Geographic Information System Development
for the
Water Division of the City of Cleveland
by
The Northern Ohio Data and Information Service
(NODIS)
Maxine Goodman Levin College of Urban Affairs
Cleveland State University
NODIS Responsibilities
As a subcontractor to Metcalf & Eddy, an engineering consulting
company, NODIS lead the two year development of an advanced
Geographic Information System (GIS) for hydraulic modeling and
other GIS applications for the City of Cleveland Water Division
(CWD). NODIS was responsible for evaluating and recommending
GIS software and geographic databases (including the base map),
GIS database design, management of the digital conversion of
water distribution infrastructure maps, some specialized tool
applications development, selected database enhancements, and
GIS software training.
Project Description:
The Division serves a population of 2.3 million persons and over
400,000 customer accounts with over 5,300 miles of pipes and
appurtenances, 4 water treatment plants, 17 secondary pumping
stations, and 13 primary and 75 secondary pressure zones.
Environmental Systems Research Institute (ESRI) GIS software
was selected for the project. Base maps include the county’s
digital orthophotography, associated planimetry, and cadastral
databases. The infrastructure database includes water mains,
valves, hydrants, and other water distribution facilities. The GIS
database (managed by ESRI’s SDE database software) interfaces
with an Oracle database and provides input to the hydraulic,
surge, and water quality models, as well as mapping of model
results. The project required very significant enhancement to the
water distribution model and tools provided by the ArcGIS
software system.
Base Map Layers & Other Data Layers:
Description
Origin or Source
Accuracy
Planimetric Base Map
Developed
from March,
Orthophotographs
1,132
Planimetric
Files1993
forDigital
each layer
Files acquired from Cuyahoga County Engineer’s Office
Methodology
to Convert:
Scale 1” = 200’
1,132 Digital Files
Translate each file from AutoCAD
drawing file to ArcInfo format
Append each file to create ONE seamless
coverage for the each of the 9 planimetric layers
Create the Cleveland Regional Geodetic Survey (CRGS)
projection
Planimetric Base Map:
Railroad
Bridge
Curbs
Tree
Highway
Waterway
Recreation
Building Footprints Area
Retention Wall
Each data layer is seamless with a geographical coverage of Cuyahoga
County and approximately 2 miles outside the county extents.
Accuracy of Planimetric Data
Approximately ± 5 feet in positional accuracy from the
1” to 200’ scale orthophotography
An additional ± 2 feet after defining the CRGS
projection, a local projection, based on known control
points
Missing any changes between March 1993 and the present
such as new subdivision development or building
demolition, etc.
Cadastral Base Map
Comprised of Parcel Properties
Seamless Parcel Polygon Data Layer
Geographic Coverage- all Cuyahoga (1994) and Medina County (1999),
northern portion of Summit County (2000)
Cadastral Accuracy
In Cuyahoga County:
Parcel layer current to November 1994.
Parcel splits or combinations since November 1994
are not present.
In general, the parcel layer is relatively spatially
accurate compared to the planimetrics.
However, there are many occurrences in which
parcels are less spatially accurate.
Planimetric curb
has higher degree
of spatial accuracy
Some groups of
parcels required
moving to conform
to the planimetric
curb.
Improving Cadastral Accuracy
GOAL:
To increase the relative positional accuracy of parcels to the
planimetric curbs
APPROACH:
Accomplished through moving blocks of parcels and trimming
parcels where appropriate
RESULT:
Relative location of parcels and aesthetic appearance was
improved


Facilitated the use of the “Connection Tool”
Moved and/or Trimmed Parcels
Example: red parcels
intersect the curb
on northern end.
They are moved as a
group to conform to
the curb layer.
Moved and/or Trimmed Parcels
BEFORE
AFTER
Parcel Adjustment Statistics
Total number of parcels
499,027
Parcels moved or centered in relation
to curb
120,538
24%
Parcels trimmed 2 feet from curb
4,643
0.9%
Summary: Planimetric and Cadastral Layers
Planimetric layer has highest spatial accuracy
Parcels were adjusted, where necessary, to planimetric
Relative accuracy levels are acceptable for the hydraulic
modeling project and other water department
applications
Recently developed areas since 1993 (planimetrics) and
1994 (parcels) have undergone change and need to be
updated.
Summit and Medina Counties both required the creation
of a pseudo-curb layer.
Other Land Base Data Layers –
Triangulated Irregular Network (TIN), Cuyahoga County, 1993
Developed from the Digital Elevation Model
(DEM) data acquired from the Cuyahoga County
Engineer’s Office
DEM files created from the orthophotos in
CRGS coordinate system
From the DEM elevation mass points and
breaklines, TIN was created using the linear
bivariate method
TIN was re-projected to U.S. State Plane
(NAD83) feet
Large file size of 826 MB
Triangulated Irregular Network
As the TIN contains
the elevations of
each corner,
calculations can be
made to find the
elevation of any
point within the
triangle.
955.895
936.985
945.876
942.133
Accuracy of TIN Data
Positional Accuracy similar to Planimetrics: approximately ± 5 feet
90% of selected TIN elevation values were within ± ½ foot of spot
elevation value from planimetrics
(elevation difference due to differences between linear
bivariate method and the quintic method)
Combined TIN for Medina and Summit Counties
Developed from United States Geological Survey (USGS)
7.5 ‘ quadrangles
Locational errors can be up to 200 feet
Other Land Base Data Layers
Modified street centerline file:
For Cuyahoga County:
Source is 1997 TIGER street centerline file from Census Bureau
Conflated to fit within planimetric curb
For other 6 surrounding counties:
2000 TIGER street files were appended to 1 street file
Positional accuracy at any point can be ±200 foot
TIGER
Modified
TIGER
Other Land Base Data Layers
Traffic Analysis Zones (TAZ)
Zones developed by NOACA and AMATS for Census Bureau
Attribute data population values and estimates 1990 to 2025
Waterways
2000 TIGER Census Bureau waterways for 7 counties
City Borders
Based on planimetric and parcel layers for Cuyahoga, Medina, and
Summit Counties. Other 4 counties are based on 2000 TIGER files
Landuse
Based on Ohio Department of Natural Resources (ODNR) landuse
maps from 1976 to 1985 for 7 counties.
Appended to 1 landuse data layer
Other Land Base Data Layers
Zoning
1997 zoning developed for NOACA
5 county zoning coverage- Cuyahoga, Lake, Geauga, Lorain, & Medina
Appended to 1 zoning data layer
TIGER level accuracy
Wards
2001 political voting wards for City of Cleveland
Conflated to planimetric/ parcel layers
Telephone Area Codes and Postal Zip Codes
Covers 7 counties
TIGER level accuracy
Populating the Database
Methods
Fit to base map
Populating Methods
Digitizing 113 section sheet maps at 1” = 400’ scale
113 section sheets scanned to create raster image
Water features digitized from image using AutoCAD
AutoCAD .dwg files converted to GIS format- ESRI
shapefiles
CWD Section Sheet Index Map
Populating Methods
Captured Features:
PIPE
Hydrants
Valves
Description:
Line feature with
diameter
Point
Point feature
features
attribute.
1 pipe
at
with
insertion
status
segment defined
along
attribute.
pipe.
as pipe
Hydrant
Types
are
type
intersection
to
and
system,
control,
pipe direction
intersection,
or
tocaptured.
diameter
also
and
flush
pipe
change.
valves.
Example of Section Sheet
Status: closed
or open.
Populating Methods
- Features
Schematic Drawings
Scales Vary from 1” = 5’ to 1” = 100’
Captured from Facility Maps:
Fittings
(Point
Features)
Valve
(Point
Features)
Facility
(Point
Feature)
Pump,
Pump
Motor,
Pipe (Line
Feature)
Venturi,
Master
Meter
Pump
Station,
Reservoir,
Tower,
Created
at
pipe
segment
Drain,
check,
pump
Contains
Diameter
Surge
Tank,
Vault, Maintenance
(Point
Features)
ends
andair,
when
diameter
control,
control,
Attribute
or
Treatment
Plant
changes
flush,
or air cock.
Populating Methods - Feature Attribute Population
Pipe Type attribute values were populated using spatial & attribute queries:
Yes
Trunk Main
Yes
Diameter >= 20”
No
Yes
Intersect a
Trunk Main
No
Length < 400’
Yes
No
Supplemental Connection
Distribution Main
Distribution Main
Hydrant
Attached
No
Circulation Main
Populating Methods
Detailed drawings of trunk mains were used to populate
the locations of the following point features:






Air cocks
Access manholes
Automatic air valves
Drain valves
Electrolysis test stations
Pitometers
Attributes recorded- size, manufacturer, class, pressure
rating, internal coating, material, and year installed
Populating Methods
Populate connections:
Using the custom connection tool, a connection line, fitting,
meter, and curb stop is generated for each water customer to
the associated parcel.
Multiple connections to a parcel can exist
From the customer billing database, customers linked to a
parcel by:
Matching ppn in billing to ppn in parcel database or
Matching address in billing to address in parcel database
A connection is generated when parcel PPN or address matches
billing database
Populating Methods
– Single and Multiple Connections
Connections consist of the following:
Connection Line
•Drawn perpendicular
from the closest
distribution or circulation
main toward the parcel
centroid.
•Terminates 6 feet inside
the parcel frontage.
•Multiple connections to a
customer parcel
generated where
applicable
Curb Stop
Fitting
•Point Feature
•Created at the
junction of a pipe and
connection.
•Point Feature
•Created and placed 3
feet outside the street
pavement.
Meter
•Point Feature
•Created and placed 5
feet inside the parcel
frontage.
Populating Methods
Populate installation date of distribution & circulation mains:
Based on connection date and hydrant type
Connection features are linked to pipe features.
Oldest connection date is determined (based on connection number).
Hydrant features are linked to pipe features.
Ear or no ear hydrants are determined from hydrant type.
NO EARS
EARS
If pipe has oldest connection prior to 1955 (with or without
hydrant ears):
Installation date is the oldest connection on the pipe
If pipe has oldest connection after 1955 & hydrants without ears:
Installation date is 1955
If pipe with oldest connection after 1955 & hydrants with ears:
Installation date is the oldest connection on the pipe
Populating Methods
Populate pipe cleaning and lining data:
Used Paradox cleaning & lining database from CWD
Identified pipes that correspond to cleaning & lining records
Generated/ updated cleaning & lining fields in geodatabase related
table
Populate control valve settings & diameter:
Used regulator database from CWD
Settings and diameters fields updated to control valve feature
Populate pumps & storage units:
Pump curve data provided by CWD linked and updated to pump table
Storage unit shapes also provided by CWD and linked to storage units
Checking Network Connectivity
All point features snapped (snap tolerance of 1/10 foot) to pipe.
The snapping was performed while digitizing in AutoCAD as well as
snapping features when creating the geodatabase.
To ensure network connectivity:
If there was a missing point feature present at pipe ends (when
creating the water network), a network junction was generated.
The missing point feature (replacing the network junction) was
added to the network.
A network connectivity tool was also used to ensure that all
features were in the geodatabase network.
Statistics
Schema size:
Tables
Attributes
Relationships
Domains
Subtypes
223
3,293
230
70
12
Pipes: 53,223 pipe segments;
5,237 miles
Trunk main: 422 miles
Trunk main survey points:
11,291
Fittings: 342,611
Hydrants: 70,879
System valves: 56,098
Flush Pipes: 1,301
Pumps: 100