Address matching or Geocoding  Very common for:  E 911  Crime reports  Customer records  Tax/Parcel records  Marketing  Driving directions Most common form of ‘geographic’ data (places are located without coordinates)

TIGER files  Topologically  Integrated  Geographic  Encoding and  Referencing Developed for the US Census Bureau, the best free base level street maps available. (but far from perfect!! You really do get what you pay for)

TIGER files available from ESRI (saves navigating the US Census Website!)

A sample of a TIGER road file for Benton County. Note the specific topology for each street Each street is represented by multiple segments. Each segment is defined by a Fnode (from node) and a Tnode (to node) This provides a direction for each segment... Address ranges are assigned for the right and left sides of the street segment.

A spatial interpolation algorithm estimates the approximate location, the offset can be specified by the user.

Arcview uses the address fields from the TIGER File to begin locating a given address. Before gecoding an address table, it is necessary to go into the theme/properties tab and set up the geocoding ‘address style’ field.

In ArcGIS one must create a ‘address locator’ in Arc Catalog

These examples are from Arcview... However the settings are the same for ArcGIS

Rates below 50% of address correctly matched on the first try are fairly common.

To maximize the number of addresses automatically matched you should:  Don’t use periods. Periods are ALMOST NEVER used (except when its part of the street name, which is very, very unusual);  Don’t spell out street numbers (e.g. 14th St; NOT Fourteenth St);  "W" for West and "E" for East (e.g. 215 W 118th St). However,"East"and "West" are spelled out when its part of the street name (e.g. West Side Hwy);  "th" or "rd" or "st" contiguous with the street number, when appropriate (e.g. 215 W 118th St)

Standardized Address Format...

When addresses have been geocoded, it is possible to begin analyzing the spatial distribution of points, and relationships. In this example, veterinary clients are seen with median income as a backdrop.