3D virtual forest replicas from terrestrial laser scanning for microwave interaction modelling

Résumé fourni par la source

Terrestrial laser scanning (TLS) is being recognized as a key technology in forest monitoring by providing highly detailed 3D point clouds of the ecosystem. Recent algorithmic and computational advances now allow for the near-automated processing of the raw point clouds into 3D reconstructions of real forests. Here, we show how these 3D ‘virtual forest’ replicas, combined with the parameterization of its components (e.g. leaves, stems, soil), can serve as input for microwave interaction models (MIM) to study the interaction of electromagnetic waves with forests scenes in a realistic simulation environment. First, we present ongoing work on in-vivo stem dielectric permittivity estimation with wood penetrating radar (WPR). Novel experimental WPR sensors are currently being tested, which non-destructively measure the forward and back scatter of multi-frequency microwaves emitted through the tree trunk by placing two antennas on opposite sides of the stem. Two such sensors have been installed on a sycamore tree in the Ghent University forest experimental site (Belgium) and have been measuring at a 20-minute time interval since February 2024. Concurrently, weather and microclimate variables are recorded and monthly TLS scans of the tree are made to capture the 3D dynamics (e.g. seasonality, growth, branch loss) of the tree. From the WPR measurements, the (dynamic) dielectric permittivity can be estimated, which holds potential to parametrize the woody components of the virtual forest for microwave MIM. We show preliminary results of how the dielectric permittivity relates to environmental and phenological variability. Secondly, we demonstrate the use of microwave MIM using data from the Caxiuanã research site in the eastern Amazonia (Para, Brazil), the longest running drought experiment in the tropics. Both the 1-ha control plot and 1-ha rain throughfall exclusion (TFE) plot have been reconstructed into a 3D virtual forest from TLS acquired in November 2024. Additionally, for both plots, a tower radar system is installed centrally in the plot and 21 trees in the field of view of the radar are equipped with FDR sensors to estimate the stem water content. By combining these data sources, we aim to parameterize the MIPERS-4D microwave MIM and will show preliminary results of how simulations compare to actual measurements. With these two use cases, we aim to demonstrate that the combination of structurally accurate 3D virtual forests with a parameterized microwave MIM would allow for a powerful instrument to facilitate the calibration and validation of remote sensing signals and derived biophysical products such as forest water status or biomass.

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