LIDAR Point Cloud Visualization

A common question we get asked is how to visualize the point cloud data produced by either the Linear-mode or Geiger-mode LIDAR simulations. First, you should remember that the point cloud files produced by the "APD Processor" are simple ASCII/text files. Each line is the entry for a single return or "point" in the point cloud, including the point location and some attributes that vary depending on whether you modeled a Linear-mode or Geiger-mode system.

For a Linear-mode system, a point cloud file will generally look like the example below:

12.7388 -45.3612 -0.0256 5.0290 0 0 0 0
12.8169 -45.3612 -0.0264 4.8362 0 1 0 0
12.8950 -45.3612 -0.0271 4.8362 0 2 0 0
...
32.4008 -25.5446 10.5945 4.6783 0 65533 0 0
32.4781 -25.5446 10.5953 5.8959 0 65534 0 0
32.5360 -25.5640 12.5408 5.9185 0 65535 0 0

The first three columns are the X/Y/Z location of the point return. The 4th column is the intensity (in photons). Since Linear mode can support multiple returns per pulse, the 5th column is the return number. The 6th column is the pixel number, followed by the pulse number and the task number.

The following tools are available as either freeware or trial-ware that are specifically designed to visualize and analyze LIDAR point cloud data:

• LViz
• Fusion
• SAGA-GIS
• MARS FreeView

However, since the data is simple 3D point data almost any 3D plotting tool can be used. That includes the plotting capabilities in tools like Matlab, IDL, etc. One of the easiest tools to acquire is GNUplot, which is available for free on nearly every platform. This article will show you some easy ways to use GNUplot to visualize ASCII/text point cloud data.

In these examples, I have a point cloud file that I produced using the Linear-mode model (the file is named "lmapd.xyz"). The following GNUplot command produces a basic 3D point plot:

gnuplot> splot "lmapd.xyz" using 1:2:3 with points

The "splot" command takes the filename and a few options. The "using 1:2:3" option tells it to use the 1st, 2nd and 3rd columns for the X/Y/Z point location. The "with points" option tells it to draw the points using the "points" style. This command results in the plot below:

This simple command shows us that there is some 3D structure in the data, but it is very hard to make sense of it because the points are big and hard to distinguish. GNUplot has an option to color-code the points based on an attribute with each point. The following plot command will color code based on the Z (height):

gnuplot> splot "lmapd.xyz" using 1:2:3:3 with dots palette

The "with dots" option plots each point with a smaller symbol and the "palette" option will color-code the points based on the 3rd field, which is the Z height (note the 4th token in the "using" option defines which column is used to drive the color). The resulting plot is shown below:

Note that with the height color coded and the smaller plot symbols we can start to make out that this is a flat field near a tree line. When modeling a Linear-mode detector, the 4th column in the point cloud file is the intensity. We can using that field to drive the point color using the following plot command:

gnuplot> splot "lmapd.xyz" using 1:2:3:4 with dots palette

which results in the plot below:

Notice that you can now see some variation in the ground reflectance and visually identify two different tree species (the brighter yellow tree in the back corner and the darker orange ones). The intensity also reveals that there is an object under the trees that is much darker than the rest of the area. In this case, that object is a tank and at this wavelength (1064 nm) the paint is much darker than the vegetation (vegetation has high reflectance in the near-IR region).

Note that this article shows static views of the point cloud, but on most platforms you can click and drag to rotate the GNUplot display interactively. Where GNUplot starts to struggle is with really large point clouds. Most of the LIDAR specific visualizers use "level of detail" and "point culling" techniques to make the display fast regardless of how many points are being displayed. Although GNUplot lets you set the range of points to plot (see the "set xrange", "set yrange", etc. commands), it is a brute-force plotting tool and draws every single point.

This article focused on visualizing output of a Linear-mode system, but the same basic commands can be used on used on Geiger-mode point clouds. Since GmAPD systems tend to pulse the same area multiple times, I sometimes associate the "palette" color with the pulse number so I can see which overlapping points are associated with which pulse.