VR-based visual analytics of LIDAR data for cliff erosion assessment

ABSTRACT

The ability to explore, conceptualize and correlate spatial and temporal changes of topographical records, is needed for the development of new analytical models that capture the mechanisms contributing towards sea cliff erosion. This paper presents a VR-centric approach for cliff erosion assessment from light detection and ranging (LIDAR) data, including visualization techniques for the delineation, segmentation, and classification of features, change detection and annotation. Research findings are described in the context of a sea cliff failure observed in Solana Beach in San Diego county.