new series of long-term products of microwave vegetation optical depth (VOD), a model-based indicator that is closely related to the total water contained in the aboveground biomass. The products were created by fusing VOD products from various sensors operating in C-, X-, and Ku-band. The single-sensor level 2 products are combined by a statistical merging approach, which involves spatial and temporal matching and resampling, bias correction, and an optimal merging into homogenized global gridded products with a spatial sampling of 0.25°. Separate products were generated for C-, X-, and Ku- bands to preserve the unique response of each frequency to different vegetation characteristics. The resulting products cover the period 1987-2018, 1998-2018, and 2002-2018 for the Ku-, X, and C-band respectively. In this study, we provide an overview of the merging methodology, present the product characteristics of the novel products, and evaluate their spatial and temporal characteristics against independent leaf area index observations from optical remote sensing. Moreover, we show how VOD data can be used to provide estimates of gross primary production.