PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
April 2015
269
Q: I was among the attendees of your session on the new
ASPRS Map Accuracy Standards during the last ASPRS
fall conference held in Denver in November 2014. Could
you please elaborate more on the new standards, its
similarity with the previous standards and how to use it?
Anonymous
Dr. Abdullah:
PART II: In the January 2015 issue of “Mapping
Matters”, I introduced PART I of my answer to the question
by introducing the new standard and the reasons behind
its development. In the last couple decades, the Geospatial
community witnessed tremendous changes in the mapping
process due to the rapid advancements in data acquisition
sensor technologies and the maturity of processing software
and algorithms. Such changes created the opportunity and
need for new standards in evaluating and quantifying the
quality and the accuracy of the more sophisticated mapping
products. Naturally, such changes in the mapping process
deemed all previous legacy map accuracy standards; such as
ASPRS Map Accuracy Standard of 1990 and the National Map
Accuracy Standard (NMAS); obsolete and unable to represent
today’s more sophisticated mapping processes and products.
PART I also introduced the horizontal accuracy measure for
Geospatial Data and how the accuracy class definition does
not limit the classes to a certain ranking or certain number of
classes as the legacy standards did. In PART II I will continue
the discussions on horizontal accuracy and will introduce the
vertical accuracy measure for Geospatial Data.
In PART I of my answer, I included an example that was
provided in the new standard on how to convert a horizontal
accuracy measure, according to the new standard, to its
equivalent in the legacy ASPRS standard of 1990. A similar
example was provided in the new standard on how to relate a
horizontal accuracy measure, according to the new standard, to
its equivalent in the legacy National Map Accuracy Standard
(NMAS) of 1947 as illustrated in the following example:
Example 2: Converting the horizontal accuracy of
a map or orthoimagery from the new ASPRS 2014
standard to the legacy of 1947.
Given:
a map or orthoimagery with an accuracy of RMSE
x
= RMSE
y
= 15 cm according to the new 2014 standard,
compute the equivalent accuracy and map scale according
to the legacy National Map Accuracy Standard (NMAS) of
1947, for the given map or orthoimagery.
Solution:
1. Because the accuracy figure of RMSE
x
= RMSE
y
= 15 cm
is relatively small, it is safe to assume that such accuracy
value is derived for a map with a scale larger than
1:20,000. Therefore, we can use the factor “1/30 inch.”
2. Use the formula CMAS (CE90) = 2.1460 × RMSE
x
=
2.1460 × RMSE
y
CE 90% = 2.1460 × 15 cm = 32.19 cm
3. Convert the CE 90% to feet
32.19 cm = 1.0561 foot
4. Use the NMAS accuracy relation of CE90% = 1/30 inch on
the map, compute the map scale
CE 90% = 1/30 × (ground distance covered by an inch of
the map), or ground distance covered by an inch of the
map = CE 90% × 30 = 1.0561 foot × 30 = 31.68 feet
5. The equivalent map scale according to NMAS is equal to
1” = 31.68’ or 1:380
H
orizontal
A
ccuracy
R
equirements
for
E
levation
D
ata
When it comes to the horizontal accuracy for elevation data, the
new standard distinguishes between two sources of elevation
data. Those are the ones produced from the photogrammetric
process such as stereo-compilation and auto-correlation or the
ones produced from modern scanning sensors such as LiDAR
and IFSAR.
Photogrammetric Elevation Data:
For elevation data
derived from photogrammetric means such as stereo
compilation or image-based auto-correlation, the horizontal
accuracy equates to the horizontal accuracy class that would
apply to planimetric data or digital orthoimagery produced from
the same source imagery and the same aerial triangulation/
INS solution. Therefore, if the horizontal accuracy class
for digital orthoimagery or planimetric data produced from
certain imagery is RMSE
x
and RMSE
y
equal to10-cm, then
the horizontal accuracy for any elevation data such as break
lines, mass points, spot heights, or point cloud derived from
stereo-pairs generated from the same imagery using the same
