400
May 2014
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
Table 5 Bias removal from measurements
Residuals (after bias removal)
ΔE
(Easting)
ΔN
(Northing)
ΔH
(Elevation)
meter
meter
meter
-0.001
0.036
0.055
0.159
-0.089
-0.006
-0.001
0.036
-0.017
-0.053
-0.037
0.042
-0.061
0.106
-0.011
-0.041
-0.089
0.013
-0.001
0.036
0.048
Number of check points
7
7
7
Mean (m)
0.000
0.000
0.018
StDEV (m)
0.075
0.073
0.030
RMSE (m)
0.069
0.068
0.033
Finally, according to the accuracy requirements for Class I of
the ASPRS map standard, the RMSE of Easting and RMSE
of Northing needs to be within 15 cm (if we consider the
ortho photo with GSD of 7.5 cm supports mapping at scale of
1:600 or 1”=50’). In our case the ortho photo is meeting the
standard before and after the bias removal. As for the vertical
accuracy, the Lidar data needs to have an RMSE of 10 cm or
less vertically in order to meet Class I of the standard for 1 ft
contours. Looking at the vertical accuracy results of 0.033m,
the Lidar data is meeting the standard as well.
“Most the value of the mean can
be interpreted as a bias if the
standard deviation is very low or
approaches zero”
**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.
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