Comparing Two Methods of Surface Change Detection on an Evolving Thermokarst Using High-Temporal-Frequency Terrestrial Laser Scanning, Selawik River, Alaska

Theodore Barnhart,Benjamin Crosby

doi:10.3390/rs5062813

Abstract

Terrestrial laser scanners (TLS) allow large and complex landforms to be rapidly surveyed at previously unattainable point densities. Many change detection methods have been employed to make use of these rich data sets, including cloud to mesh (C2M) comparisons and Multiscale Model to Model Cloud Comparison (M3C2). Rather than use simulated point cloud data, we utilized a 58 scan TLS survey data set of the Selawik retrogressive thaw slump (RTS) to compare C2M and M3C2. The Selawik RTS is a rapidly evolving permafrost degradation feature in northwest Alaska that presents challenging survey conditions and a unique opportunity to compare change detection methods in a difficult surveying environment. Additionally, this study considers several error analysis techniques, investigates the spatial variability of topographic change across the feature and explores visualization techniques that enable the analysis of this spatiotemporal data set. C2M reports a higher magnitude of topographic change over short periods of time (~12 h) and reports a lower magnitude of topographic change over long periods of time (~four weeks) when compared to M3C2. We found that M3C2 provides a better accounting of the sources of uncertainty in TLS change detection than C2M, because it considers the uncertainty due to surface roughness and scan registration. We also found that localized areas of the RTS do not always approximate the overall retreat of the feature and show considerable spatial variability during inclement weather; however, when averaged together, the spatial subsets approximate the retreat of the entire feature. New data visualization techniques are explored to leverage temporally and spatially continuous data sets. Spatially binning the data into vertical strips along the headwall reduced the spatial complexity of the data and revealed spatiotemporal patterns of change.

Highlights

In the last decade, techniques to rapidly acquire high density topographic data have proliferated; the tools to adequately analyze change within these complex data sets have only begun to emerge
The difference in the change detection thresholds is due to the fact that M3C2 considers the RMS error and the uncertainty due to local and apparent roughness when determining if a calculated displacement is significant
This study presents a comparison of two point cloud change detection techniques, cloud to mesh (C2M) and Multiscale Model to Model Cloud Comparison (M3C2) [22], which were applied to an extensive Terrestrial laser scanners (TLS) data set gathered under difficult survey conditions at a permafrost dominated field site

Summary

Introduction

Techniques to rapidly acquire high density topographic data have proliferated; the tools to adequately analyze change within these complex data sets have only begun to emerge. Enable the acquisition of topographic data sets with postings between 1 m and

Methods

Results

Conclusion