name:ahmed wazer Nov 2012
category: heighing and Gps
LIMITATIONS TO GPS HEIGHTING
In practice, GPS heighting typically involves measuring ellipsoidal heights with GPS,
applying some form of geoid model and making any adjustment to fit the resulting
orthometric heights to the existing vertical datum. Therefore, in examining the limitations of
GPS heighting it is necessary to consider three broad areas:
· limitations of the GPS measurement
· limitations due to the available geoid model
· limitations due to vertical datum issues
Some or all of these issues vary in importance depending on the overall extent of the GPS
survey in question. GPS surveys over national and continental scale are typically associated
with datum level geodetic operations and need to consider many more issues than day to day
surveys which extend over a few kilometres or less. In considering limitations to GPS
heighting, this paper will attempt to highlight when the scale of the project is relevant.
Limitations of the GPS measurement
Obviously, the first limitation in GPS heighting is the quality of the GPS solutions used to
obtain a height. Three broad categories of GPS observation types are possible:
· Point Positioning which is the stand alone navigation mode for which GPS was
designed;
· Differential GPS (DGPS) which uses a differential correction approach but which is
primarily based on pseudo range measurements and
· GPS Surveying using a differential approach but primarily based on measurement of
the phase of the GPS signals.
While DGPS and even Point Positioning may be useful for producing heights in certain
applications, the term GPS Heighting is typically taken to refer to the use of phase
measurement techniques that can be grouped under the broad heading of GPS Surveying.
This paper concentrates on heighting using these higher precision GPS Surveying
techniques.
Within GPS Surveying, an overall consideration is whether the phase ambiguities have been
resolved to integer values. Ambiguity resolution affects all three dimensions, not only height.
For the measurement techniques known as Rapid Static and Real Time Kinematic (RTK),
which are used for shorter baselines, ambiguity resolution is a prerequisite and should be
achieved for most day to day GPS surveying applications. It is important to realise that RTK
uses the smallest possible amount of data and even the best algorithms sometimes resolve
the ambiguities incorrectly. To avoid such errors, which can reach the metre level, it is
important to build redundancy into a survey by, for example, occupying stations more than
once.
Two aspects that can affect the overall quality of the baseline solution are errors in the
ephemeris or in the starting coordinates used in the processing. The effect of these can reach
several parts per million and apply to all three dimensions. Assuming that the broadcast
ephemeris quality remains as high as in recent times, its effect will be minimal for most
applications over short baselines. However, it should be noted that obtaining a WGS84
three-dimensional starting position of a reasonable quality (say +/- 10m or better) could be
more problematic in some areas of the world.
Another error source to consider is multi-path. Reflective surfaces can mean that some of
the signal reaching the antenna does not travel on a direct path from the satellite. The effects
of multi-path can reach the decimetre level in three dimensions. Observation over time to
allow the satellite geometry to change sufficiently enables the effect of multi-path to be
reduced through averaging. However, with the short observation times typical of the Rapid
Static and RTK techniques in common use, it is necessary to pay attention to this issue.
While modern hardware and software designs include various ways of reducing the effects of
multi-path, even over short observation times, it is important to choose stations so as to
reduce the likelihood of multi-path and build redundancy into the survey to enable detection
of any remaining effect.
Atmospheric delay is another issue to be considered. For a short baseline one can reasonably
assume that the radio signals measured by both receivers pass through the same part of the
atmosphere. However, as baseline length increases that assumption begins to break down
and atmospheric effects need more consideration. Two components of the atmosphere are
relevant, the ionosphere and the troposphere.
Problems due to the upper atmospheric layer known as the ionosphere can affect all three
dimensions and become significant on lines longer than, say 20km. For such longer baselines,
processing software is able to take advantage of the fact that the ionospheric effect is related
to the frequency of the signal and dual frequency measurements can be used to remove most
of the effect. The effect of the ionosphere is greater near the poles and the geomagnetic
equator and varies over time in association with solar disturbance cycles. Therefore, it
should be noted that for certain areas and certain times the ionospheric effect can be
significant, even over short baselines.
The effect of the troposphere is particularly significant for height measurement. Unlike the
ionosphere, tropospheric delay cannot be mitigated using dual frequency measurement.
Furthermore, the GPS signal can be delayed due to both the dry and wet components of the
troposphere. Most GPS processing includes models to account for the dry component of the
troposphere. However, it is difficult to model the wet component given its greater variability
and estimating the wet delay as part of the overall baseline estimation process is the best
approach.
Over longer baselines (say 100km or more) it is typical for many hours of GPS data to be
observed and the high level of redundant data allows for the tropospheric delay to be
estimated at regular intervals through the data set (e.g. one delay each hour). For such long
baselines, ignoring the tropospheric delay can cause a height error of several centimetres
(see, for example, Dodson et al, 1996).
For many day to day surveys, the baselines are typically quite short and the effect of the
troposphere is less significant. Also the data observation times are short meaning that less
data is available to estimate the delay even if it were significant. Generally speaking, such
surveys can simply use the software model for the dry component and the remaining effect
will not be significant. However, it should also be noted that the tropospheric effect could be
significant when there is a significant change in height between the ends of the baseline. For
steep baselines, even when relatively short, there may be situations where longer observation
time and estimating the delay may be warranted.
Tidal phenomena may be significant for GPS heighting in certain circumstances. These
include the earth tide and the ocean tide’s variable loading of the crust in and adjacent to the
coastal zone. While not usually significant for day to day GPS surveying over short
baselines, there can be significant differential effects for baselines of 100km and longer;
amounting to centimetre level errors in height. Some software packages enable modeling of
these tidal effects for those situations when they are significant.
The other major source of error for GPS heighting involves the antenna. The first and most
obvious problem is that the height of the antenna above the survey mark must be correctly
measured. Many RTK systems use a pole for the roving antenna to decrease occupation time
compared to tripod usage. An advantage of this for heighting is that the fixed height of the
pole minimises the possibility of incorrect antenna heights. When variable height tripods are
used it is important to have a field routine for checking the height measurement at each
station. Use of a slant height (to the outside of the ground plane) and comparison to the
vertically measured height is a technique in common usage. Measurement in both metric and
imperial units is another approach.
A less obvious antenna issue arises when various antenna types are mixed in the same
survey. The problem with antenna mixing is that different antenna may have their effective
antenna phase centre (also called the electrical centre) in different positions. This effect can
be most significant in the height component and can reach values of several centimetres. The
International GPS for Geodynamics Service (IGS) has had to address this issue to account
for the many types of antennae used at its various permanent tracking stations. Antenna
models are available and they can be applied in some software packages to mitigate the
effects of antenna mixing (see Mader and MacKay, 1996).
Most GPS surveying applications use receivers and antennae that are all from the same
manufacturer and this problem is minimised. However, there may be situations where a
survey mixes antennae that have significantly different characteristics and surveyors need to
be aware of this issue. One situation where this could arise is when using data from a base
station run by another organisation. At present such a possibility is limited mainly to post
processed applications but the increasing popularity of RTK along with adoption of standard
RTK data formats is likely to lead to mixing of receiver and antenna types from different
manufacturers, even in RTK surveying. For such situations antenna modeling will need to be
addressed to ensure reliable height measurement.
Accuracy of GPS measurement for Height
Despite all of the issues outlined above, the bottom line for the practicing GPS surveyor is
what can be achieved using typical Rapid Static and RTK approaches? A pragmatic
approach to answering that question is to look at the accuracy claims of manufacturers. A
quick scan of product brochures or information on web sites of a number of manufacturers
led to the following:
· Leica state baseline rms values for their new SR530 for real time static of 5mm + 2ppm
and real time stop & go and kinematic of 10mm + 2ppm. No differentiation is made
between horizonatal and vertical accuracies.
· Ashtech produce a RTK system that uses both GPS and the Russian GLONASS systems
and measures single frequency data from both systems. The stated vertical accuracy for
the GG-RTK system is 1cm +1ppm at 1 sigma.
· Javad Positioning Systems make a general statement of 1mm + 1ppm for dual frequency
and 2mm + 2ppm for single frequency.
· Trimble gives a quite comprehensive outline in the data sheet for their 4800 GPS Total
Station product (summarised in the following Table). While not specifically stated, it
would appear that these are 1 sigma values. Note that the term fast static used by
Trimble and the term rapid static used in this paper are the same. Also note that for
RTK the stated accuracy varies according to the update rate used (1Hz is a rate of 1
update per second and 5Hz equals 5 per second).
Mode Accuracy Latency
Static and Fast Static 5mm + 1ppm Horizontal
10mm + 1ppm Vertical
Post processed kinematic 10mm + 2ppm Horizontal <10km
20mm + 1ppm Horizontal >10km
20mm + 1ppm Vertical
RTK at 1 Hz 10mm + 2ppm Horizontal 0.4 sec
20mm + 2ppm Vertical
RTK at 5 Hz 30mm + 2ppm Horizontal 0.1 sec
50mm + 2ppm Vertical
If one accepts these figures then the vertical accuracy possible for the types of GPS
surveying modes used in most day to day surveys are shown in the Tables below. The table
shows values in millimetres for baseline lengths of 1, 5 and 10km. As well as 1 sigma, the
table also shows 3 sigma values to give an indication of the worst results that may be
expected.
Mode mm + ppm Error in mm (1 sigma) Error in mm (3 sigma)
1km 5km 10km 1km 5km 10km
Fast Static 10 1 11 15 20 33 45 60
Kinematic 20 1 21 25 30 63 75 90
RTK 1 Hz 20 2 22 30 40 66 90 120
RTK 5 Hz 50 2 52 60 70 156 180 210
It must be remembered that the issues and accuracy values outlined in this section are only
for the GPS measurements. For day to day surveys over project areas less than 10km in
extent, the GPS measurement is often the least significant part of the GPS Heighting
problem.
Limitations due to Geoid Model
GPS surveying measures differences in ellipsoidal heights (h in Figure 1) and to produce
physically meaningful heights such as orthometric heights (H) there is a need for a
sufficiently precise model of the separation between the geoid and the ellipsoid; the geoid
height (N). Also, GPS surveying can measure that ellipsoidal height difference over large
distances very efficiently. These two points can highlight problems in the existing geoid
model or vertical datum, or both.
In some areas of the world the only available geoid model is a global geopotential model
(GGM). A GGM is typically computed as a series of spherical harmonic expansions to a
maximum degree and order. Many recent GGM use an expansion to degree and order 360.
That means they are able to resolve features in the geoid with a wavelength down to half a
degree (nominally 55km). With such resolution, even state of the art models such as the
Earth Geopotential Model 1996 (EGM96 - Lemoine et al, 1996) are limited to absolute
accuracy at the metre level and relative accuracy at the several decimetre level.
Topography
Ellipsoid
Geoid
H
h
N
Figure 1 Geoid Height
In many regions of the world, it is desirable to improve upon the accuracy possible using
only the GGM by computing a local geoid model. The model typically takes the form of a
grid of geoid heights to be interpolated by users as required. Local geoid models are derived
in two parts. The long wavelength component comes from the best available GGM while the
short wavelength component is computed using locally observed gravity data. The short
wavelength component of the geoid can be computed using several techniques, including
doing the integration directly (with quadratures or rings), least squares collocation or fast
fourier transform. Sunkel (1996) gives a summary of recent geoid developments in various
countries. Obviously, geoid height accuracy is strongly influenced by how well the gravity
data used in the computation represents the actual gravity field and recent improvements
include:
· use of satellite altimetry data for increasing gravity data density offshore,
· use of digital elevation model data (DEM) to account for terrain effects on the gravity
field,
· use of DEM data to reflect high frequency gravity field variations and improve the
gridding or interpolation of the raw gravity data.
The limiting factors for the inherent accuracy of a geoid model are the amount of variability
in the gravity field and in the terrain. A geoid model will typically be least accurate in areas
with rugged terrain and highly variable underlying geology.
However in applying a geoid model, its inherent accuracy is not the only limitation. How
well the geoid model can be used in conjunction with the existing vertical datum also
requires consideration.
Limitations due to Vertical Datum
The definition of the vertical datum in many areas of the world has often been localized with
realization through published orthometric or normal heights from local adjustment of
networks of spirit level, barometric and trigonometric heighting observations. Sometimes
multiple vertical datum developed with each propagating from a single point such as a tide
gauge. Some regional or national vertical datum have been developed by constraining the
adjustment of the leveling and heighting observations to the height of mean sea level at one
or more tide gauges.
In the realisation of the Australia Height Datum (AHD) for example, the adjustment of
97,320km of leveling was constrained to mean sea level at 30 tide gauges. Oceanographic
influences along with possible errors in the leveling mean that the surface formed by the base
of AHD could be distorted significantly from the purely geopotential surface of the geoid
(see for example Featherstone, 1998). In such cases a possible solution is to address the
problem at the level of the vertical datum by developing an appropriate model of the
distortion and adding it to the geoid model.
Whether or not such a distortion process has been incorporated into the geoid model, it is
prudent for the GPS survey to verify the agreement between the geoid model and the
vertical datum in a given project area. Occupying at least three existing stations with vertical
datum height values as part of the GPS survey can do this. If there is some residual local
distortion it can be removed as part of the process of adjusting the survey.
Another issue for modern vertical datum is the need to refine our information management
in relation to heights. Prior to GPS, most geodetic databases typically stored only an
orthometric (or normal) height for a station because that was the typical form for height
observations. With GPS, vertical datum will increasingly be made up of stations at which
heights are observed directly as orthometric heights and others at which ellipsoidal heights
are observed. There is also a need to treat a geoid height like any other observation type in
that it is of a particular quality at a particular time. Without careful management of these
different data types any problems can blur into one another and make maintenance and
improvement of the vertical datum difficult.
In practice, GPS heighting typically involves measuring ellipsoidal heights with GPS,
applying some form of geoid model and making any adjustment to fit the resulting
orthometric heights to the existing vertical datum. Therefore, in examining the limitations of
GPS heighting it is necessary to consider three broad areas:
· limitations of the GPS measurement
· limitations due to the available geoid model
· limitations due to vertical datum issues
Some or all of these issues vary in importance depending on the overall extent of the GPS
survey in question. GPS surveys over national and continental scale are typically associated
with datum level geodetic operations and need to consider many more issues than day to day
surveys which extend over a few kilometres or less. In considering limitations to GPS
heighting, this paper will attempt to highlight when the scale of the project is relevant.
Limitations of the GPS measurement
Obviously, the first limitation in GPS heighting is the quality of the GPS solutions used to
obtain a height. Three broad categories of GPS observation types are possible:
· Point Positioning which is the stand alone navigation mode for which GPS was
designed;
· Differential GPS (DGPS) which uses a differential correction approach but which is
primarily based on pseudo range measurements and
· GPS Surveying using a differential approach but primarily based on measurement of
the phase of the GPS signals.
While DGPS and even Point Positioning may be useful for producing heights in certain
applications, the term GPS Heighting is typically taken to refer to the use of phase
measurement techniques that can be grouped under the broad heading of GPS Surveying.
This paper concentrates on heighting using these higher precision GPS Surveying
techniques.
Within GPS Surveying, an overall consideration is whether the phase ambiguities have been
resolved to integer values. Ambiguity resolution affects all three dimensions, not only height.
For the measurement techniques known as Rapid Static and Real Time Kinematic (RTK),
which are used for shorter baselines, ambiguity resolution is a prerequisite and should be
achieved for most day to day GPS surveying applications. It is important to realise that RTK
uses the smallest possible amount of data and even the best algorithms sometimes resolve
the ambiguities incorrectly. To avoid such errors, which can reach the metre level, it is
important to build redundancy into a survey by, for example, occupying stations more than
once.
Two aspects that can affect the overall quality of the baseline solution are errors in the
ephemeris or in the starting coordinates used in the processing. The effect of these can reach
several parts per million and apply to all three dimensions. Assuming that the broadcast
ephemeris quality remains as high as in recent times, its effect will be minimal for most
applications over short baselines. However, it should be noted that obtaining a WGS84
three-dimensional starting position of a reasonable quality (say +/- 10m or better) could be
more problematic in some areas of the world.
Another error source to consider is multi-path. Reflective surfaces can mean that some of
the signal reaching the antenna does not travel on a direct path from the satellite. The effects
of multi-path can reach the decimetre level in three dimensions. Observation over time to
allow the satellite geometry to change sufficiently enables the effect of multi-path to be
reduced through averaging. However, with the short observation times typical of the Rapid
Static and RTK techniques in common use, it is necessary to pay attention to this issue.
While modern hardware and software designs include various ways of reducing the effects of
multi-path, even over short observation times, it is important to choose stations so as to
reduce the likelihood of multi-path and build redundancy into the survey to enable detection
of any remaining effect.
Atmospheric delay is another issue to be considered. For a short baseline one can reasonably
assume that the radio signals measured by both receivers pass through the same part of the
atmosphere. However, as baseline length increases that assumption begins to break down
and atmospheric effects need more consideration. Two components of the atmosphere are
relevant, the ionosphere and the troposphere.
Problems due to the upper atmospheric layer known as the ionosphere can affect all three
dimensions and become significant on lines longer than, say 20km. For such longer baselines,
processing software is able to take advantage of the fact that the ionospheric effect is related
to the frequency of the signal and dual frequency measurements can be used to remove most
of the effect. The effect of the ionosphere is greater near the poles and the geomagnetic
equator and varies over time in association with solar disturbance cycles. Therefore, it
should be noted that for certain areas and certain times the ionospheric effect can be
significant, even over short baselines.
The effect of the troposphere is particularly significant for height measurement. Unlike the
ionosphere, tropospheric delay cannot be mitigated using dual frequency measurement.
Furthermore, the GPS signal can be delayed due to both the dry and wet components of the
troposphere. Most GPS processing includes models to account for the dry component of the
troposphere. However, it is difficult to model the wet component given its greater variability
and estimating the wet delay as part of the overall baseline estimation process is the best
approach.
Over longer baselines (say 100km or more) it is typical for many hours of GPS data to be
observed and the high level of redundant data allows for the tropospheric delay to be
estimated at regular intervals through the data set (e.g. one delay each hour). For such long
baselines, ignoring the tropospheric delay can cause a height error of several centimetres
(see, for example, Dodson et al, 1996).
For many day to day surveys, the baselines are typically quite short and the effect of the
troposphere is less significant. Also the data observation times are short meaning that less
data is available to estimate the delay even if it were significant. Generally speaking, such
surveys can simply use the software model for the dry component and the remaining effect
will not be significant. However, it should also be noted that the tropospheric effect could be
significant when there is a significant change in height between the ends of the baseline. For
steep baselines, even when relatively short, there may be situations where longer observation
time and estimating the delay may be warranted.
Tidal phenomena may be significant for GPS heighting in certain circumstances. These
include the earth tide and the ocean tide’s variable loading of the crust in and adjacent to the
coastal zone. While not usually significant for day to day GPS surveying over short
baselines, there can be significant differential effects for baselines of 100km and longer;
amounting to centimetre level errors in height. Some software packages enable modeling of
these tidal effects for those situations when they are significant.
The other major source of error for GPS heighting involves the antenna. The first and most
obvious problem is that the height of the antenna above the survey mark must be correctly
measured. Many RTK systems use a pole for the roving antenna to decrease occupation time
compared to tripod usage. An advantage of this for heighting is that the fixed height of the
pole minimises the possibility of incorrect antenna heights. When variable height tripods are
used it is important to have a field routine for checking the height measurement at each
station. Use of a slant height (to the outside of the ground plane) and comparison to the
vertically measured height is a technique in common usage. Measurement in both metric and
imperial units is another approach.
A less obvious antenna issue arises when various antenna types are mixed in the same
survey. The problem with antenna mixing is that different antenna may have their effective
antenna phase centre (also called the electrical centre) in different positions. This effect can
be most significant in the height component and can reach values of several centimetres. The
International GPS for Geodynamics Service (IGS) has had to address this issue to account
for the many types of antennae used at its various permanent tracking stations. Antenna
models are available and they can be applied in some software packages to mitigate the
effects of antenna mixing (see Mader and MacKay, 1996).
Most GPS surveying applications use receivers and antennae that are all from the same
manufacturer and this problem is minimised. However, there may be situations where a
survey mixes antennae that have significantly different characteristics and surveyors need to
be aware of this issue. One situation where this could arise is when using data from a base
station run by another organisation. At present such a possibility is limited mainly to post
processed applications but the increasing popularity of RTK along with adoption of standard
RTK data formats is likely to lead to mixing of receiver and antenna types from different
manufacturers, even in RTK surveying. For such situations antenna modeling will need to be
addressed to ensure reliable height measurement.
Accuracy of GPS measurement for Height
Despite all of the issues outlined above, the bottom line for the practicing GPS surveyor is
what can be achieved using typical Rapid Static and RTK approaches? A pragmatic
approach to answering that question is to look at the accuracy claims of manufacturers. A
quick scan of product brochures or information on web sites of a number of manufacturers
led to the following:
· Leica state baseline rms values for their new SR530 for real time static of 5mm + 2ppm
and real time stop & go and kinematic of 10mm + 2ppm. No differentiation is made
between horizonatal and vertical accuracies.
· Ashtech produce a RTK system that uses both GPS and the Russian GLONASS systems
and measures single frequency data from both systems. The stated vertical accuracy for
the GG-RTK system is 1cm +1ppm at 1 sigma.
· Javad Positioning Systems make a general statement of 1mm + 1ppm for dual frequency
and 2mm + 2ppm for single frequency.
· Trimble gives a quite comprehensive outline in the data sheet for their 4800 GPS Total
Station product (summarised in the following Table). While not specifically stated, it
would appear that these are 1 sigma values. Note that the term fast static used by
Trimble and the term rapid static used in this paper are the same. Also note that for
RTK the stated accuracy varies according to the update rate used (1Hz is a rate of 1
update per second and 5Hz equals 5 per second).
Mode Accuracy Latency
Static and Fast Static 5mm + 1ppm Horizontal
10mm + 1ppm Vertical
Post processed kinematic 10mm + 2ppm Horizontal <10km
20mm + 1ppm Horizontal >10km
20mm + 1ppm Vertical
RTK at 1 Hz 10mm + 2ppm Horizontal 0.4 sec
20mm + 2ppm Vertical
RTK at 5 Hz 30mm + 2ppm Horizontal 0.1 sec
50mm + 2ppm Vertical
If one accepts these figures then the vertical accuracy possible for the types of GPS
surveying modes used in most day to day surveys are shown in the Tables below. The table
shows values in millimetres for baseline lengths of 1, 5 and 10km. As well as 1 sigma, the
table also shows 3 sigma values to give an indication of the worst results that may be
expected.
Mode mm + ppm Error in mm (1 sigma) Error in mm (3 sigma)
1km 5km 10km 1km 5km 10km
Fast Static 10 1 11 15 20 33 45 60
Kinematic 20 1 21 25 30 63 75 90
RTK 1 Hz 20 2 22 30 40 66 90 120
RTK 5 Hz 50 2 52 60 70 156 180 210
It must be remembered that the issues and accuracy values outlined in this section are only
for the GPS measurements. For day to day surveys over project areas less than 10km in
extent, the GPS measurement is often the least significant part of the GPS Heighting
problem.
Limitations due to Geoid Model
GPS surveying measures differences in ellipsoidal heights (h in Figure 1) and to produce
physically meaningful heights such as orthometric heights (H) there is a need for a
sufficiently precise model of the separation between the geoid and the ellipsoid; the geoid
height (N). Also, GPS surveying can measure that ellipsoidal height difference over large
distances very efficiently. These two points can highlight problems in the existing geoid
model or vertical datum, or both.
In some areas of the world the only available geoid model is a global geopotential model
(GGM). A GGM is typically computed as a series of spherical harmonic expansions to a
maximum degree and order. Many recent GGM use an expansion to degree and order 360.
That means they are able to resolve features in the geoid with a wavelength down to half a
degree (nominally 55km). With such resolution, even state of the art models such as the
Earth Geopotential Model 1996 (EGM96 - Lemoine et al, 1996) are limited to absolute
accuracy at the metre level and relative accuracy at the several decimetre level.
Topography
Ellipsoid
Geoid
H
h
N
Figure 1 Geoid Height
In many regions of the world, it is desirable to improve upon the accuracy possible using
only the GGM by computing a local geoid model. The model typically takes the form of a
grid of geoid heights to be interpolated by users as required. Local geoid models are derived
in two parts. The long wavelength component comes from the best available GGM while the
short wavelength component is computed using locally observed gravity data. The short
wavelength component of the geoid can be computed using several techniques, including
doing the integration directly (with quadratures or rings), least squares collocation or fast
fourier transform. Sunkel (1996) gives a summary of recent geoid developments in various
countries. Obviously, geoid height accuracy is strongly influenced by how well the gravity
data used in the computation represents the actual gravity field and recent improvements
include:
· use of satellite altimetry data for increasing gravity data density offshore,
· use of digital elevation model data (DEM) to account for terrain effects on the gravity
field,
· use of DEM data to reflect high frequency gravity field variations and improve the
gridding or interpolation of the raw gravity data.
The limiting factors for the inherent accuracy of a geoid model are the amount of variability
in the gravity field and in the terrain. A geoid model will typically be least accurate in areas
with rugged terrain and highly variable underlying geology.
However in applying a geoid model, its inherent accuracy is not the only limitation. How
well the geoid model can be used in conjunction with the existing vertical datum also
requires consideration.
Limitations due to Vertical Datum
The definition of the vertical datum in many areas of the world has often been localized with
realization through published orthometric or normal heights from local adjustment of
networks of spirit level, barometric and trigonometric heighting observations. Sometimes
multiple vertical datum developed with each propagating from a single point such as a tide
gauge. Some regional or national vertical datum have been developed by constraining the
adjustment of the leveling and heighting observations to the height of mean sea level at one
or more tide gauges.
In the realisation of the Australia Height Datum (AHD) for example, the adjustment of
97,320km of leveling was constrained to mean sea level at 30 tide gauges. Oceanographic
influences along with possible errors in the leveling mean that the surface formed by the base
of AHD could be distorted significantly from the purely geopotential surface of the geoid
(see for example Featherstone, 1998). In such cases a possible solution is to address the
problem at the level of the vertical datum by developing an appropriate model of the
distortion and adding it to the geoid model.
Whether or not such a distortion process has been incorporated into the geoid model, it is
prudent for the GPS survey to verify the agreement between the geoid model and the
vertical datum in a given project area. Occupying at least three existing stations with vertical
datum height values as part of the GPS survey can do this. If there is some residual local
distortion it can be removed as part of the process of adjusting the survey.
Another issue for modern vertical datum is the need to refine our information management
in relation to heights. Prior to GPS, most geodetic databases typically stored only an
orthometric (or normal) height for a station because that was the typical form for height
observations. With GPS, vertical datum will increasingly be made up of stations at which
heights are observed directly as orthometric heights and others at which ellipsoidal heights
are observed. There is also a need to treat a geoid height like any other observation type in
that it is of a particular quality at a particular time. Without careful management of these
different data types any problems can blur into one another and make maintenance and
improvement of the vertical datum difficult.
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