Coastal LiDAR
Santa Clara county
For this project I want to closely examine a reach of road that goes into the hills to see if it can accommodate addition of a footpath.
I downloaded data that was collected by the Santa Clara Water District in 2006. The area of interest is small, covered by 4 tiles. See https://coast.noaa.gov/htdata/lidar1_z/geoid12a/data/4870/ The data is in LAZ format.
What coordinate system is this data in? It's in WGS84 and the vertical unit is 1 meter.
First thing I want to do is generate simple first return and last return surfaces.
The files are already classified, see the metadata:
"This data set is an LAZ (compressed LAS) format file containing LIDAR point cloud data. LAS format files, raw LiDAR data in its native format, classified bare-earth LiDAR DEM and photogrammetrically derived breaklines generated from LiDAR Intensity stereo-pairs. Breakline, Top of Bank, and contour files in ESRI personal geodatabase format, Microstation V8 .dgn format, and AutoCAD 2004 formats for the San Jose Phase 3 project of Santa Clara County, Ca. This project arrived with only unclassified data. NOAAs Office for Coastal Management performed an automated classification using lasground. Although class 1 and class 2 are available, there was no QA/QC on the points after lasground was performed."
Generating surfaces from raw data For ArcGIS this means "terrains". For QGIS it means DEM rasters.
I am starting with terrains, which means first I need to get the data out of the LAZ files and into ArcGIS.
I installed the lastools into ArcGIS already, let's see what I have in there.
http://www.spatialguru.com/lidar-data-to-raster-file-with-open-source-gdal-tool/
http://www.cs.unc.edu/~isenburg/lastools/ See the README files for details on each tool.
In the order I might use them in my tool chain:
lasmerge : Merge my tiles into one LAS file. lasmerge -i *.las -o out.las
lasclip : Clip the data to a polygon. Most of one of the tiles is outside my study area, so I should get rid of that data. Except processing the full 4 tiles is so fast that it does not matter!
lasground : tool for bare earth extraction (class=2 : ground, class=1 not ground)
las2dem : Make a TIN then make a raster from the TIN.
This is interesting too.
lastrack : Generates profile along a GPS track.
Setting step size will help remove buildings. Default is 5m, try -town or -city or -metro as options.
Vertical unit can be meters (the default) or else try "-feet".
For steep hills try "-fine" or "-extra_fine"
lasinfo (160710) report for D:\GISData\CA\SantaClara\LAH_merged.laz
reading 'D:\GISData\CA\SantaClara\LAH_merged.laz' with 13366138 points
reporting all LAS header entries:
file signature: 'LASF'
file source ID: 0
global_encoding: 0
project ID GUID data 1-4: 00000000-0000-0000-0000-000000000000
version major.minor: 1.1
system identifier: 'LAStools (c) by rapidlasso GmbH'
generating software: 'lasmerge (version 160710)'
file creation day/year: 1/1970
header size: 227
offset to point data: 387
number var. length records: 2
point data format: 1
point data record length: 28
number of point records: 13366138
number of points by return: 11562914 1709526 92895 803 0
scale factor x y z: 0.0000001 0.0000001 0.001
offset x y z: 0 0 0
min x y z: -122.1056002 37.3255269 -795.944
max x y z: -122.0878199 37.3532182 971.289
variable length header record 1 of 2:
reserved 43707
user ID 'NOAA_CSC'
record ID 129
length after header 2
description 'Sort Order'
variable length header record 2 of 2:
reserved 43707
user ID 'LASF_Projection'
record ID 34735
length after header 48
description 'Projection Parameters'
GeoKeyDirectoryTag version 1.1.0 number of keys 5
key 1024 tiff_tag_location 0 count 1 value_offset 2 - GTModelTypeGeoKey: ModelTypeGeographic
key 2048 tiff_tag_location 0 count 1 value_offset 4269 - GeographicTypeGeoKey: GCS_NAD83
key 2054 tiff_tag_location 0 count 1 value_offset 9102 - GeogAngularUnitsGeoKey: Angular_Degree
key 4096 tiff_tag_location 0 count 1 value_offset 5103 - VerticalCSTypeGeoKey: VertCS_North_American_Vertical_Datum_1988
key 4099 tiff_tag_location 0 count 1 value_offset 9001 - VerticalUnitsGeoKey: Linear_Meter
the header is followed by 2 user-defined bytes
LASzip compression (version 2.4r2 c2 50000): POINT10 2 GPSTIME11 2
reporting minimum and maximum for all LAS point record entries ...
X -1221056002 -1220878199
Y 373255269 373532182
Z -795944 971289
intensity 1 5100
return_number 1 4
number_of_returns 1 4
edge_of_flight_line 0 0
scan_direction_flag 0 0
classification 1 2
scan_angle_rank 0 0
user_data 0 0
point_source_ID 294 770
gps_time 661.683328 602614.538400
number of first returns: 11562914
number of intermediate returns: 93700
number of last returns: 11563016
number of single returns: 9853492
overview over number of returns of given pulse: 9853492 3233170 276260 3216 0 0 0
histogram of classification of points:
9643729 unclassified (1)
3722409 ground (2)
Success. lasinfo done.
Completed script lasinfo...
Succeeded at Mon Jul 18 12:11:15 2016 (Elapsed Time: 6.35 seconds)
Gold Beach
20-Apr-2011 Going to Gold Beach for Easter weekend, so naturally I am looking at Curry county data once again.
I have a nice NAIP 2009 photo of the area now. 1/2 meter 2009 county level files are available as zipped files via FTP from Oregon Explorer
Working with LiDAR obtained from the Oregon Coastal Atlas
Holes in LiDAR data
I have created a contour and a hillshade, which is great, but the LiDAR is full of holes! I think since it's a coastal dataset (NOAA) they don't care about the areas up a bit from the beach.
I am thinking I can fill the holes with 10m DEM data, so I found an example on how to do this and will look at it this evening.
