Changes between Initial Version and Version 1 of Processing/LIDARDEMs

Timestamp:

Apr 8, 2008, 6:32:12 PM (16 years ago)

Author:

benj

Comment:

Created

Processing/LIDARDEMs

@@ +1 @@
+== Creation of DEMs from LIDAR point clouds ==
+
+This guide assumes you have a LIDAR dataset comprising a number of files containing LIDAR lines of the following format:
+{{{
+217755.001130 30563577.97 4513423.12 1293.23   178 30563577.96 4513423.12 1293.28   178
+time(gps?)(last pulse) ZZeasting northing height(m) pulse_time? (first pulse) ZZeasting northing height(m) pulse_time? 
+}}}
+
+1. Merge files and strip off unnecessary UTM zone number by running trim_lidar.sh in the directory containing the lidar files:
+Usage: trim_lidar.sh output_file
+
+2. Generate a histogram for the lidar data to determine min/max reasonable data values by running lidar_histogram.py:
+Usage: python lidar_histogram.py input_file
+
+This generates a 5x log histogram (ie it's a histogram of the base-10 log of the lidar values binned into 10m bins, multiplied by 5 to scale). If there are a small number of low or high values in the histogram then decide on a scaling cutoff. eg:
+
+{{{
+20: 
+40: #################
+50: #############################
+60: #############################
+70: ##############################
+80: ##############################
+90: ###############################
+100: ###############################
+110: ###############################
+120: ################################
+130: ################################
+140: ###############################
+150: #############################
+160: ############################
+170: ############################
+180: ###########################
+190: ###########################
+200: ##########################
+210: #######################
+220: ###################
+230: ##############
+590: #####
+600: ######
+610: ######
+620: ####
+}}}
+
+In the given example, there are a very few values between 20-30m at the bottom end, and a big gap at the top end before a small number of values above 590m (nothing between 240m and 590m). So it would be sensible to pick 30m as a minimum cutoff and 250m as a maximum.
+
+3. Open GRASS, select (or create) an appropriate UTM/WGS84 location and set the region appropriately for the dataset - easiest way is to look at the start of the trimmed lidar data file for the starting co-ordinates of the first line, set an approximate region from there, view the map in GRASS and then adjust the region appropriately.
+
+4. Read in the trimmed lidar file using r.in.xyz:
+{{{
+r.in.xyz input=<trimmed_lidar_file> output=<lidar_basemap> x=2 y=3 z=4 fs=" " zrange=<min_cutoff>,<max_cutoff>
+}}}
+
+5. Interpolate gaps in the map using r.fillnulls:
+{{{
+r.fillnulls input=<lidar_basemap> output=<lidar_interp_map>
+}}}
+
+6. Generate an ASCII DEM as per [wiki:Processing/NextMapDEMs Creation of DEMs from NextMap data]:
+{{{
+r.out.ascii input=<lidar_interp_map> output=lidar.dem null=0
+}}}