PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
March 2014
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The DQMs are not direct point-to-point comparisons
because it is nearly impossible for a lidar system to col-
lect conjugate points in different swaths. It is easier to
identify and extract conjugate surfaces and related fea-
tures (e.g. roof edges) from lidar. The DQMs over natural
surfaces and over roof planes assume that these conjugate
surfaces are planar, and determine the measure of sepa-
ration between a point and the surface (plane). The DQM
over roof edges extract break lines or roof edges from two
intersecting planes and measure their discrepancy.
DQM Over Natural Surfaces:
Point to (Tangential) Plane Distance
This DQM is calculated by selecting a point from one swath
(e.g. point ‘p’ in swath # 1), and determining the neigh-
boring points (at least three) for the same coordinates in
swath # 2. Ideally, the point ‘p’ (from swath # 1) should lie
on the surface defined by the points selected from swath
# 2. Therefore, any departure from this ideal situation
will provide a measure of discrepancy, and hence can be
used as a DQM. This departure is measured by fitting a
plane to the points selected from swath # 2, and measur-
ing the (perpendicular) distance of point ‘p’ to this plane.
DQM Over Roof Planes:
Point to Conjugate Plane Distance
Where man-made planar features (e.g. roof planes) are
present in the region of overlap, these features can be ex-
tracted and used for measuring the inter-swath goodness
of fit. These planes can be extracted automatically, or with
assistance from an operator. Assuming PL1 and PL2 to be
conjugate roof planes in swath # 1 and swath # 2 respec-
tively, the perpendicular distance of points used to define
PL1 to the plane PL2 can be determined easily. Instead
of selecting any random point, the centroid of points used
to define PL1 can be determined. The centroid to plane
PL2 (in swath # 2) distance can be used as a DQM to mea-
sure the inter-swath goodness of fit (Habib et. al., 2010).
DQM Over Roof Break Lines:
Point to Conjugate Line Distance
If man-made linear features (e.g. roof edges) are present in
the overlapping regions, these can also be used for measuring
discrepancy between adjacent swaths. Roof edges can be de-
fined as the intersection of two adjacent roof planes and accu-
rately extracted. Conjugate roof edges (L1 and L2) in swaths
#1 and # 2 should first be extracted automatically or using
operator assistance. The perpendicular distance between the
centroid of L1 (in swath # 1) to the roof edge L2 (in swath #
2) is a measure of discrepancy and can be used as DQM to
the measure inter-swath goodness of fit (Habib et. al., 2010).
Absolute Accuracy of Lidar Data
The current practice of measuring the accuracy of lidar
data is to collect GCPs in open horizontal regions and mea-
sure the discrepancy in the vertical coordinates from the
lidar-derived surface. A disadvantage of using this method
is that horizontal errors in the data are not accounted for.
Specially designed and built targets are commonly used
in photogrammetry, and can be used as a means to assess
Table 1. Data Quality Measures (DQMs) or inter-swath goodness of fit measures
Nature of surface
Examples
Data Quality Measures (DQMs)/Goodness
of fit measures
Units
Natural surfaces
Ground surface, i.e. not
trees, chimneys, electric
lines etc.
Point to natural surface (tangential plane to surface) distance Meters
Point to surface vertical distance
Meters
Man-made surfaces
Roof planes
Perpendicular distance from the centroid of one plane to the
conjugate plane
Meters
Roof edges
Perpendicular distance of the centroid of one line segment to
the conjugate line segment
Meters
Figure 3. Representation of DQM over natural surfaces. Point ‘p’ (red dot) is from swath # 1 and the blue dots are from swath # 2
