Access to estimates of above Ground Biomass (AGB) is of prime importance to monitor vegetation health and estimate the carbon stocks, amongst other applications. The Vegetation Optical Depth (VOD) derived from the multi-angular Brightness Temperatures (TB) measured by the Soil Moisture and Ocean Salinity (SMOS) mission can be processed in order to get a global AGB estimation.
he AGB time series cover the life span of SMOS, i.e. 2010- 2022 at the moment.
The estimated global and annual AGB maps and their uncertainties are available (yes for free, no strings attached!) as NetCDF files. Each file contains the AGB and associated standard deviation for all years since SMOS launch (i.e., 2010 to now, 13 years already!).
With this data set it is possible thus to monitor changes with time while most of the existing products are static.
As there are different AGB estimates in the literature we have made a set of maps for different references (currently ESA CCI 2018 [1,2] and Avitabile [3]. Details are given in the documentation provided here.
More to come soon to complement this collection.
Maps are freely distributed by CATDS – Centre Aval de Traitement des Données SMOS so that users can benefit from them in their studies on e.g. vegetation state monitoring, carbon stock estimation, land cover and land use or any other relevant topics.
product can be downloaded here
[1] M. Santoro and O. Cartus, “Esa biomass climate change initiative (biomass_cci): Global datasets of forest above-ground biomass for the years 2010, 2017 and 2018, v3,” NERC EDS Centre for Environmental Data Analysis, 2021. [Online]. Available: http://dx.doi.org/10.5285/5f331c418e9f4935b8eb1b836f8a91b8
[2] M. Santoro, R. Lucas, H. Kay, and S. Quegan, “Cci biomass product user guide v3,” CCI_BIOMASS_PUG_V3, p. 47p, 2021. [Online]. Available: https://climate.esa.int/media/documents/D4.3_CCI_PUG_V3.0_20210707.pdf
[3] V. Avitabile, M. Herold, G. Heuvelink, S. L. Lewis, O. L. Phillips, G. P. Asner, J. Armston, P. S. Ashton, L. Banin, N. Bayol, and N. J. Berry, “An integrated pan-tropical biomass map using multiple reference datasets,” Global Change Biology, vol. 22, pp. 1406–1420, 2016.