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| Subject: | [gislist] DTED and basics of GPS |
| Date: |
09/27/2004 11:20:01 PM |
| From: |
DickBoyd .. aol.com |
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I read Dr. Young's 15 page "Spatial Modeling of Highways Using GPS Data. The
modeling will be used to estimate highway sighting distance, both for passing
and stopping. The paper was a thumbnail representation of Dr. Young's hard
work in advancing the art of surveying and its applications to civil engineering.
Thank you, Dr. Young.
Some things that came to mind when I read Dr. Young's paper.
Digital Terrain Elevation Data (DTED), in my mind, is the baseline for
elevation data in digital format.
OMB Circular A-16 provides guidance to those in the public sector for
collecting, archiving and processing geographic information.
Two web sites that provide more information on GIS:
http://da.state.ks.us/gis/
http://www.ceres.ca.gov/tcsf/GIS/
These sites also link to other GIS information sources.
My experience has been that agencies tend to reinvent the wheel because they
don't know what data exists, or what researchers in associated disciplines are
studying. GIS provides a common ground to exchange geographic information.
The error models and analysis of data distribution in the GIS program should,
in my opinion, be the same for all users. Distribution both in the sense of
communication and histogram spread.
DTED is based on NIMA. National Imaging Agency photo reduction. The data is
presented in 30 arc second samples. (About half a mile.) However, underlying
data is available for finer resolution. I don't know what the smallest
resolution is.
The graininess, or least significant difference, is the key to establishing
sight distance. Richard Haberman explains "graininess" in his book
"Mathematical Models". Except Haberman uses traffic counts and sampling times to
illustrate the rapid variation of traffic density's dependence on length of measuring
time. If the measuring time is too short, the observations vary excessively
from sample to sample. If the observation is too long, the phenomenon is averaged
out and is hidden by the data reduction system. Dr. Young hints at sampling
distance, but must be using this paper just to whet a mathematician or
surveyor's intellectual appetite.
Dr. Young mentions using GPS receivers to collect geographic information.
GPS is a clock. Every second each satellite transmits a coded signal. The
signal is very accurately timed and also contains information on the satellites
position, orbit and propagation corrections. A GPS receiver decodes the signal
and determines time of arrival. Using the time of arrival and information
regarding the position of the satellite, the receiver solves a series of
simultaneous equations for the intersections of the spheres that represent the distance
from each satellite. The receiver then applies corrections to converge the
solution to a single point. Or if the solution does not converge to a point,
then to a minimum likely volume. If this likely volume is not zero, there are
residual errors.
Possibly a discussion of "dilution of precision" would help in quantifying
the errors. There is GPS geometric dilution of precision that represents the
volume created by the intersection of four spheres.
Vertical observations have the most errors because seldom is a GPS satellite
directly overhead. Usually the earth itself is considered a pseudolite to
converge the position solution. Knowing how the GPS receiver solves the equations
should provide some help in deciding how to weight observations.
For horizontal sighting distance, vertical accuracy is not that much of an
error source. But for vertical sighting, vertical accuracy is key to consistent
results.
A "truth" or verification method was mentioned briefly. Will researchers go
out to the roads with transits, chains and levels to verify the calculation
from data?
Dr. Young used the terms "relative" and "absolute" to describe errors.
Absolute being earth center as reference. Relative being an observation or monument
near to a group of other observations.
The absolute error represents how close the solution comes to describing
earth coordinates and being able to repeat the measurement. Relative errors
represent how close the solution describes distances and angles between nearby
places.
Dr. Young's work can result not only in more uniformly marked roads, but also
in more consistent justification for needed improvements in alignments and
grades.
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