The high sensitivity of SMOS L-Band vegetation optical depth to biomass

Abstract

Abstract. The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infra-red vegetation indices. This study is devoted to the characterisation of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz).Three different SMOS L-band VOD (L-VOD) data sets (SMOS Level 2, Level 3 and SMOS-IC) were compared with data sets on tree height, visible/infra-red indexes (NDVI, EVI), cumulated precipitation, and above ground biomass (AGB) for the 5 African continent. For all relationships, SMOS-IC showed the lowest dispersion and highest correlation. Overall, we found a strong (R > 0.85) correlation with no clear sign of saturation between L-VOD and four AGB data sets. The relationship linking L-VOD to tree height (R = 0.87) and Baccini's AGB (R = 0.94) was strong and linear. The relationships between L-VOD and three other AGB data sets were linear per land cover class, but with a changing slope depending on the land cover type. For low vegetation classes, the annual mean of L-VOD spans a range from 0 to 0.7 and it is linearly correlation with the amount of 10 the average annual precipitations. SMOS L-VOD showed a higher sensitivity to AGB as compared to NDVI and K/X/C-VOD (VOD measured, respectively, at 19, 10.7, and 6.9 GHz). The results showed that although the spatial resolution of L-VOD is coarse (∼ 40 km), the high temporal frequency and sensitivity to AGB makes SMOS L-VOD a very promising index for large scale monitoring of the vegetation status, in particular biomass.

Satellite‐Observed Major Greening and Biomass Increase in South China Karst During Recent Decade

“…The higher frequency of the X‐VOD sensor makes it more sensitive to smaller vegetation components (such as leaves and twigs) than L‐VOD, and X‐VOD is mainly sensitive to the characteristics of the upper canopy layer when the vegetation is dense, similar to vegetation indices computed in the optical domain (Liu et al, ; Tian et al, , ). Consequently, although both the L‐VOD and X‐VOD indices can be used for biomass monitoring, L‐VOD can be efficiently used to sense the entire biomass volume even over dense vegetation canopies (Rodríguez‐Fernández et al, ; Vittucci et al, ; Zhang et al, ). The daily X‐VOD and L‐VOD observations are aggregated to annual medians, strongly reducing undesired effects of noise (e.g., radio frequency interferences; RFIs).…”

“…There exists a good demonstration that X‐VOD and L‐VOD signal scale with above‐ground biomass (Brandt et al, ; Liu et al, ; Rodríguez‐Fernández et al, ; Vittucci et al, ; Zhang et al, ). We thus report relative changes in VOD as proxies of the relative changes in above‐ground vegetation biomass at an annual time scale.…”

“…The retrieved VOD index is largely insensitive to atmospheric perturbations and closely related to the water content of the entire vegetation layer, including all vegetation elements such as stems, leaves, and additionally branches and trunks in the case of woody vegetation (Guglielmetti et al, ; Wigneron et al, ). Contrary to the VOD index retrieved at higher frequencies (>5 GHz, hereafter termed X‐VOD), the L‐band VOD (hereafter termed L‐VOD) is not limited to the upper canopy, shows no saturation over densely vegetated areas, and is almost linearly linked to biomass volumes (Brandt et al, ; Konings et al, ; Rodríguez‐Fernández et al, ; Vittucci et al, ). This makes L‐VOD a well suited proxy for monitoring temporal changes in biomass of forest biomes and marks a new era in vegetation monitoring from space (Wigneron et al, ).…”

A carbon sink-driven approach to estimate gross primary production from microwave satellite observations

“…In recent years, studies have proposed to use VOD to estimate aboveground living biomass (Liu et al, 2011(Liu et al, , 2015Momen et al, 2017;Rodríguez-Fernández et al, 2018;Tian et al, 2016). Biomass and/or temporal change in biomass, however, relate to Net Primary Production (NPP) (Clark et al, 2001a,b;Girardin et al, 2010;Gower et al, 2001;Lavigne and Ryan, 1997;Luyssaert et al, 2007) and to Autotrophic Respiration (R a ) (Lavigne and Ryan, 1997;Ryan, 1990), the sum of which constitutes GPP (e.g.…”

The Performance of Multiple Model-Simulated Soil Moisture Datasets Relative to ECV Satellite Data in China

“…Moreover, the surface soil moisture changes have considerable impacts on the evolution of vegetation. As a proxy for vegetation development, the long-term seasonal NDVI variations have been commonly used to indicate the structural changes in surface soil moisture (the NDVI dataset has higher temporal and spatial resolutions than the vegetation optical depth/VOD) [28,77,78]. The NDVI dataset was obtained from the long-term Global Inventory Monitoring and Modeling Studies (GIMMS) 3 g version (https://ecocast.arc.nasa.gov/data/pub/ gimms/).…”