Centerline Magic
System Process
The first process is to create a table of unique street direction, name and street type combinations
from each of the input files. Once this has been accomplished the two files maybe compared to
determine where, if at all, there will be any obvious no-assignment conditions. This would occur
if there are 12 parcels with addresses on Elm Street, but no street segments found by that name in
the street centerline file. This condition would obviously result in a no match situation.
Both the centroid file and centerline file are read simultaneously. If the first street to be processed
is Ash Street, then all the street segments named Ash Street and all the parcel centroids on
Ash Street are extracted and written to two temporary files.
A proximity command is then performed (in Arc/Info this is the NEAR command) which
calculates the distance from the centroid to the nearest arc segment. This information is recorded
in a third file.
Table 4: Process Input Record
| Seg –ID |
Point-ID |
Address |
| 154 |
1257 |
110 N Elm St |
| 154 |
1256 |
102 N Elm St |
| 154 |
1258 |
105 N Elm St |
| 154 |
1265 |
101 N Elm St |
Once this information has been collected, the data is analyzed for information such as segment
side, its relative position along the segment, and parity. The address range record is then
generated.
| ID |
Street |
Even Low |
Even High |
Odd Low |
Odd High |
| 000154 |
N Elm St |
102 |
110 |
101 |
105 |
Having collected the necessary information, it is now possible to determine all address points
that abut the street segment. We can also determine:
- The high and low ranges for each side of each segment
- The parity of each side of each segment
- Whether the direction of the line segment is consistent with the direction of addresses
One side benefit of this process is the creation of a tally sheet of addresses per segment. This
may not appear to be much of a benefit, but it provides a strong indication of the reliability of the
resulting address ranges. Another benefit of this process is in identi~ing anomalous addresses,
those located within the wrong hundred block or located on the wrong side of the street.
Some post processing must be performed to “fill in” the blanks in cases where there exists only
one abutting street address along a street segment. This occurs in sparsely populated areas on the
urban fringe. It also occurs in heavily developed urban areas when a single structure or parcel
may occupy an entire city block. An additional post-processing step corrects the direction of the
line segments identified as being contrary to the direction of the addresses.
The end result of this process is an automated tool that mimics the field collection techniques
used for so long in building street centerlines. In stead of sending field personnel onto the streets,
a software module does the looking and encoding. The automated tool “looks” at existing data
sets using a consistent process based on high school trigonometry and Boolean logic. By using
this automated approach, intelligent street range graphic files may be constructed in a shorter
amount of time and by performing less field work–resulting in a file that has a greater degree of
accuracy and is more defendable.
Conclusion
An automated address assignment process has many advantages over traditional field or map
compilation methods:
- A significant time and cost reduction
- Defendable and repeatable address range construction
- Graphic and Tabular editing occurring in one automated jobstream
- Address statistics for each centerline segment
- Periodic recompilation is an option
- Subjective operator interpretation is removed from the process
