" ability to take a point cloud that has no color information on it, and overlay it into an orthophoto to produce a colorized point cloud"
Add-on to ArcGIS
LP360 for ArcGIS™ (Basic, Standard and Advanced)
I'm a little late to the party but here is another suggestion: http://potree.org/
It's an open souce, WebGL based point cloud viewer I've been working on for quite a while.
== UPDATE ==
It can render large amounts of colored point clouds. LIDAR data without colors will be supported soon.
Source code: https://github....
ESRI has a pretty good help section on LiDAR (below). For more formal details on LiDAR, I would recommend the following books:
Topographic Laser Ranging and Scanning: Principles and
Airborne and Terrestrial Laser Scanning
Remote Sensing and Image Interpretation
LiDAR Laser Returns
Laser pulses emitted from a lidar system reflect from ...
According to Diego Alonso's comments from the mappingGIS blog1, this error is related to QGIS version 2.14. With the upgrade, the standalone installer eliminated the msys folder from GRASS 7 algorithms.
To bypass this error, go to Processing -> Options -> Provider and deactivate all GRASS folders from previous versions. Set these paths as blanks. Then, ...
I decided to merge other answers with mine and organize them into a tabular format. I think it is easier to read and manage for future visitors:
The table can be accessed from the following link in csv format:
View in tabular form: Free LiDar DataSources
Download (csv): Free LiDar DataSources
Please submit pull request if you intended to add to this ...
lidR is a great package in R for forestry applications.
From the GitHub lidR documentation:
R package for Airborne LiDAR Data Manipulation and Visualization for
The lidR package provides functions to read and write .las and .laz
files, plot point clouds, compute metrics using an area-based
approach, compute digital ...
Generating LiDAR DEMs from unclassified point clouds with:
MCC-LIDAR - Multiscale Curvature Classification (MCC) algorithm.
(supports LAS versions 1.1 to 1.3)
MCC-LIDAR is a command-line tool for processing discrete-return LIDAR data in forested environments (Evans & Hudak, 2007).
a) unclassified point cloud.
b) ground returns ...
It's not possible to convert GEDI .h5 file to LAS file as including all data. Because .h5 file includes a lot of information about a point (actually it is a window in GEDI .h5 format, not a point). Also, since LAS file has certain attributes for a point not matching attributes/values in .h5 file, you cannot add all information to LAS file. For example, which ...
laspy is another good LAS read/write software. It supports working with the data directly in numpy arrays and a number of other nice Pythonic features. It isn't processing software per se, however.
PDAL has the ability to use Python as an in-pipeline filtering language, but this isn't a processing engine either.
There isn't too much in the Python quiver ...
ArcGis has a new LiDAR dataset at 10.1 which will allow you to view your LiDAR data directly and also see more information than what's in a raster... for example you can add to ArcMap and then filter down the display to just tree classes, or just first returns!
LiDAR data contains much more than just elevation, there's intensity that is stored by default (...
This ended up being more straightforward than I thought, with all of the capabilities lying in the rasterio.open function.
Here is an example using a proj4 string instead of wkt.
from rasterio.transform import from_origin
arr = np.random.randint(5, size=(100,100)).astype(np.float)
transform = from_origin(472137, 5015782, 0.5, 0.5)
Your PointsXYZIC is now a numpy array. Which means you can use numpy indexing to filter the data you're interested in. For example you can use an index of booleans to determine which points to grab.
#the values we're classifying against
unclassified = 1
ground = 2
#create an array of booleans
filter_array = np.any(
PointsXYZIC[:, 4] == ...
When converting a LiDAR dataset to a DEM, you are taking a set of discrete data points and converting them into a single, continuous dataset. Let's say that your .las file contains X (latitude), Y (longitude) and Z (elevation) values with an average resolution of ~1 meters. The resolution here is really important- we're only talking about an average and so ...
For converting to las 1.2 from las 1.4, PDAL's translate command is an option:
pdal translate --writers.las.minor_version=2 input-las14.las output-las12.las
LAStools can also do the job:
las2las -i input-las14.las -set_version 1.2 -o output-las12.las
In general, las 1.4 support is patchy among free and open-source las-aware software, e.g. liblas doesn't ...
It sounds like you want either a voxel-based thinning or maybe a Poisson-based one. PDAL can do either. See PDAL's tutorial on the topic at https://pdal.io/tutorial/sampling/index.html
As far as the size of the file, please define "large". Just about any technique except simple rank decimation (remove n-th points) is going to want to have access to the ...
Set the scaling and offset when reprojecting to WGS84, e.g.:
las2las --a_srs EPSG:26911 --t_srs EPSG:4326 -i file1.las -o output.las --scaling 1e-7 1e-7 0.01 --offset <something close to your data's longitudes>,<something close to your data's latitudes>,0
You've been caught by a limitation/feature of the las file format. Internally,...
Have you consider to use GRASS GIS analysis? I have expirience that GRASS algorithms have very good accurance on hydrology analysis. For example, I want to generate something like drainage network on DTM with resolution 5x5m. I had compared tools from ArcMap (including ArcHydro Tools) and you can view the result on first picture (red lines). Then I tried to ...
libLAS can indeed be used commercially. So can Martin Isenburg's LASlib, which is LGPL, and speaking as the author of libLAS, faster and more completely supported than libLAS. Both are indeed C++ libraries, however, and there isn't too much in the ASPRS LAS space for native .NET.
I'm also the primary author of PDAL, and PDAL can also read ASPRS LAS data, ...
There is a considerable body of literature on individual crown detection in spectral and lidar data. Methods wise, perhaps start with:
Falkowski, M.J., A.M.S. Smith, P.E. Gessler, A.T. Hudak, L.A. Vierling and J.S. Evans. (2008). The influence of conifer forest canopy cover on the accuracy of two individual tree measurement algorithms using lidar data. ...
Thank you for clarifying your question as it was previously quite unclear. You can read a multiband raster using the stack or brick function in the raster package and assign the associated RGB values to an sp SpatialPointsDataFrame object using extract, also from raster. Coercion of the data.frame object (which results from read.csv) to an sp point object,...
I develop an open-source GIS called Whitebox Geospatial Analysis Tools that can be used to perform a range of tasks geared towards processing LiDAR data. It works with the popular LAS file format as well as shapefiles. The software can be used to interpolate raster grids, including bare-Earth DEMs and vegetation canopy models. Many of the interpolators are ...
Inside a Geodatabase, there are certain ways you can't name a table or Feature Class. Beginning with a number is one of those ways.
Validating Table and Field Names in Python:
Try renaming your table to las_1 or something and see if it works
I have recently released an open-source (MIT) stand-alone (i.e. no dependencies) library called WhiteboxTools for performing many types of geospatial analysis, including LiDAR data processing. The library is written in Rust and has extensive support for Python-based scripting. For example, the following Python script uses the WhiteboxTools library to ...
If you have a raster DEM already, then there is a tool that I developed in Whitebox Geospatial Analysis Tools called Remove Off-Terrain Objects, contained within the LiDAR toolbox, that works well for creating bare-earth DEMs, particularly in urban and agricultural settings. It works less well where either the terrain is steeply sloped or the forest cover is ...
If you are open to using alternative software to solve your problem, then I can suggest the Remove Off-Terrain Objects tool of the cross-platform open-source GIS Whitebox Geospatial Analysis Tools (of which I am lead developer). I realize that you said in your question that you could not convert your data to LAS format, but the tool takes a raster, not LAS ...
The picture below from Fernandez-Diaz (2011) might help complementing Aaron's answer.
Lidar returns are discrete observations* recorded when a laser pulse is intercepted and reflected by targets. Multiple returns derive from one laser pulse intercepting multiple targets (e.g. a top of a tree, its branches, and the ground).
*such as coordinates x, y and z; ...
If you have the opportunity to get LAS or LAZ instead of TXT ... absolutely go for it. It will be trivial for you to go from LAS or LAZ to TXT (for example with the free and open source las2txt tool from LAStools). Ordering TXT instead of LAS means to loose many important attributes that you may not care about today but will in a few months or years. It also ...
The answer by Howard Butler pretty much sums it up. Some more background. When I created the first LAStools and the LASlib library that the tools are build upon I was a postdoc at UC Berkeley and merely needed to prepare LAS files as input for my research on Streaming Delaunay (or Streaming TIN) processing. Because the code seemed useful on its own I zipped ...
The current option to import las files in ArcGIS is the LAS dataset data type. According to ESRI:
The LAS dataset provides fast access to large volumes of lidar and surface data without the need for data conversion.
If the surface (raster) you are trying to create is a bare-earth DEM refer to the following posts:
One option is the LAS dataset to Raster ...