LASmoons: Scott W. Anderson

Scott W. Anderson (recipient of three LASmoons)
University of Colorado at Boulder, USA
Institute of Arctic and Alpine Research (INSTAAR)

Background:
In September of 2013, a combination of atmospheric events conspired to produce immense volumes of rain over the Front Range of Colorado. Between September 9th and 15th, the region received as much as 18″ of precipitation, as much as normally falls over the course of a full year. In addition to the well-documented floods, recent mapping by the USGS has identified at least 1,300 debris flow/landslide events. A subset of these mass failures are captured in both a 2010 airborne LiDAR survey covering the area west of Boulder, CO, and an October, 2013 survey flown by FEMA in the aftermath of the floods.

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Goal:
This research primary aims to estimate the volume of material mobilized by these debris flows through LiDAR differencing. With careful alignment of the two surveys, such differencing techniques provide a robust and spatially continuous measure of the volume of sediment transport in these flows. This will:
+ provide insight into the fate of the debris flow sediment as they enters trunk-valley streams
+ produce estimates of total landscape lowering that place this event within a larger landscape-evolution context
+ help explore the dynamics of debris flow bulking (how and why debris flow gain or lose mass)

2010 Data:
+ 370 square kilometers of LiDAR west of Boulder, Colorado
+ average point density: 11.6 pts/m2

2013 Data:
+
310 square kilometers of LiDAR focused on main drainages of the Front Range, Colorado
+ point density not yet known

LAStools processing:
1)
transform the 2010 dataset from the GEOID03 to GEOID12a ellipsoid (lasheight)
2) remove roll-bias in the 2013 dataset (lasheight)
3) classify ground points to ensure consistent classification techniques (lasground)
4) create 1 meter DTMs (las2dem or blast2dem)
5) perform vertical alignment checks using the LiDAR (lasoverlap) or with terrain matching based on the raster DTM (ArcGIS), translate the point clouds (las2las) and create final DTMs.

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