Authors: Maurizio Santoro and Jukka Miettinen
As you may remember, the European wide biomass mapping in the FCM project is conducted with the BIOMASAR approach developed by Gamma Remote Sensing. The same approach is used for the global biomass mapping conducted in the ESA CCI Biomass project. In the FCM project, the method is finetuned for European conditions and high resolution (20 m) mapping. The approach is based on growing stock volume (GSV) estimation, which is subsequently converted to above and below ground biomass. The mapping uses only spaceborne radar sensors.
The method is described in an article recently published in the Remote Sensing journal titled “Estimation of Forest Growing Stock Volume with Synthetic Aperture Radar: A Comparison of Model-Fitting Methods“, which explores the application of synthetic aperture radar (SAR) data in estimating GSV. Forest GSV estimation is crucial for sustainable forest management and ecological research. SAR data is well suited for estimation of GSV due to its ability to penetrate forest canopies and operate in various weather conditions. The study compares different model-fitting methods to determine which provides the most accurate estimates using SAR data, especially in densely vegetated areas.
Using four testing datasets from the main phase of the FCM project, two model fitting techniques were evaluated. The results show that calibration with auxiliary data performs similarly to a training based on reference measurements. This outcome is significant, as it implies that satellite-based maps of forest resources can be obtained when lacking a dataset of reference measurements, e.g. at continental level. Improved GSV estimation not only aids in tracking forest resources but also supports carbon accounting and conservation efforts.
In the extension of the FCM project, the BIOMASAR method will be used to create two more European wide maps. Together with the earlier maps, they will result in a time series of four maps (2017-2020-2021-2023). All four maps will be re-run to implement latest algorithm improvements and to make the four maps fully comparable. The work on the maps is progressing well, with the pre-processing phase finished. The production of the new maps is estimated to start early next year.
Full citation of the article: Santoro, M., Cartus, O., Antropov, O. and Miettinen, J. (2024) Estimation of Forest Growing Stock Volume with Synthetic Aperture Radar: A Comparison of Model-Fitting Methods. Remote Sensing 16: 4079. https://doi.org/10.3390/rs16214079