TEC researchers provide new techniques for visualizing dynamic landscapes

Published Oct. 17, 2013
A time-series representation of nearshore elevation surfaces showing the dynamic layer of terrain change and the shoreline evolution band over a given time period.

A time-series representation of nearshore elevation surfaces showing the dynamic layer of terrain change and the shoreline evolution band over a given time period.

This image shows the Tangible Geospatial Modeling System (TanGeoMS) at North Carolina State University used for analyzing relationships between the morphology of elevation surfaces and dynamic landscape processes.  A flexible physical model can be modified by hand and scanned to create digital representations of altered landscapes within a geographic information system.

This image shows the Tangible Geospatial Modeling System (TanGeoMS) at North Carolina State University used for analyzing relationships between the morphology of elevation surfaces and dynamic landscape processes. A flexible physical model can be modified by hand and scanned to create digital representations of altered landscapes within a geographic information system.

ALEXANDRIA, Va. - ERDC-TEC scientists are conducting an ongoing research project involving the analysis of time-series Light Detection and Ranging (LiDAR) point clouds to better understand terrain evolution in space and time, resulting in new methods for visualizing landscape dynamics.

This work has been captured in “Visualizations of Coastal Terrain Time-series” for the international journal Information Visualization under lead author Laura Tateosian.  ERDC contributing author is Bruce Blundell, with additional authors Helena Mitasova, Sidharth Thakur, Eric Hardin, and Emily Russ. 

The team took advantage of multiple airborne LiDAR collections over the dynamic near-shore environment of North Carolina’s Outer Banks.  Using this information, the team was able to investigate new approaches for 3D visualization of spatio-temporal information using a voxel model of time-series elevation data to create a space-time reference cube (STC) that captures terrain dynamics in a continuous space-time domain.  The STC approach allows the analyst to visualize the space-time trajectories of objects or terrain features undergoing dynamic change.

These new approaches will aid the assessment of significant topographic change and resulting effects, landscape evolutionary trends, and the vulnerability of a region to storm impacts and earth-movement activity.