PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
September 2017
601
S
hould
you
generate
contours
in
the
presence
of
a
dense
and
accurate
lidar
dataset
?
Unless you need contours plotted on a hard copy map for field
workers or support, I believe creating contours from a lidar
dataset is an unwise practice for the following reasons:
1.
You can benefit more from the lidar points cloud, as it
is denser and richer in information than contours. Con-
tours are generated by subsampling, (parsing or thin-
ning) dense lidar data to generate less dense data. In
other words, it is equivalent to hiding some valuable
information about the terrain elevation residing in the
points cloud.
2.
Generating contours from a lidar points cloud is prob-
lematic and, if you want the contours to have the aes-
thetic look of the contours generated from photogram-
metry, takes valuable labor hours. Remember, contours
generated from DTM (i.e. breaklines and mass points)
are smooth, as the contours are interpolated from mass
points (and breaklines, if they exist) with post spacing
of 50 feet or more. Such wide spacing of mass points
smooth the interpolated contours, as it is less sensitive
to the micro changes in elevation across the terrain. On
the contrary, lidar points cloud, because of their high
density, are very sensitive to changes in elevation, so
contours generated from lidar do not look appealing.
However, such contours are more accurate in represent-
ing the terrain than the photogrammetric contours.
3.
Many software applications can handle lidar datasets
and can model the terrain in more creative ways than
contours.
Q
uestion
2—D
o
we
need
breaklines
to
augment
the
lidar
dataset
before
generating
contours
?
Assuming your applications demand the creation of contours
to plot on a paper map, the quality and accuracy of the creat-
ed contours using a lidar dataset depends on the lidar points
cloud density and the application at hand. For most applica-
tions, when using a USGS QL2 lidar dataset, you don’t need
to add breaklines due to the high density of the points cloud.
Remember that breaklines are only needed in the absence of a
dense points cloud, as was the case with the photogrammetric
modeling of terrain. Why would anyone need breaklines for
terrain modeling when the ground is sampled at a 71-centi-
meter or even 35-centimeter interval? What would be a better
way to define terrain relief than by surveying a spot elevation
every 35 or 71 centimeters that lidar data can provide? Some
people are concerned about the contours’ accuracy with the
absence of breaklines. I can assure you that breaklines will
not add much to the definition or the accuracy of the terrain
model when using a dense lidar dataset. It can result in more
appealing contours at road edges and other sharp breaks in
the terrain, but again, it will not add to the accuracy or the
quality of the contours. Some applications call for breaklines
for hydro enforcement, which is another problematic concept.
That is mainly due to the limitation of many software appli-
cations used in hydro modeling. For down-slope flow model-
ing, this software expects lidar points not to fluctuate, even
within the noise limit or accuracy of the lidar data. That is
the only reason massive modeling of breaklines is added to
represent linear water feature and to assure a smooth and
enforced downhill flow. These modeling software companies
or agencies would help the industry and reduce project cost
if they would implement a tolerance of elevation fluctuation
to within the repeatability of the lidar points cloud, which is
specified in the USGS lidar base specifications to be around
6 centimeters. Some specify breakline compilation solely for
hydro flattening of water bodies. In my opinion, the latter use
of breaklines is a total waste of effort, because most of the
time this is done for aesthetic reasons. Users of lidar data
should accept the fact that lidar data is very dense, and there
always will be an unevenness in the surface due to the ran-
dom errors in the data represented by the repeatability of
lidar data, which in most cases amounts to within 6 centi-
meters. Lake surfaces do not need to look completely flat and
smooth in a lidar dataset. If we accept this fact, we could save
hundreds if not thousands of hours flattening such surfaces.
Even for volumetric computations, such unevenness of lidar
data will not compromise the volume computations’ accura-
cy. Such fluctuation is random and occurs around the mean
terrain elevation, assuming all biases are removed from the
lidar dataset. We need to recognize that some applications or
situations will require the collection of breaklines even with a
very dense lidar dataset at least for the time being and until
our processes and modeling software changes. Examples of
such situations are the following:
1.
Road Design and Engineering:
Most specifications
for departments of transportation (DOTs) call for pre-
cise delineation of the following:
a.
Edge of pavement
b.
Road crown
c.
Curbs and gutter lines
d.
Top and base of curves
e.
Other elements of the road
Current capabilities of aerial lidar collection do not allow
engineers to accurately determine these lines from lidar,
therefore manually collected breaklines are needed to com-
plete DOT road engineering activities. In addition, providing
breaklines with mobile mapping system (MMS) data allows
for the reduction of the size of the delivered data so modeling
“contours generated from lidar make a
better representation of the terrain than
the contours generated from DTM”
