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The Challenge of Community LiDAR data
LiDAR acquisition over km2 = billions of LiDAR returns > km2 0.5 m DEM tiles as “standard” products Large user community with variable needs and levels of sophistication. How do we deliver large community datasets such as these? Northern California GeoEarthScope LiDAR
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The Challenge of Community LiDAR data
LiDAR coverage of the southern San Andreas and San Jacinto faults - ~ 3.7 billion LiDAR returns, ~1.9 TB - Very high-res., supports cm DEMs
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Delivery Hard Disc or DVD Files organized into tiles Point cloud Pre-computed DEMs Organization typically kilometer tiles or USGS quarter quads Naming convention hopefully meaningful
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Files x,y,z,date,time,returnnumber,noreturns,offnidar,returnint,classification , ,69.06,1204, E+003,1,5,15.63,116,"G" , ,69.28,1204, E+003,1,5,15.18,114,"G" , ,69.11,1204, E+003,1,5,14.72,86,"G" , ,68.84,1204, E+003,1,5,14.27,84,"G" , ,68.74,1204, E+003,1,5,15.58,104,"G" , ,68.91,1204, E+003,1,5,15.12,132,"G" , ,68.86,1204, E+003,1,5,14.67,100,"G" , ,68.53,1204, E+003,1,5,14.21,77,"G" , ,68.28,1204, E+003,1,5,13.77,61,"G" , ,68.12,1204, E+003,1,5,13.40,62,"G" , ,68.05,1204, E+003,1,5,12.95,59,"G" , ,67.77,1204, E+003,1,5,12.50,55,"G“ x,y,z,gpstime,returnint,passid , ,920.10," ",117,"Str_169" , ,919.99," ",138,"Str_169" , ,919.24," ",137,"Str_169" , ,918.94," ",126,"Str_169" , ,919.26," ",104,"Str_169" , ,919.28," ",107,"Str_169"
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Files, Cont. LAS: Binary point cloud format “industry standard” Much smaller file sizes due to binary format Requires specific tools to read or translate Relatively uncommon in geoscience datasets
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Files cont. Digital Elevation Models: ESRI binary grids Filtered and unfiltered a.k.a. bare earth and full feature Ascii grids (.asc) Arc ascii “standard” ascii
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