Period: 2010


Resolutions: 0.01 degree

Extent: Northern Hemisphere

Data can be accessed here.

Algorithm description: The Growing Stock Volume (GSV) is estimated using BIOMASAR algorithm that relies on the following Water Cloud type of model:

{ \sigma }_{ forest }^{ 0 }\quad =\quad { \sigma }_{ ground }^{ 0 }\quad { e }^{ -\beta V }\quad +\quad { \sigma }_{ canopy }^{ o }\quad (1-{ e }^{ -\beta V })

where \sigma represents the backscattering of forest, ground or canopy,   \beta a coefficient and V is GSV.

The above equation is inverted using measured backscatter to retrieve GSV. GSV is estimated for each timestep and then weighted to obtain a final GSV estimate.

Accuracy: The spatial distribution of the GSV across four ecological zones (polar, boreal, temperate, subtropical) was well captured by the ASAR-based estimates. The uncertainty of the retrieved GSV was smallest in boreal and temperate forest (<30% for approximately 80% of the forest area) and largest in subtropical forest.

For major forested countries within the Northern hemisphere, the relative RMSE was between 12% and 45% with an average of 29% (compared with National Forest Inventory).

In Europe, the RMSE was estimated to 46.1 m3/ha (i.e. relative RMSE= 26.2% on average). Strongest agreement was found in northern Europe, Baltic countries and Hungary. For central European countries, the relative RMSE was slightly higher (mostly between 20% and 35%) due to frequent average GSV above 200 m3/ha. Errors above 40% were obtained in Ireland (very small forest area proportion) and Switzerland (strong land fragmentation, mountainous terrain and NFI-derived GSV averages well above the 200 m3/ha level).


  • Larger uncertainty was found for fragmented forest landscapes on sloped terrain or when GSV is very low (< 20 m3/ha)
  • Systematic underestimation occurred in regions of very high GSV (>300 m3/ha)


Santoro, M. et al. Retrieval of growing stock volume in boreal forest using hyper-temporal series of Envisat ASAR ScanSAR backscatter measurements. Remote Sens. Environ. 115, 490–507 (2011).

Santoro, M. et al. Estimates of Forest Growing Stock Volume for Sweden, Central Siberia, and Québec Using Envisat Advanced Synthetic Aperture Radar Backscatter Data. Remote Sens. 5,4503–4532 (2013).

Santoro, M. et al. Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR. Remote Sens. Environ. 168, 316–334 (2015).