It is that time of the quarter again where I am buried in projects to grade. We just wrapped up another round of the Digital Terrain Modeling Course at OSU. We had 17 graduate students in the class from backgrounds including Civil Engineering (many focused on Geomatics), Geography, Water Resources, Forestry Engineering, and Biological and Ecological Engineering. In the class the students learn fundamental skills to program, work with LIDAR data, and apply those skills to create DTMs using several methods such as triangulation, ground filtering, gridding, and thin plate spline. The students also use Cyclone software provided by Leica Geosystems to manipulate the point cloud data.
I decided to distract myself from grading and write this quick article discussing the exciting and innovative projects that the students developed. There were 6 groups, each who developed an outstanding presentation.
The Wata Group
This group obtained LIDAR data for the Portland, Oregon area and performed a flood mapping analysis based on a portion of the data. The students compared several techniques of DTM generation, breakline insertion, and combining LIDAR and bathymetry data to produce a high quality DTM. They then used ArcGIS and Hec-Ras software to perform inundation studies, which were exported to Google Earth for visualization.
Team Biomass obtained LIDAR data for a forest in Northern California and extracted inventory data using the US Forest Service (USFS) software Fusion. They then used those metrics to calculate biomass using a regression equation. The LIDAR derived values were comparable to estimates derived through traditional techniques.
This group extracted parameters such as slope and terrain roughness from a DTM to determine landslide susceptibility. They compared slopes at locations with landslides to locations that did not have landslides using SLIDO (Statewide Landslide Information Database for Oregon) created by the Oregon Department of Geology and Mineral Industries (DOGAMI). These comparisons could then be used to determine landslide susceptible areas.
This team used a point cloud created using Microsofts online service Photosynth to produce a terrain model of a stream channel bank. This data was then compared to data acquired using a total station for erosion volume estimates. This site experienced significant erosion when a major storm event occurred after a removal of a dam.
This team used a micron-resolution scanner to scan surfaces to evaluate surface roughness. The students performed a comprehensive comparison of all modes of the scanner (distance from surface, level of light, point density, and application of powder for improved reflectivity) and several methods to calculate surface roughness. They also evaluated the impact of filling holes from occlusions in the model and its influence on the results.
Team JCL studied the Johnson Creek Landslide, which continually damages Highway 101 along the Oregon Coast. This team used two terrestrial laser scan datasets to evaluate landslide movement. The students extracted points from several trees across the site, created code to do a least squares fit of a circle to those points and compared movement of that tree in the two datasets. The results were compared to cylinder extraction in Cyclone and were generally consistent (within 1-4 cm). One tree had moved by 42 cm in the 6 months between datasets! One student will continue this work to automate the procedure for his graduate thesis research project.
Thanks to: The students who worked hard in the class, Leica Geosystems for providing software, and Chris Gifford-Miears, Rachelle Valverde, and Tseganeh Gichamo (The Wata Group) for providing the images!