Europe-wide maps of biomass density based on satellite remote sensing data for 2017, 2020, 2021 and 2023

  • Maurizio Santoro*
  • , Oliver Cartus
  • , Arnan Araza
  • , Martin Herold
  • , Jukka Miettinen
  • , Ake Rosenqvist
  • , Kazufumi Kobayashi
  • , Takeo Tadono
  • , Frank Martin Seifert
  • *Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Spatially explicit information on forest structure and biomass is needed to meet the monitoring and reporting requirements of several European policies. Satellite images enable mapping and monitoring of the Europe’s forest resources through operational observations from the Sentinel-1 Synthetic Aperture Radar (SAR) and the Advanced Land Observing Satellite 2 (ALOS-2) Phased Array l -band SAR 2 (PALSAR-2) instruments. Data acquired in 2017, 2020, 2021 and 2023 were used to generate annual maps of forest biomass variables, namely Growing Stock Volume (GSV), Aboveground Biomass (AGB) and Belowground Biomass (BGB), with a pixel size of 20 m × 20 m. All products are in the geometry of the Sentinel-2 tiling system. A spatially averaged map with a pixel size of 100 m × 100 m (1 hectare) in geographic projection is also supplied, for users who do not require the highest spatial resolution. The maps were generated with a fully documented processing chain that includes (i) pre-processing of the SAR data to create stacks of co-registered terrain geocoded images of the backscattered intensity and (ii) inversion of a physically-based model to estimate GSV. AGB and BGB were subsequently estimated using allometric relationships. Per-pixel standard deviations were computed for each biomass variable by propagating uncertainties from both the SAR observations and the model parameters. The maps clearly reproduce the expected spatial patterns of forest biomass across Europe and provide sufficient spatial detail to identify biomass dynamics related to, e.g., logging and regrowth. Validation against measurements collected by National Forest Inventories (NFIs) indicates poor agreement with map values at the pixel scale, with errors larger than 50% of the reference biomass. The correspondence substantially improved for spatial aggregates, such as administrative units, for which the bias was mostly negligible and the mean square error was below 30% of the reference value. The number of ALOS-2 PALSAR-2 images affected the inter-annual consistency of the maps, which was lower in regions with only one or two observations per year.

Original languageEnglish
Article number112536
JournalData in Brief
Volume65
DOIs
Publication statusPublished - Apr 2026
MoE publication typeA1 Journal article-refereed

Funding

The work was carried out under the EOEP5 programme and funded by the European Space Agency (ESA), contract 4000135015/21/I-NB—Forest Carbon Monitoring. The satellite data processing was supported by the ESA Network of Resources Initiative. The authors want to thank Tornator Oyj for providing the field plot data for the Romanian study site. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Keywords

  • AGB
  • ALOS-2 PALSAR-2
  • BGB
  • Forest
  • GSV
  • LiDAR
  • Sentinel-1

Fingerprint

Dive into the research topics of 'Europe-wide maps of biomass density based on satellite remote sensing data for 2017, 2020, 2021 and 2023'. Together they form a unique fingerprint.

Cite this