Generalized Extraction of Surface Dynamics from Multimodal 4D Point Clouds for Topographic Monitoring of Earth Surface Processes and Their Interactions (Extract4D)

• Applicants: Professorin Dr. Katharina Anders; Professor Dr. Bernhard Höfle
• Subject Area: Geodesy, Photogrammetry, Remote Sensing, Geoinformatics, Cartography
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 535733258

The observation of surface dynamics in natural landscapes provides valuable insights on Earth shaping processes, their complex interactions, and environmental drivers. The analysis of surface activities in 4D point cloud data has therefore become integral to topographic monitoring of local landscape scenes in environmental research. These data contain detailed 3D information of the topography with time as additional dimension, acquired by techniques like permanent terrestrial laser scanning (TLS) or time-lapse 3D photogrammetry at (sub-)hourly intervals over months to years. Recent methods of change analysis incorporate the time series information to identify and characterize surface activities with variable spatiotemporal properties. However, methods so far focus on data from unimodal acquisitions (e.g., TLS only) and assuming a regular acquisition interval of near-continuous 3D observation systems. However, 4D point clouds are often adaptively sampled in time, both by design or due to external influences on regular acquisition schedules. Further, supplementary acquisitions, e.g. by multistation TLS or UAV-based 3D sensing are often performed to increase coverage and decrease uncertainty. This project seeks to advance information that can be gained on surface dynamics by integrating multimodal 4D point clouds in time series-based change analysis for various data sources and types of surface activities. This research entails the generalization of a recent and the current state-of-the-art 4D point cloud method, the extraction of 4D objects-by-change (4D-OBCs), which delineates individual surface activities in an observed scene in space and time. 4D-OBC extraction will be extended to automatically adjust to different input point clouds (laser scanning vs. photogrammetry, variable temporal sampling and spatial scales, different types of surface dynamics), mainly by considering spatially and temporally variable uncertainties, and by accounting for irregular temporal sampling. Based on this, different strategies of integrated change analysis are investigated, with approaches of fusion on the data level of 3D time series and on the feature level of change information derived from each unimodal 4D point cloud dataset. The project makes use of virtual laser scanning of a variety of scenarios of surface dynamics and three use cases of real 4D point cloud data from different geographic settings. By this, the project improves automatic analysis and results which can be obtained from 4D point clouds in topographic monitoring of complex natural scenes. This basic research renders methods of 4D change analysis transferrable to a variety of use cases in environmental research.

• DFG Programme: Research Grants