ATTAINING FEATURE ACCURACY IN UTILITY ENGINEERING GIS
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http://gis.esri.com/library/userconf/proc01/professional/papers/pap522/p522.htm
ATTAINING FEATURE ACCURACY IN UTILITY ENGINEERING GIS
Swapan Nag, Lois Yoon and Ahmed Husain
ABSTRACT
Accuracy is a measure of quality of an engineering utility GIS
database. Schematic representation may suffice for small-scale maps
(1"=600' and smaller) and some system engineering modeling
applications, but large-scale engineering mapping (1"=100' and
larger) demands positional accuracy better than +2 feet. Stage-wise
implementation gives precedence to layers of higher accuracy. GPS
survey control, COGO cadastre input, aerial photography, analytical
aerial triangulation, digital terrain modeling, rectified digital ortho
photography, planimetry and topography is followed by precision digital
input of utility layers. The final product is analyzed in terms of
accuracy of different levels of base information utilized to reference
it.
POSITIONAL ACCURACY
This paper summarizes efforts to develop Utility GIS to meet stringent
engineering specifications, and the lessons learnt during the
implementation of utility projects at the City of Downey, California.
Municipal GIS has, until recently, focused mainly on a macro level of
spatial analysis, applicable to Planning and Development activities.
Engineering and Utility Management departments have adopted these
systems to some extent to monitor and track utility consumption in
network modeling applications that do not require a high precision of
facility location. Maps at this macro level are generally
representative or schematic. A reason for the reluctance to move
towards a micro-analytical capability has been the cost associated with
attaining high precision data. Municipalities have invested minimally
at initial stages of GIS development, until proof of concept has
justified higher levels of spending.
Macro scales of GIS mapping start from 1:2400 with positional accuracy
of 50 foot horizontally, and 25 foot vertically and up.
With the adoption of Global Positioning System (GPS) technology, the
cost of obtaining survey control has reduced dramatically, making
feasible the scope for attaining engineering accuracy within the GIS
environment. Accuracy is fundamental to acceptance of GIS as a viable
tool by Public Works and Engineering Departments within municipalities.
These departments have, until recently, shown a preference for
CAD-based systems tailored to meet their needs for graphic
manipulation, a capability required for the creation of maps that meet
engineering specification. Attribute information has been represented
as annotation, with the analytical capability remaining largely
un-harnessed. These systems have served the general purpose of
replacing, to some extent, the maintenance of hardcopy maps by the
departments concerned.
If Utility GIS is to replace current engineering systems, every piece
of information available on hard copy engineering as-built records must
be transferred into an attribute format within the GIS. It is
imperative also for graphic representation within the GIS to reflect
the same accuracy as the hardcopy record. The need to automate
applications to support decision making, manage infrastructure and to
administer asset inventory and maintenance of utility systems make it
imperative for productivity to be increased through the use of spatial
database management systems. GIS has to evolve as a centralized
repository of all engineering information that can be easily accessed
and manipulated to provide information to the user as needed.
Although the scanned source map can be made available digitally through
a hot-link within the GIS environment, it's reference will,
hopefully, gradually recede once engineering staff become familiar with
the much more "intelligent" information available within the GIS.
Engineering accuracy is generally related to three basic mapping
scales: 1:240, 1:480 and 1:1200 (in the metric system, this would
translate to 1:250, 1:500 and 1:1000 scale maps).
TABLE 1: ENGINEERING SCALE MAPS
Map Scale Horizontal Accuracy Vertical Accuracy Function
1:240
0.5'
0.25'
Site Specific Design
1:480
1.0'
0.50'
Utility Engineering Design
1:1200
2.5'
1.00'
Operations & Maintenance
1:2400
5.0'
2.50'
Planning
SURVEY CONTROL
In implementing utility GIS conversion projects, precedence in the work
process follows a path of degradation in accuracy. The highest order of
accuracy, the ground survey, establishes control for the entire process
to follow. Too often, GIS developers ignore this aspect of control,
only to find out later that they are unable to relate their data to
accurate positions in the real world. Fragmented control of GIS-related
operations within a municipality, if performed by different departments
in isolation, may not plan for different data layers to, some day, be
brought together on a common datum. Control is the means of
establishing a firm foundation for all data layers to subsequently be
cross-referenced.
At the City of Loma Linda, the aerial contractor was instructed to use
as much of the survey control established by the County of San
Bernardino Surveyor. These points were earlier used to control the
cadastral conversion of property information. As a result, the
registration between the COGO-ed land base and the planimetry compiled
by the aerial firm has remarkable coincidence. Where this simple means
of registration is not exercised, the two data sources can seldom be
brought together meaningfully.
At the City of Downey, the legacy land base showed major discrepancy
when cross-referenced to the more recent aerial mapping project. The
City established a tight control network of 850 GPS points located at
street intersections throughout the jurisdiction. Based on this
control, the accuracy of the original cadastre was determined to have a
root mean square error (RMSE) of 139.300', compared to an RMSE of
1.805' for the aerial planimetric data. Since the location of
utilities is largely defined in relation to street centerlines and
parcel boundaries, a major effort was involved in creation of street
centerlines using coordinate geometry (COGO) and in correcting the
parcel data based on right-of-way dimensions along the centerlines.
Figure 1: An example of GPS Control of Street Intersections
An example of GPS Control of Street Intersections
The GPS Intersection Index was utilized to register street centerlines
during the COGO process, and to serve as an error detection system for
quality control of the entire conversion process.
PHOTOGRAMMETRY
The City obtained digital ortho photography and curb and sidewalk
planimetry at 1:480 scale. On cross-referencing curb faces with the
street intersection GPS control, a relative accuracy of 1.805 foot was
determined. This was much higher than the 0.5-foot accuracy specified
for capture of planimetric features. . Photogrammetric standards for
this map scale specify a "limiting rms-error" of 0.4 foot in either the
X- or Y- direction for "well-defined" features (that is, 90% of
"well-defined" features compiled should be within 0.4 foot of their
correct position in either cardinal direction). Compared to the
extrapolated GPS intersections, limiting rms errors of 1.370 foot in
the X- and 1.175 foot in the Y-direction was observed for a 45 randomly
selected points checked. These extrapolated values cannot be
interpreted as "well-defined" in any sense of the term; so the above
RMSE observation does not refer to a standard measure of
photogrammetric accuracy. Instead, it was a measure of the accuracy of
data extrapolated from the planimetric features for the purpose of
locating utilities.
DIGITAL ORTHO PHOTOGRAPHY
While no analysis of the accuracy of the digital ortho photography was
conducted during this study, our expectation was that selection of
features off the digital ortho map would be an order less reliable than
the planimetric data. Digital ortho photographs are rectified by a
digital terrain model (DTM). Unless the DTM is prepared to standards of
photogrammetric map accuracy suitable for the creation of topographic
data, utilization of the digital ortho photograph for registration of
utility features is not recommended.
Figure 2: Digital Ortho Photography referenced to Sewer Facilities
Digital Ortho Photography referenced to Sewer Facilities
CENTERLINE COGO
GPS street intersection coordinates were used as a starting point for
COGO location of street centerlines. 118 parcel maps, 73 records of
survey and 681 tract maps were sourced to produce the street centerline
coverage. Star*net was used to COGO the centerlines.
Figure 3: COGO-ed Street Centerlines, GPS Control and Planimetric Curbs
with Star*net's Error Residual Report
COGO-ed Street Centerlines, GPS Control and Planimetric Curbs with
Star*net's Error Residual Report
An RMSE of 0.546 and 1.330 foot was observed in X- and Y-directions
respectively for the COGO-ed centerlines when compared back to the GPS
control.
PARCEL BASE AND RELATED LAYERS
The legacy parcel data registered to the California State Plane North
American Datum (NAD) 1927 was projected onto the NAD83 Coordinate
Datum, and rectified against GPS control as a single entity. Positional
error was analyzed against the GPS control before any further
correction of the legacy data was performed. An RMSE of 86.014 foot in
the X- and 109.572 foot in the Y-direction was observed.
Figure 4 is a display of the parcel boundaries cross-referenced to GPS
control, street curbing and final position of the parcel data after
corrections were performed. Error conditions are seen to vary
substantially throughout the area, a consistent finding throughout this
operation. Each City block was individually registered utilizing GPS
control, street centerlines, rights-of-way, curbs and sidewalks to
produce the final parcel layout (shown as blue on the map). Care was
taken not to distort parcel shapes.
Figure 4: Legacy parcels cross-referenced to GPS control, centerlines,
curbs and corrected parcels
Legacy parcels cross-referenced to GPS control, centerlines, curbs and
corrected parcels
Source attributes were then conflated back into the rectified coverage.
This operation was repeated for each of several layers of information
provided by the City. Accuracy of the final parcel base was determined
to be 2.069 and 1.586 foot in the X- and Y-directions.
STORM DRAIN SYSTEM
For the Storm system, mains and laterals were precision input using
centerline offsets to locate the pipes. Graphic representation
reflected exact lengths of facilities specified on the source. Where
necessary, distances were measured off the source documents if
annotation for offset distance or length were missing.
Direction of digitizing reflected upstream to downstream flow. This was
validated against invert elevation attributes. Although the facilities
were located too sparsely for statistical validity against randomly
selected GPS locations for the project as a whole, the location is
expected to be relatively accurate as large-scale source maps were
available for the conversion.
Figure 5: An example of a Storm Drain Facility Map
An example of a Storm Drain Facility Map
WATER DISTRIBUTION SYSTEM
Water source maps were not as accurate. 1"=100' scale water base maps
were provided. Pipes were precision input as were valves and fire
hydrants (from offset locations provided by the Fire Department). Most
offsets were measured off parcel boundaries, and the accuracy (or lack
thereof) played a role in limiting positional accuracy of water
facilities. The source maps, at best, were of 2-foot accuracy and the
parcels 2.607-foot. Limiting RMSE for the finished water facilities was
determined to be 1.548 foot in the X- and 2.064 foot in the
Y-coordinate directions. The fact that the accuracy of the water
facility slightly improved upon the parcel accuracy may be attributed
to several large-scale as-built maps those were available for some
newer development areas that were used. However, the error is
approximately of the same order, as may be expected.
Figure 6: An example of a Water Facility Map
An example of a Water Facility Map
SANITARY SEWER SYSTEM
The sanitary sewer system posed the biggest challenge. Approximately
3,600 source as-built maps were converted (compared to 545 storm drain
maps and 498 water base maps). An automated application in C++ was
developed for data entry. The programs generated precision graphics of
mains and laterals appropriately identified and associated with their
attributes. The program used stationing to create the graphics.
Redundancy in data entry was substantially reduced, as were errors. The
automated process is validated by the high levels of accuracy attained:
limiting RMSE values of 0.257 foot and 0.351 foot were determined when
sewer facilities were statistically referenced against GPS control.
Figure 7: An example of a Sanitary Sewer Facility Map
An example of a Sanitary Sewer Facility Map
TABLE 2: COMPARATIVE LAYER ACCURACY
Layer
X-RMSE Y-RMSE Error Tolerance
Planimetry
1.175
1.370
+1.805
COGO-ed Street Centerlines
1.330
0.546
+1.438
Legacy Parcel Base
86.014
109.572
+139.300
Adjusted Parcel Base
1.586
2.069
+2.607
Water System
1.548
2.064
+2.580
Sanitary Sewer System
0.257
0.351
+0.435
CONCLUSION
*
The data conversion product is, at best, as good as its source.
*
High order survey control must serve as a common foundation to
every GIS layer added to the system.
*
Accuracy will degrade as you move downstream in the conversion
process, so it is important to establish precedence in operational
methodology.
*
Digital ortho will not serve to meet engineering specification.
Even stereo-compiled data is suspect unless every manhole is targeted,
which may prove to be an expensive option. Accuracy specifications
provided by aerial contractors apply to "well-defined" features
compiled by them.
*
Parcel land base must be COGO-ed to achieve engineering accuracy.
The COGO process is often criticized for the cost incurred and the time
it takes to convert parcel data. However, this method is the only
technical option that will ultimately serve to meet engineering
specification.
*
For accurate location of facilities, precision input is a must.
Schematic representation will serve only macro analysis. Engineering
demands accuracy at least to the extent that is presently available on
hard copy.
*
Automated precision input is a trend of the future. The resulting
accuracy meets the most stringent engineering specifications.
Swapan Nag (B.Sc., B.Tech., M.B.A.)
President
Engineering Systems
355 South Grand Avenue, Suite 3292
Los Angeles, CA 90071-1560
Tel: 213.625.7636 x15
Fax: 213.625.3824
swapa...@engineeringsys.com,