Zak Kus (recipient of three LASmoons)
Topology Enthusiast
San Francisco, USA
Background:
While LiDAR data enables a lot of research and innovation in a lot of fields, it can also be used to create unique and visceral art. Using the high resolution data available, a 3D printer, and a long tool chain, we can create a physical, 3D topological map of the San Francisco bay area that shows off both the city’s hilly geology, and its unique skyline.
Goal:
The ultimate goal of this project is to create an accurate, unique physical map of San Francisco, and the surrounding areas, which will be given to a loved one as a birthday gift. Using the data from the 2010 ARRA-CA GoldenGate survey, we can filter and process the raw lidar data into a DEM format using LAStools, which can be converted using a python script into a „water tight“ 3D printable STL file.
While the data works fairly well out of the box, it does require a lot of manual editing, to remove noise spikes, and to delineate the coast line from the water in low lng areas. Interestingly, while many sophisticated tools exist to edit STLs that could in theory be used to clean up and prepare the files at the STL stage, few are capable of even opening files with so much detailed data. Using LAStools to manually classify, and remove unwanted data is the only way to achieve the desired level of detail in the final piece.
Data:
+ LiDAR data provided through USGS OpenTopography, using the ARRA-CA GoldenGate 2010 survey
+ Average point density of 3.33 pts/m^2 (though denser around SF)
+ Covers 2638 km^2 in total (only a ~100 km^2 subset is used)
LAStools processing:
1) Remove noise [lasnoise]
2) Manually clean up shorelines and problematic structures [lasview, laslayers]
3) Combine multiple tiles (to fit 3d printer) [lasmerge]
4) Create DEMs (asc format) for external tool to process [las2dem]