Download Data Quality Control in Multi-State, Multi-year, Multi-type Databases: A Method for Examining Year-to-Year Percentage Changes

Data Quality Control in Multi-State, Multi-year, Multi-type Databases: A Method for Examining Year-toYear Percentage Changes
Li wan Chen, LENDIS Corporation, McLean, VA
Forrest Council, Highway Safety Research Center, University of North Carolina
ABSTRACT
The Highway Safety Information System (HSIS) is a
multi-state, multi-year, and multi-type database that
contains accident, roadway inventory, and traffic
volume data from eight states. HSIS contains
approximately a million observations of information
per state per year. The ultimate use of these data is in
data analyses across states, file types, and years.
However, from a quality-control standpoint, one of the
challenges is the monitoring of data changes in each of
the hundreds of variables each year to detect possible
errors of state-induced coding changes or data entry
errors leading to inconsistent data across years. Since
computer monitoring is mandated by the database size,
the effective use of the SAS macro facility could save
significant programming time for repetitive tasks. In
addition, it is easy to modify and maintain the
program. This presentation is to demonstrate the use of
a very limited number of macro language lines to
analyze year-to-year percentage changes for any state,
any two-year data, and any type of data in HSIS.
Specifically, the main program contains a few subroutines. The subroutines process the following tasks:
read in data, merge two-year data, calculate percentage
changes, set up the criterion, output the SAS format,
and printout the results for specific state, year, and
type of data.
INTRODUCTION
The HSIS is a relational database system. SAS/ACCESS
software is utilized as an interface between the SAS and
the Sybase database management systems [SAS/ACCESS
Software for Relational Databases: Reference.,1994] .
The HSIS stores the data – hundreds of variables per year
received from eight states [Council, F.M. and Williams,
C.D. ,1995;Council, F.M. and Williams, C.D., 1996].
Currently, there are four to more than ten different file
types (e.g., accident, vehicle, occupant, roadway
inventory, intersection inventory). Each file contains
one to more than ten years of information depending on
states and file types. It takes significant time and
repetitive effort to conduct a small set of data analyses
across states, file types, and years.
Part of the HSIS mission is to meet safety research
needs and provide research services to key federal, state,
and private officials who are making safety decisions.
Given the large database, it is necessary to understand the
trends or changes in variables across years to ensure that
the quality of the data remains at an acceptable level. To
meet this need, this quality control (QC) program is set up
to allow the analyst to access the Percentage Change (PC)
for a particular variable between any two years in the HSIS
databases. For the purpose of this presentation, the
examination of extreme values of PC in a variable defined
as “Average Annual Daily Traffic volume” (AADT) in the
‘ROAD’ file in ‘BB’ state is shown. The AADT is stored
for each “homogeneous section” of roadway, with the
section record defined by a beginning(BEGMP) and an
ending milepost(ENDMP) on a given route in a given
county(CNTYRTE).
Some of the key MACRO variables1 in the program are
listed as follows:
STATE
YEAR1
YEAR2
FILE
=
=
=
=
2-character state name.
the first year, i.e., 96
the second year, i.e., 97
file type, i.e., ROAD
The QC program consists of a main program and a few
external SAS files. The analyst is required to input a few
MACRO variables in the main program such as STATE,
YEAR1, YEAR2, and FILE. The above MACRO variables
are subsequently recognized as MACRO variables in the
computation, variable format, title statement, and file
recognition throughout the entire QC program, e.g., if
STATE=BB, any statement in the main program or
subroutines related to &STATE is identified as BB. Then,
the two-year data with SAS/ACCESS view descriptors are
read into the program. The RENAME procedure is
necessary at this data step because county route might
differ in different states. Given a county route, there are
11 possible types of roadway types (RODWYCLS), for
example, urban two-lane roads or rural two-lane roads. In
order to distinguish the different years of AADT, a
designation of “first” or “second” year is appended to
AADT. Then, the four subroutines are executed. The
interpretation of the subroutines is presented next.
Finally, part of the output is shown in the appendices.
1
SAS® MACRO languages could be applied in different ways
such as variables, parameters, iterative execution, function, or screen
control language [Carpenter, A. 1998]. In this QC program, SAS®
MACRO language is primarily used as MACRO variables or a list of
variables.
MAIN PROGRAM
/****************************************/
/* PURPOSE: QUALITY CONTROL PROGRAM
*/
/* USAGE:
AADT PERCENTAGE CHANGE(PC) */
/*
BETWEEN ANY TWO-YEAR
*/
/* PROGRAM NAME: BBMAIN20.SAS
*/
/* UPDATED DATE: 6-2000
*/
/****************************************/
/* INPUT STATE, YEARS, AND FILE TYPE */
%GLOBAL STATE YEAR1 YEAR2 FILE VIEW LIB;
%LET STATE=BB;
%LET YEAR1=92;
%LET YEAR2=94;
%LET FILE=ROAD;
%LET VIEW=VIEW;
%LET LIB="D:\SASDATA\&STATE\VIEW";
LIBNAME &STATE "D:\&STATE";
FILENAME PGM "D:\&STATE";
LIBNAME &STATE&VIEW &LIB;
/* READ IN DATA - VIEW DESCRIPTIVE */
DATA &STATE&YEAR1 (KEEP=RODWYCLS CNTYRTE BEGMP
ENDMP AADT&YEAR1);
SET &STATE&VIEW..&STATE&YEAR1&FILE;
RENAME AADT=AADT&YEAR1 CNTY_RTE=CNTYRTE;
RUN;
DATA &STATE&YEAR2 (KEEP=RODWYCLS CNTYRTE BEGMP
ENDMP AADT&YEAR2);
SET &STATE&VIEW..&STATE&YEAR2&FILE;
RENAME AADT=AADT&YEAR2 CNTY_RTE=CNTYRTE;
RUN;
/* CALCUATE PERCENTAGE DIFFERENCE BETWEEN 2
YEARS */
%INC PGM (PDIFF20);
/* SET UP THE CRITERION FOR OUTLIER */
%INC PGM (QC20);
/* OUTPUT VARIABLE FORMAT */
%INC PGM (FORMAT20);
/* OUTPUT THE NUMBER OF OUTLIERS AND PRINTOUT
THE EXTREME OUTLIER */
%INC PGM (RESULT20);
QUIT;
CALCULATING THE MEAN AND STANDARD
DEVIATION OF PC
There are different ways to assess change between any
two-time period, e.g., raw change (difference between
any two-year AADTs’), standardized change (dividing the
raw change by standard deviation), or PC (the percentage
of raw change divided by the first year AADT). The
AADT change is believed to be proportional to the first
year AADT, so the PC is used. We calculated means and
standard deviations of the PC within roadway
classification, since we felt that the critical difference
was within a given roadway type. This was because we
would expect major differences in the base variable
(AADT) between roadway class (e.g., Interstate road
sections would always have much higher average AADT’s
than rural two-lane roads).
Based on the above reasons, the first step of this
subroutine is to merge any 2-year data with roadway type,
county route, beginning milepost, and ending milepost
(different variables in the HSIS might need different
merged variables.). Then, calculate PC and attach the first
and second years to the PC (i.e., PDIFF9394 represents
PC from 1994 to 1993). List out the variables of the first
merged file. Output the mean (M&YEAR1&YEAR2) and
standard deviation (STD&YEAR1&YEAR2) of PC by
roadway types (by using PROC MEANS). The means and
standard deviations of PCs are then merged with the first
merged file.
/* FILENAME: PDIFF20 */
/* THE EXTERNAL CODE FILE: CALCULATE PC */
PROC SORT DATA=&STATE&YEAR1; BY RODWYCLS CNTYRTE
BEGMP ENDMP;RUN;
PROC SORT DATA=&STATE&YEAR2; BY RODWYCLS CNTYRTE
BEGMP ENDMP;RUN;
DATA AADT&YEAR1&YEAR2;
MERGE &STATE&YEAR1 &STATE&YEAR2;
BY RODWYCLS CNTYRTE BEGMP ENDMP;
RUN;
DATA AADT&YEAR1&YEAR2;
SET AADT&YEAR1&YEAR2;
IF AADT&YEAR1 = 0 THEN DELETE;
IF AADT&YEAR2 = 0 THEN DELETE;
IF AADT&YEAR1=. THEN DELETE;
IF AADT&YEAR2=. THEN DELETE;
PDIF&YEAR1&YEAR2=(AADT&YEAR2AADT&YEAR1)/AADT&YEAR1*100;
RUN;
PROC CONTENTS DATA=AADT&YEAR1&YEAR2;
TITLE1 "&STATE: COMPARE &YEAR1 WITH &YEAR2";
TITLE2 'CONTENT OF FIRST MERGED FILE';
RUN;
PROC MEANS DATA=AADT&YEAR1&YEAR2 NOPRINT;
VAR PDIF&YEAR1&YEAR2 ;
BY RODWYCLS;
OUTPUT OUT=RESULT MEAN=M&YEAR1&YEAR2
STD=STD&YEAR1&YEAR2;
RUN;
DATA AADT&YEAR1&YEAR2;
MERGE AADT&YEAR1&YEAR2 RESULT;
BY RODWYCLS ;
RUN;
SETTING THE CRITERION FOR THE OUTLIER
The “outlier” could be defined as being any number of
standard deviations away from the mean within any
particular roadway type. In this example use, we decided
that we only wanted to look at the most extreme outliers
(four and five standard deviations away). In other cases,
the user could set at any value that is suitable, and modify
the criterion in this subroutine.
The outliers are calculated in this subroutine using the
means and standard deviations within roadway class. The
dummy variables are created to signalize the extreme
cases. For example, the PC of AADT(PDIFF) is five
standard deviations below the mean of PC for a certain
roadway type(ADT5L=1). The PC of AADT(PDIFF) is
four standard deviations above the mean(ADT4H=1). The
first year and second years are again attached to the
above variables.
/* FILENAME: QC20 */
/* THE EXTERNAL CODE FILE - CRITERION FOR
OUTLIERS */
DATA &STATE..AADT&YEAR1&YEAR2;
SET AADT&YEAR1&YEAR2;
IF PDIF&YEAR1&YEAR2 <= (M&YEAR1&YEAR2 5*STD&YEAR1&YEAR2)
THEN ADT5L&YEAR1&YEAR2=1;
ELSE ADT5L&YEAR1&YEAR2=0;
IF PDIF&YEAR1&YEAR2 <= (M&YEAR1&YEAR2 4*STD&YEAR1&YEAR2)
THEN ADT4L&YEAR1&YEAR2=1;
ELSE ADT4L&YEAR1&YEAR2=0;
IF PDIF&YEAR1&YEAR2 >= (M&YEAR1&YEAR2 +
4*STD&YEAR1&YEAR2)
THEN ADT4H&YEAR1&YEAR2=1;
ELSE ADT4H&YEAR1&YEAR2=0;
IF PDIF&YEAR1&YEAR2 >= (M&YEAR1&YEAR2 +
5*STD&YEAR1&YEAR2)
THEN ADT5H&YEAR1&YEAR2=1;
ELSE ADT5H&YEAR1&YEAR2=0;
RUN;
OUTPUTTING FORMAT FOR THE VARIABLES
After setting up the criterion, it is logical to format the
variables. The PROC FORMAT reads in two formats:
roadway class and outliers for AADT. There are 11 types
of roadway classification in the HSIS. The sections with
outliers are also outputted. For example, the PC of
AADT in five standard deviations above the mean will be
printed as “SECTIONS WITH
PDIF9294>=(MPDIF+5*STDPDIF)” if the format
variable, ADT4H, is requested.
/* FILENAME: FORMAT20 */
* THE EXTERNAL CODE FILE: FORMAT;
PROC FORMAT;
VALUE
$RODWYCL
'01' = 'URBAN FREEWAYS'
'02' = 'URBAN FREEWAYS < 4 LN'
'03' = 'URBAN 2 LANE ROADS'
'04' = 'URBAN MULTILANE DIVIDED NON FREEWAYS'
'05' = 'URBAN MULTILANE UNDIVIDED NON FREEWAYS'
'06' = 'RURAL FREEWAYS'
'07' = 'RURAL FREEWAYS < 4 LN'
'08' = 'RURAL 2 LANE ROADS'
'09' = 'RURAL MULTILANE DIVIDED NON FREEWAYS'
'10' = 'RURAL MULTILANE UNDIVIDED NON FREEWAYS'
'99' = 'OTHERS';
VALUE ADT5L
0 = "SECTIONS WITH PDIF&YEAR1&YEAR2> (MPDIF5*STDPDIF)"
1 = "SECTIONS WITH PDIF&YEAR1&YEAR2<=(MPDIF5*STDPDIF)";
VALUE ADT4L
0 = "SECTIONS WITH PDIF&YEAR1&YEAR2> (MPDIF4*STDPDIF)"
1 = "SECTIONS WITH PDIF&YEAR1&YEAR2<=(MPDIF4*STDPDIF)";
VALUE ADT4H
0 = "SECTIONS WITH PDIF&YEAR1&YEAR2<
(MPDIF+4*STDPDIF)"
1 = "SECTIONS WITH
PDIF&YEAR1&YEAR2>=(MPDIF+4*STDPDIF)";
VALUE ADT5H
0 = "SECTIONS WITH PDIF&YEAR1&YEAR2<
(MPDIF+5*STDPDIF)"
1 = "SECTIONS WITH
PDIF&YEAR1&YEAR2>=(MPDIF+5*STDPDIF)";
RUN;
OUTPUTTING THE NUMBER OF OUTLIERS AND
LISTING THE EXTREME OUTLIERS.
The final subroutine is to print out the results. The mean
and standard deviation of PC for each roadway type are
printed out. A macro variable is created to indicate a list
of variables for the outliers. The PROC FREQ procedure
prints the number of the outliers; PROC PRINT with
WHERE statement lists out the cases. Note that the
global macro variables are used in the TITLE statement to
distinguish year, state, and PC (i.e., &STATE, &YEAR1,
&YEAR2, PDIFF&YEAR1&YEAR2), so the repetitive
effort is reduced.
/* FILENAME: RESULT20 */
/*THE EXTERNAL CODE FILE - THE RESULTS */
%LET GROUP12=
ADT5L&YEAR1&YEAR2 ADT4L&YEAR1&YEAR2
ADT4H&YEAR1&YEAR2 ADT5H&YEAR1&YEAR2;
PROC MEANS DATA=&STATE..AADT&YEAR1&YEAR2 N MEAN
STD;
VAR PDIF&YEAR1&YEAR2 ;
BY RODWYCLS;
FORMAT RODWYCLS $RODWYCL.;
TITLE1 "&STATE: COMPARE &YEAR1 WITH &YEAR2";
TITLE2 'MEAN AND STD OF PERCENTAGE DIFFERENCE';
RUN;
PROC SORT DATA=&STATE..AADT&YEAR1&YEAR2; BY
RODWYCLS; RUN;
PROC FREQ DATA=&STATE..AADT&YEAR1&YEAR2;
TABLES RODWYCLS*(&GROUP12)/NOPERCENT NOCOL;
FORMAT
ADT5L&YEAR1&YEAR2 ADT5L.
ADT4L&YEAR1&YEAR2 ADT4L.
ADT4H&YEAR1&YEAR2 ADT4H.
ADT5H&YEAR1&YEAR2 ADT5H.
RODWYCLS $RODWYCL.;
TITLE1 "&STATE: COMPARE &YEAR1 WITH &YEAR2";
TITLE2 "FREQUENCY ROADWAY BY GROUPING";
RUN;
PROC PRINT DATA=&STATE..AADT&YEAR1&YEAR2 ;
VAR RODWYCLS CNTYRTE M&YEAR1&YEAR2
STD&YEAR1&YEAR2 AADT&YEAR1 AADT&YEAR2
PDIF&YEAR1&YEAR2;
BY RODWYCLS;
WHERE ADT5H&YEAR1&YEAR2=1 OR
ADT4H&YEAR1&YEAR2=1 OR ADT5L&YEAR1&YEAR2=1 OR
ADT4L&YEAR1&YEAR2=1;
FORMAT
ADT5L&YEAR1&YEAR2 ADT5L.
ADT4L&YEAR1&YEAR2 ADT4L.
ADT4H&YEAR1&YEAR2 ADT4H.
ADT5H&YEAR1&YEAR2 ADT5H.
RODWYCLS $RODWYCL.;
TITLE1 "&STATE: COMPARE &YEAR1 WITH &YEAR2";
TITLE2 "CASES-OUTLIERS";
RUN;
CONCLUSION
Given the large databases in the HSIS, this presentation
combines the use of macro variables and subroutines to
analyze the AADT change in a state given any two years.
We find that the effective use of the SAS macro
languages could save significant programming effort for
repetitive tasks. The subroutines consist of reading data,
calculating changes and criterion, outputting the SAS
format, and printing the results. This setup allows the
analyst to modify the different types of changes and
criterion by definition.
REFERENCES
Carpenter, A. (1998) Carpenter’s Complete Guide to
the SAS Macro Language, Cary, NC: SAS Institute Inc.
Council, F.M. and Williams, C. D. (1995) Highway
Safety Information System Guidebook For the
California Data Files, Vol. 1., FHWA, Washington, D.C.
Council, F.M. and Williams, C.D. (1996) Highway
Safety Information System Guidebook For the Illinois
State Files, Vol. 1., FHWA, Washington, D.C.
SAS/ACCESS Software for Relational Databases:
Reference. (1994) Version 6, First Edition.
Whitlock, I. (1999). Getting Started with Macro.
Proceedings of NorthEast SAS Users Group, Inc. 12th
Annual Conference. Washington, D.C.
Zdeb, M.S. (1999). An Introduction to Macro Variables
and Macro Programs. Proceedings of NorthEast SAS
Users Group, Inc. 12th Annual Conference. Washington,
D.C.
Acknowledgments
This presentation is to address one specific purpose. A
few questions have been raised in terms of the breadth of
each topics in analytical and programming field (e.g.,how
to measure change). Only the basic breadth is applied.
The authors are thankful to the Federal Highway
Administration for providing the data. This paper reflects
solely authors’ point of view.
Contact Information
Li wan Chen
LENDIS Corporation
6300 Georgetown Pike, Rm T-211
McLean, VA 22101
Work Phone: 202-493-3466
Email:[email protected].
APPENDICES - PARTIAL OUTPUT
BB: COMPARE 92 WITH 94
CONTENT OF FIRST MERGED FILE
The CONTENTS Procedure
Data Set Name:
Member Type:
Engine:
Created:
Last Modified:
Protection:
Data Set Type:
Label:
WORK.AADT9294
DATA
V8
16:55 Thursday, June 15, 2000
16:55 Thursday, June 15, 2000
Observations:
Variables:
Indexes:
Observation Length:
Deleted Observations:
Compressed:
Sorted:
-----Alphabetic List of Variables and Attributes----#
Variable
Type
Len
Pos
Format
Informat
Label
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
3
AADT92
Num
8
16
11.
11.
aadt
6
AADT94
Num
8
24
11.
11.
aadt
1
BEGMP
Num
8
0
BEST22.
BEST22.
begmp
4
CNTYRTE
Char
7
40
$7.
$7.
cnty_rte
2
ENDMP
Num
8
8
BEST22.
BEST22.
endmp
7
PDIF9294
Num
8
32
5
RODWYCLS
Char
2
47
$2.
$2.
rodwycls
62258
7
0
56
0
NO
NO
BB: COMPARE 92 WITH 94
MEAN AND STD OF PERCENTAGE DIFFERENCE
-------------------------------------------------- rodwycls=URBAN FREEWAYS ---------------------------The MEANS Procedure
Analysis Variable : PDIF9294
N
Mean
Std Dev
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
1375
2.3941314
2.3686341
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
----------------------------------------------- rodwycls=URBAN FREEWAYS < 4 LN -----------------------Analysis Variable : PDIF9294
N
Mean
Std Dev
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
64
2.0562667
0.1203551
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
------------------------------------------------ rodwycls=URBAN 2 LANE ROADS -------------------------Analysis Variable : PDIF9294
N
Mean
Std Dev
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
8364
2.2748350
12.1223146
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ
BB: COMPARE 92 WITH 94
FREQUENCY ROADWAY BY GROUPING
The FREQ Procedure
Table of RODWYCLS by ADT5L9294
RODWYCLS(rodwycls)
Frequency
Row Pct
ADT5L9294
‚
‚SECTIONS‚SECTIONS‚
‚ WITH PD‚ WITH PD‚
‚IF9294> ‚IF9294<=‚
‚(MPDIF-5‚(MPDIF-5‚
‚*STDPDIF‚*STDPDIF‚
‚)
‚)
‚
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ
URBAN FREEWAYS
‚
1375 ‚
0 ‚
‚ 100.00 ‚
0.00 ‚
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ
URBAN FREEWAYS < ‚
64 ‚
0 ‚
4 LN
‚ 100.00 ‚
0.00 ‚
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ
URBAN 2 LANE ROA ‚
8364 ‚
0 ‚
DS
‚ 100.00 ‚
0.00 ‚
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ
URBAN MULTILANE ‚
5963 ‚
5 ‚
DIVIDED NON FREE ‚ 99.92 ‚
0.08 ‚
WAYS
‚
‚
‚
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ
URBAN MULTILANE ‚
1664 ‚
5 ‚
UNDIVIDED NON FR ‚ 99.70 ‚
0.30 ‚
EEWAYS
‚
‚
‚
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ
RURAL FREEWAYS
‚
1172 ‚
6 ‚
‚ 99.49 ‚
0.51 ‚
ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆƒƒƒƒƒƒƒƒˆ
Total
62233
25
Total
1375
64
8364
5968
1669
1178
62258
BB: COMPARE 92 WITH 94
CASES-OUTLIERS
-------------------------------------------------- rodwycls=URBAN FREEWAYS -----------------------------------------------Obs
58
59
60
RODWYCLS
CNTYRTE
M9294
STD9294
AADT92
AADT94
PDIF9294
URBAN FREEWAYS
URBAN FREEWAYS
URBAN FREEWAYS
0161041
0161041
0161041
2.39413
2.39413
2.39413
2.36863
2.36863
2.36863
115920
101262
101262
211071
129659
128696
82.0833
28.0431
27.0921
------------------------------------------------ rodwycls=URBAN 2 LANE ROADS ---------------------------------------------Obs
2159
2178
2185
2374
2377
2385
2386
2387
2394
3948
4875
4876
4877
4878
4879
RODWYCLS
URBAN
URBAN
URBAN
URBAN
URBAN
URBAN
URBAN
URBAN
URBAN
URBAN
URBAN
URBAN
URBAN
URBAN
URBAN
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
LANE
LANE
LANE
LANE
LANE
LANE
LANE
LANE
LANE
LANE
LANE
LANE
LANE
LANE
LANE
ROADS
ROADS
ROADS
ROADS
ROADS
ROADS
ROADS
ROADS
ROADS
ROADS
ROADS
ROADS
ROADS
ROADS
ROADS
CNTYRTE
M9294
STD9294
AADT92
AADT94
PDIF9294
0161041
0165019
0165043
0168076
0168089
0168119
0168119
0168119
0168182
0458103
0498063
0498063
0498063
0498063
0498063
2.27484
2.27484
2.27484
2.27484
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