174
March 2015
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
S
pecific
R
equirements
Testing is always recommended but may not be required for all data sets;
specific requirements must be addressed in the project specifications. When
testing is required, horizontal accuracy shall be tested by comparing the
planimetric coordinates of well-defined points in the data set with coordinates
determined from an independent source of higher accuracy. Vertical accuracy
shall be tested by comparing the elevations of the surface represented by the
data set with elevations determined from an independent source of higher
accuracy. This is done by comparing the elevations of the checkpoints with
elevations interpolated from the data set at the same x/y coordinates.
All accuracies are assumed to be relative to the published datum and
ground control network used for the data set and as specified in the
metadata. Ground control and checkpoint accuracies and processes should
be established based on project requirements. Unless specified to the
contrary, it is expected that all ground control and check points should
normally follow the guidelines for network accuracy as detailed in the
Geospatial Positioning Accuracy Standards, Part 2: Standards for Geodetic
Networks, Federal Geodetic Control Subcommittee, Federal Geographic
Data Committee (FGDC-STD-007.2-1998). When local control is needed
to meet specific accuracies or project needs, it must be clearly identified
both in the project specifications and the metadata.
Horizontal accuracy is to be assessed using root-mean-square-error
(RMSE) statistics in the horizontal plane, i.e., RMSE
x
, RMSE
y
, and RMSE
r
.
Vertical accuracy is to be assessed in the z dimension only. For vertical
accuracy testing, different methods are used in non-vegetated terrain (where
errors typically follow a normal distribution suitable for RMSE statistical
analyses) and vegetated terrain (where errors do not necessarily follow
a normal distribution). When errors cannot be represented by a normal
distribution, the 95
th
percentile value more fairly estimates accuracy at a
95% confidence level. For these reasons vertical accuracy is to be assessed
using RMSE
z
statistics in non-vegetated terrain and 95
th
percentile statistics
in vegetated terrain. Elevation data sets shall also be assessed for horizontal
accuracy where possible.
With the exception of vertical data in vegetated terrain, error thresholds
stated in this standard are presented in terms of the maximum acceptable
RMSE value. Corresponding estimates of accuracy at the 95% confidence
level values are computed using
National Standard for Spatial Data
Accuracy
(NSSDA) methodologies and are subject to the limitations that
the data be normally distributed and with systematic bias removed such that
the mean error of the data is small.
A
ccuracy
R
equirements
for
A
erial
T
riangulation
and
G
round
C
ontrol
P
oints
The standard introduces for the first time accuracy measures for the
ground control used in aerial triangulation and for the results of the
aerial triangulation itself. The standard distinguishes between accuracy
requirements for the ground control based on the final products derived
from the process. Two different requirements are specified, those are:
•
Accuracy of ground control designed for planimetric data
(orthoimagery and/or digital planimetric map) production only:
RMSE
x
or RMSE
y
= ¼ * RMSE
x(Map)
or RMSE
y(Map)
,
RMSE
z
= ½ * RMSE
x(Map)
or RMSE
y(Map)
•
Accuracy of ground control designed for elevation data, or planimetric
data and elevation data production:
RMSE
x
, RMSE
y
or RMSE
z
= ¼ * RMSE
x(Map)
, RMSE
y(Map)
or
RMSE
z(DEM)
As for the measure of accuracy for aerial triangulation, the standard also
based it on the intended final products derived from the process. Two
different requirements are specified, those are:
•
Accuracy of aerial triangulation designed for digital planimetric data
(orthoimagery and/or digital planimetric map) only:
RMSE
x(AT)
or RMSE
y(AT)
= ½ * RMSE
x(Map)
or RMSE
y(Map)
RMSE
z(AT)
= RMSE
x(Map)
or RMSE
y(Map)
of orthoimagery
•
Accuracy of aerial triangulation designed for elevation data, or
planimetric data (orthoimagery and/or digital planimetric map) and
elevation data production:
RMSE
x(AT)
, RMSE
y(AT)
or RMSE
z(AT)
= ½ * RMSE
x(Map)
, RMSE
y(Map)
or RMSE
z(DEM)
H
orizontal
A
ccuracy
S
tandards
for
G
eospatial
D
ata
Table 1 specifies the primary horizontal accuracy standard for digital data,
including digital orthoimagery, digital planimetric data and scaled planimetric
maps. This standard defines horizontal accuracy classes in terms of their
RMSE
x
and RMSE
y
values. While prior ASPRS standards used numerical
ranks for discrete accuracy classes tied directly to map scale (i.e., Class 1,
Class 2, etc.), many modern applications require more flexibility than these
classes allowed. For example, using the new standard, a Scope of work, could
specify that digital orthoimagery, digital planimetric data, or scaled maps
must be produced to meet ASPRS Accuracy Standards for 7.5 cm RMSE
x
and RMSE
y
Horizontal Accuracy Class.
This standard does not associate product accuracy with the ground sample
distance (GSD) of the source imagery, pixel size of the orthoimagery, or
map scale for scaled maps. Due to the digital nature of today’s geospatial
data and the different architectures and configuration of aerial sensors, many
applications of horizontal accuracy cannot be tied directly to compilation
scale, resolution of the source imagery or final pixel resolution. The
relationship between the recommended RMSE
x
and RMSE
y
accuracy class
and the orthoimagery pixel size varies depending on the imaging sensor
characteristics and the specific mapping processes used. The appropriate
horizontal accuracy class must be negotiated and agreed upon between the
end user and the data provider, based on specific project needs and design
criteria. Table 2 presents examples of 24 horizontal accuracy classes and
associated quality criteria as related to digital orthoimagery.
Additional tables in the full standard, not included in this highlight article, provide
the most common associations that have been established (based on user’s
interpretation and past technologies) to relate orthoimagery pixel size to map
scale and the ASPRS 1990 legacy standard map accuracy classes; and general
guidelines to determine the appropriate orthoimagery accuracy class for three
Table1. Horizontal Accuracy Standards for Geospatial Data
Horizontal
Accuracy Class
Absolute Accuracy
Orthoimagery Mosaic Seamline Mismatch
(cm)
RMSE
x
and RMSE
y
cm)
RMSE
r
(cm)
Horizontal Accuracy at 95% Confidence Level
(cm)
X
-cm
≤
X
≤1.414*
X
≤2.448*
X
≤ 2*
X
