Planting of trees on degraded land + Biomass estimation in Tropical Forest

The project begins with the identification of land parcels suitable for afforestation under the Carbon Removal and Carbon Farming Certification Framework (CRCF). To achieve this, IABG, Cesefor and Forliance collaborate across project areas located in the Spanish province of Soria and the Colombian department of Vichada.

For each eligible parcel, Above-Ground Biomass (AGB) is estimated using species-specific allometric equations combined with Random Forest modelling approaches. The models integrate multiple geospatial and Earth Observation (EO) data sources, including Sentinel-2 and Landsat imagery, GEDI LiDAR data, digital elevation and terrain models (DEM/DTM), and canopy height models.

The resulting outputs comprise a suite of EO-based products designed to address key CRCF requirements, including baseline establishment, uncertainty quantification, double-counting prevention, leakage assessment, and the evaluation of biodiversity co-benefits. By combining rigorous geospatial analysis with transparent, science-based carbon accounting methodologies, the project provides an end-to-end framework for transforming degraded land into verifiable carbon-removal assets.

Pilot sites

• Soria (Spain)

  5ha site with a 2019 Holme oak with truffle plantation in marginal lands.

  An area of limestone soil that, prior to planting, was covered with shrubby grass and included a small area that was formerly used for dry farming (barley, wheat, and sunflowers).

   

Biomass Estimation in Tropical Forest – Innovative Pilot Site

Accurate monitoring of forest biomass, and especially of vertical structure and tree‑height, is a prerequisite for assessing ecosystem function and for reliable carbon‑stock management. Existing tropical‑forest biomass‑estimation techniques suffer from large uncertainties because of canopy complexity and limited sensor penetration. To overcome these limitations the pilot will exploit data from the upcoming ESA Biomass satellite, whose advanced Polarimetric Interferometric SAR (PolInSAR) and Tomographic SAR (TomoSAR) capabilities enable precise retrieval of three‑dimensional forest structure across large areas.

The radar‑derived height and canopy‑profile information will be complemented by hyperspectral imagery, which provides detailed spectral signatures for robust tree‑species classification. By distinguishing species with different wood density and growth patterns, the workflow can assign species‑specific carbon‑storage factors and thus capture the heterogeneity of carbon density within the stand. All observations are fed into the open‑source BIOMASS model, which produces calibrated Above‑Ground Biomass (AGB) and Above‑Ground Carbon (AGC) maps together with quantitative uncertainty estimates derived from sensor noise, model parameter variance and validation against field plots. The resulting products deliver a scientifically robust, repeatable baseline for CRCF certification and for ongoing monitoring of carbon dynamics in the tropical pilot area.

Pilot site

• 35,000 ha of afforestation and conservation land in the Vichada Department, Colombia, with over 1,000 monitoring plots.