PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
August 2014
715
Q1: In LiDAR data, do we have missing pulses that are
not returning to the sensor? When does that happen?
Dr. Abdullah:
Missing pulses occur during the LiDAR scanning process due
to various reasons including the following:
1)
When the laser pulse hits a weak or non-reflective
surface. Water, for example, has the tendency to absorb
most or all of the near-infrared laser energy directed
toward it resulting in either a very weak or absent
return. Not all water behaves this way, though, as laser
reflection from water is affected by the water surface
roughness (i.e. the presence of waves) and water contents
(i.e. turbidity). Freshly paved asphalt roads and parking
lots were also reported to absorb laser energy.
2)
When the laser pulse hits a specular reflective surface.
Specular reflection is the mirror-like reflection of light
from a surface, in which light from a single incoming
direction (a ray) is reflected into a single outgoing
direction that is away from the LiDAR. Glass slanted
at a certain angle and sometime water surface are good
examples of specular reflector.
3)
When the Laser pulse travel a distance longer than the
range gate setting allows. To manage the pulsing rate
of a LiDAR sensor, the returned signal is unwelcomed
if it returns after a very short or very long period of
time, shorter than the minimum or longer than the
maximum range gate setting. Such a cause of missing
pulses is common in a mountainous area with variable
relief if the mission is not planned carefully.
Q2: What is a break line?
Dr. Abdullah:
A break line is a three-dimensional line that is part of a digital
terrain model representing abrupt changes or breaks in the
terrain. A point cloud alone, unless super dense, is not suitable
for representing sudden drops or cuts such as retaining walls
in the terrain. Therefore, break lines are needed if the terrain
surface contains sudden changes in its slopes that usually occur
around ditches, riverbanks, roads edges, retaining walls, etc.
The following are short answers for questions raised by participants of
the ASPRS online webinar “LiDAR Fundamental and Applications.”
Q3: With photogrammetry, we use photo identifiable or
targets as QC points. With LiDAR, do you use similar
practices (identifiable) or just a position with X,Y and Z?
Dr. Abdullah:
Photo identifiable, or a targeted check point, has little or no
use in evaluating the vertical accuracy of LiDAR due to the
nature of the LiDAR point cloud. As practiced today, LiDAR
accuracy verification is usually limited to evaluating the vertical
accuracy of LiDAR data, and very little attention, if any, is paid
to the horizontal accuracy. A good check point for evaluating
LiDAR vertical accuracy is usually located in an open and
homogenously slopped or flat terrain away from elevated man-
made or natural features. Such point is defined by a known
X, Y and Z, but not necessarily identifiable. Photo identifiable
check points such as road intersections and fence corners can be
utilized to evaluate the horizontal accuracy of a LiDAR data set.
Q4: Where does one learn how to process LiDAR data
or find examples of performing the production flow you
presented in slide 45?
Dr. Abdullah:
Unfortunately, I am not aware of a formal non-degree
program that offers a technical training program on LiDAR
data processing; however, some of the LiDAR data processing
software companies such as GeoCue and Terrasolid offer
formal training courses on the use of their software for
processing LiDAR data. Pennsylvania State University
also offers a good online course on LiDAR and LiDAR data
processing. Taking advantage of either or both of these
resources is a good start for you and for whoever wants to
learn about LiDAR and LiDAR data processing.
**Dr. Abdullah is Senior Geospatial Scientist at Woolpert,
Inc. He is the 2010 recipient of the ASPRS Photogrammetric
(Fairchild) Award.
The contents of this column reflect the views of the author,
who is responsible for the facts and accuracy of the data pre-
sented herein. The contents do not necessarily reflect the offi-
cial views or policies of the American Society for Photogram-
metry and Remote Sensing and/or Woolpert, Inc.
