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Conference Agenda

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Session

📌Poster Session and Networking Aperitivo 🍷
Location: Lower Lobby

Presentation 42

BIOMASS Cal/Val with forest inventory and UAV lidar data in the Peruvian rainforest

Xiao Liu¹, Marie Schreiber², Matthias Forkel¹

1: TUD Dresden University of Technology, Germany; 2: Wilderness International

ESA’s BIOMASS mission is the first P-band SAR satellite. The penetration capability of P-band microwave and the SAR tomography (TomoSAR) configuration of BIOMASS provide an unprecedented opportunity to improve the quantification of carbon stock in tropical forests. Robust in-situ and airborne data are necessary for the calibration and validation (Cal/Val) of BIOMASS products, including above-ground biomass densities (AGB), forest height (FH) and forest disturbances (FD). To support the BIOMASS Cal/Val, this project will collect forest inventory and unmanned aerial vehicle (UAV) lidar data in the Peruvian rainforest.

Along the Tambopata River in tropical Peru, we will establish further reference sites to specifically validate BIOMASS estimates along gradients from intact to degraded tropical forests and by quantifying changes in biomass from 2024 to 2026/2027 by using UAVs with LiDAR and aerial imaging. Some areas were already surveyed in 2021 and 2024. Forest inventories on smaller plots (max. 20 × 50 m) were also conducted, recording species, stem diameter, and tree height. To meet the standards set out in the BIOMASS Products Verification and Validation Plan, larger inventories and further UAV surveys are planned to first represent a spatial gradient from degraded to undisturbed rainforest and second to quantify changes in biomass from 2024 to 2026/2027. The inventory and UAV data will be published in an open data repository.

The objectives of this project are to: (1) validate the BIOMASS products using field inventory and UAV lidar data; (2) estimate changes in forest height and AGB using BIOMASS and comparing them with the changes detected from multitemporal UAV lidar, and (3) investigate the sensitivity of the TomoSAR reflectivity profiles to the vertical forest structure by comparing the BIOMASS P-band TomoSAR reflectivity profiles with the lidar-derived forest vertical structure profiles (e.g., canopy cover profile).