VODCA v2: multi-sensor, multi-frequency vegetation optical depth data for long-term canopy dynamics and biomass monitoring

Abstract

Abstract. Vegetation optical depth (VOD) is a model-based indicator of the total water content stored in the vegetation canopy derived from microwave Earth observations. As such, it is related to vegetation density, abundance, and above-ground biomass (AGB). Moesinger et al. (2020) introduced the global microwave VOD Climate Archive (VODCA v1), which harmonises VOD retrievals from several individual sensors into three long-term, multi-sensor VOD products in the C, X, and Ku frequency bands, respectively. VODCA v1 was the first VOD dataset spanning over 30 years of observations, thus allowing the monitoring of long-term changes in vegetation. Several studies have used VODCA in applications such as phenology analysis; drought monitoring; gross primary productivity monitoring; and the modelling of land evapotranspiration, live fuel moisture, and ecosystem resilience. This paper presents VODCA v2, which incorporates several methodological improvements compared to the first version and adds two new VOD datasets to the VODCA product suite. The VODCA v2 products are computed with a novel weighted merging scheme based on first-order autocorrelation of the input datasets. The first new dataset merges observations from multiple sensors in the C-, X-, and Ku-band frequencies into a multi-frequency VODCA CXKu product indicative of upper canopy dynamics. VODCA CXKu provides daily observations in a 0.25° resolution for the period 1987–2021. The second addition is an L-band product (VODCA L), based on the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, which in theory is more sensitive to the entire canopy, including branches and trunks. VODCA L covers the period 2010–2021 and has a temporal resolution of 10 d and a spatial resolution of 0.25°. The sensitivity of VODCA CXKu to the upper vegetation layer and that of VODCA L to above-ground biomass (AGB) are analysed using independent vegetation datasets. VODCA CXKu exhibits lower random error levels and improved temporal sampling compared to VODCA v1 single-frequency products. It provides complementary spatio-temporal information to optical vegetation indicators containing additional information on the state of the canopy. As such, VODCA CXKu shows moderate positive agreement in short vegetation (Spearman's R: 0.57) and broadleaf forests (Spearman's R: 0.49) with the fraction of absorbed photosynthetically active radiation from MODIS. VODCA CXKu also shows moderate agreement with the slope of the backscatter incidence angle relation of MetOp ASCAT in grassland (Spearman's R: 0.48) and cropland (Spearman's R: 0.46). Additionally, VODCA CXKu shows temporal patterns similar to the Normalized Microwave Reflection Index (NMRI) from in situ L-band GNSS measurements of the Plate Boundary Observatory (PBO) and sap flow measurements from SAPFLUXNET. VODCA L shows strong spatial agreement (Spearman's R: 0.86) and plausible temporal patterns with respect to yearly AGB maps from the Xu et al. (2021) dataset. VODCA v2 enables monitoring of plant water dynamics, stress, and biomass change and can provide insights, even into areas that are scarcely covered by optical data (i.e. due to cloud cover). VODCA v2 is open-access and available at https://doi.org/10.48436/t74ty-tcx62 (Zotta et al., 2024).