ADVANCES IN GEOMORPHIC CHANGE DETECTION: PROMISE AND PITFALLS OF WORKING WITH BIG POINT CLOUDS

Recent advances in topographic surveying technologies have given rise to Terrestrial Laser Scanning (TLS), Multi-beam SONAR (MBS), Structure from Motion (SFM), and Airborne Laser Scanning (ALS). Each of these enables the rapid acquisition of high resolution point cloud data sets. The potential utility of these point clouds for the purpose of quantifying geomorphic process rates and geomorphic change detection is exciting but the reliability of such estimates are dependent upon the environmental conditions they were acquired in as well as the user’s ability to effectively filter the point clouds, efficiently manage the memory intensive files, quantify the uncertainty in the topographic representation, and convert the point clouds to data formats in which relevant analysis can be performed and presented from. Two basic approaches to change detection exist, one relies on cloud-to-cloud differencing and the other on surface-to-surface differencing. A variety of techniques and software packages exists to undertake these analyses, each with their own advantages and disadvantages. This presentation seeks to highlight recent methodological advances and software that enable large point clouds to be efficiently used in geomorphic change detection studies. Specific attention is given to the comparison of raster based surface-to-surface differencing that leverages the power of the high resolution point cloud. To further highlight some of the challenges large point clouds present, a case study of geomorphic change detection using MBS point clouds is used as a template to demonstrate specific improvements to the Geomorphic Change Detection Software and preview the new ZCloudTools project.