JavaScript is Disabled
Your browser's JavaScript functionality is disabled. It has to be enabled to use this function of ConfTool.
Here you can find information on how to enable JavaScript
If you have any problems, please contact the organisers at EO4Society.Conf@esa.int.

Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Daily Overview

Session

Biomass and Ecosystem Modelling
Location: Purple Hall
Session Chair: Jerome Chave, Cnrs
Session Chair: Roman Guliaev, DLR e.V.

Presentation 2

4:40pm - 5:00pm

Assessing the impact of canopy structure on modelled P-band radar backscatter for ESA BIOMASS calibration and validation

Wanxin Yang^1,2, Russell Thomas¹, Mathias Disney^1,2, Philip Lewis^1,2, Casey Ryan³, Steven Hancock^2,3, Reza M. Asiyabi³, Kyle Dexter³, John L. Godlee³, Nezha Acil^2,4, Mark R. Lomas⁵, Shaun Quegan^2,5, Oliver McFarlane⁶

1: Department of Geography, University College London, United Kingdom; 2: National Centre for Earth Observation, United Kingdom; 3: School of GeoSciences, University of Edinburgh, United Kingdom; 4: School of Geography, Geology and the Environment, Centre for Landscape and Climate Research, University of Leicester, United Kingdom; 5: School of Mathematical and Physical Sciences, University of Sheffield, United Kingdom; 6: University of Edinburgh, United Kingdom

The ESA BIOMASS mission, recently launched as the first spaceborne P-band synthetic aperture radar (SAR), aims to generate global maps of forest aboveground biomass (AGB) and improve our understanding of forest contributions to the global carbon cycle. Despite its potential, the influence of canopy structural variability on P-band radar backscatter remains insufficiently understood, limiting the physical interpretability of BIOMASS observations.

In this study, we assess the sensitivity of P-band radar backscatter to forest canopy structure using the Michigan Microwave Canopy Scattering (MIMICS) model parameterised with terrestrial laser scanning (TLS) data. Our initial analysis focuses on four savanna woodland plots in Bicuar National Park, Angola, and one tropical rainforest plot in Lopé National Park, Gabon. Individual trees were extracted from the TLS data and reconstructed into quantitative structural models (QSMs) to derive detailed branch-level architectural parameters, which were then used to parameterise MIMICS simulations across all radar polarisations and incidence angles consistent with the BIOMASS observation geometry.

To investigate the relationship between canopy structure and P-band backscatter, we computed integrated metrics capturing fundamental physical properties relevant to electromagnetic interactions. Results indicate that tree size and structural complexity are primary factors of backscatter magnitude, with less structural complex generally producing stronger P-band backscatter. Simulated backscatter from the Gabon rainforest plot was further compared with BIOMASS Level-1 products over a nearby forested region to evaluate model performance and sensitivity.

This modelling framework enables us to explore and quantify the key structural parameters driving variability in the P-band radar response, and to examine potential variations across forest types and sensitivity to environmental factors such as soil moisture. Ultimately, the insights gained from this work will support the development of a physically-informed deep-learning approach aimed at assessing the accuracy and uncertainty of EO-derived biomass estimates from regional to global scales.