Tree4D

Project title

Enhanced methods for assessing vegetation structure and change from multi-echo and full-waveform laser scanner data of terrestrial LiDAR systems

Funding

Deutsche Forschungsgemeinschaft (DFG)

Project number: 519022036

Description

Terrestrial LiDAR has become a widely accepted measurement technique for the efficient acquisition of data to describe vegetation structure. For the derivation of structural parameters such as vegetation density, biomass, and growth parameters in tree stands, the volumetric reconstruction of the measurement data with ray-propagation modelling approaches proves to be particularly advantageous. However, the performance of existing methods is limited, e.g. by systematic under-representations due to occlusion effects, non-uniform spatial resolution of the measurement data and their restriction to static measurement systems.

The central goal of the project is the development of enhanced methods for the generation of complete unbiased volumetric reconstructions of the vegetation structure. The focus is on novel ray propagation modelling approaches that take into account both the geometry and the radiometry of the laser pulses when transforming static and mobile laser scanner data into a voxel space. For full-waveform data, the complete signal is transformed into voxel space by deriving voxel space entries from the amplitudes of the reconstructed differential backscatter cross section. In the case of multi-echo data, the contact frequency within each traversed voxel is determined and the intensity of the detected echoes is taken into account. The resolution of the voxel space is adapted to the recording geometry and the spatial resolution of the measurement data. For vegetation applications, the majority of laser pulses are affected by partial or total occlusions, leading to a systematic underrepresentation of the vegetation structure. Partial occlusion modelling allows for the derivation of a correction term compensating for the effects of partial interceptions of the laser beam at leaves and branches. The basic idea of the approach to be developed is an analysis of the individual pulse history in combination with the interpretation of the recorded intensity values. For full-waveform data, an integral correction based on the signal waveform, and for multi-echo data, a segment-wise correction based on the contact frequency can be applied. Filling gaps in the volumetric reconstruction due to total occlusion effects requires the development of 3D mathematical morphology operators. The resulting volumetric representations provide a basis for exploiting the potential of the 3D measurement data and thus serve a wide range of scientific measurement tasks in the field of vegetation structure research. Applying the methodology to multi-temporal data sets, changes in vegetation structure can be determined at high accuracy.

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Relevant publications

• Boehme, S., Bienert, A., Richter, K., 2024: Untersuchung des Potentials von multi-temporalen TLS-Daten zum Monitoring des Wachstums von Laubbäumen. DGPF-Jahrestagung 2024 (44. Wissenschaftlich-Technische Jahrestagung der DGPF), Band 32, ISSN 0942-2870, S. 58-66.
• Bienert, A., Richter, K., Boehme, S., Maas, H.-G., 2024: Investigating the Potential of Hyper-Temporal Terrestrial Laser Point Clouds for Monitoring Deciduous Tree Growth, June 2024, The International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences XLVIII-2-2024:33-40, DOI:10.5194/isprs-archives-XLVIII-2-2024-33-2024

Contact

• Dr.-Ing. Katja Richter (Processing)
• Dr.-Ing. Anne Bienert (Project Manager, Processing)
• Prof. Dr. habil. Hans-Gerd Maas (Project Manager)