The availability of spatially explicit biomass estimates at a spatial resolution ≤ 1 km opens up the possibility for several applications and value-added products not obtainable from summary statistics. There are four published maps providing forest biomass density for Europe: the datasets of Thurner et al. (2014), Barredo et al. (2012), Gallaun et al. (2010) and Kindermann et al. (2008). These maps provide ready-made wall-to-wall biomass estimates over forested areas, but literature suggests assessing the maps with care as the remote sensing signals are only indirectly related to the biomass density.
To improve estimations, we use a new reference dataset produced by the National Forest Inventory organizations of 26 European countries under the European National Forest Inventory Network (ENFIN) and developed in the context of a framework contract launched by the JRC. The novelty of this dataset consists on providing estimates based on a harmonized biomass definition and a common estimator. The harmonization of the national statistics result essentially in proper integration of data from different countries. In fact, the harmonized statistics, based on almost half a million ground measurements, present significant differences compared to the national estimates for 14 countries.
The assessment of the four biomass maps is performed at regional, national and sub-national scales using harmonized statistics, and at pixel level using a subset of field plots covering most European forest types. The plots are temporally aligned with the maps using growth rates and further screened using an innovative approach to remove the plots not representative of the map cells (Avitabile and Camia, 2018).
The maps relative errors (relative RMSE) ranged from 29% to 40% at national level and increase at pixel level. Interestingly, even though the biomass maps were produced with different data and approaches, all maps tend to overestimate at low biomass (0 – 100 Mg ha-1) and underestimate at higher biomass density, resulting in an overall negative bias relative to the harmonized values (Avitabile and Camia, 2018).
Such trends may be due to several reasons, such as: (1) the use of average national values for map calibration, which do not represent the local biomass variability; (2) the limited sensitivity of existing satellite sensors to variations in canopy height and tree diameter; (3) mixed pixels where a similar signal may correspond to vegetation types with different biomass density; (4) calibration data (plots) with a size much smaller than the map cells.
This assessment and integration analysis will also include upcoming biomass maps (e.g., from the ESA GlobBiomass project and from Global Forest Watch) and include the temporal harmonization of the reference statistics using the Carbon Budget Model (CBM-CFS3, developed by the Canadian Forest Service and adapted to the specific European conditions) to improve biomass mapping for Europe, towards a biomass product in line with the harmonized national statistics and with higher accuracy at local scale.
References
Avitabile, V., & Camia, A. (2018). An assessment of forest biomass maps in Europe using harmonized national statistics and inventory plots. Forest ecology and management, 409, 489-498.
Barredo, J. I., San-Miguel-Ayanz, J., Caudullo, G., & Busetto, L. (2012). A European map of living forest biomass and carbon stock. Reference Report by the Joint Research Centre of the European Commission. EUR-Scientific and Technical Research, 25730.
Gallaun, H., Zanchi, G., Nabuurs, G. J., Hengeveld, G., Schardt, M., & Verkerk, P. J. (2010). EU-wide maps of growing stock and above-ground biomass in forests based on remote sensing and field measurements. Forest Ecology and Management, 260(3), 252-261.
Kindermann, G., McCallum, I., Fritz, S., & Obersteiner, M. (2008). A global forest growing stock, biomass and carbon map based on FAO statistics. Silva Fennica, 42(3), 387-396.
Thurner, M., Beer, C., Santoro, M., Carvalhais, N., Wutzler, T., Schepaschenko, D., ... & Schmullius, C. (2014). Carbon stock and density of northern boreal and temperate forests. Global Ecology and Biogeography, 23(3), 297-310.