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Not to be confused with GeoTagging.

Geocoding (sometimes called forward geocoding) is the process of enriching a description of a location, most typically a postal address or place name, with geographic coordinates from spatial reference data such as building polygons, land parcels, street addresses, ZIP codes (postal codes) and so on. Geocoding facilitates spatial analysis using Geographic Information Systems and Enterprise Location Intelligence systems.

Reverse geocoding is the process of enriching geographic coordinates with a description of the location, most typically a postal address or place name.

A geocoder is a piece of software or a (web) service that implements a geocoding process.

Address interpolation[edit]



Take for example: 742 Evergreen Terrace


Complicating factors[edit]



While there might be 742 Evergreen Terrace in Springfield, there might also be a 742 Evergreen Terrace in Shelbyville. Asking for the city name (and state, province, country, etc. as needed) can solve this problem. Boston, Massachusetts[1] has multiple "100 Washington Street" locations because several cities have been annexed without changing street names, thus requiring use of unique postal codes or district names for disambiguation. Geocoding accuracy can be greatly improved by first utilizing good address verification practices. Address verification will confirm the existence of the address and will eliminate ambiguities. Once the valid address is determined, it is very easy to geocode and determine the latitude/longitude coordinates. Finally, several caveats on using interpolation:

  • The typical attribution of a street segment assumes that all even numbered parcels are on one side of the segment, and all odd numbered parcels are on the other. This is often not true in real life.
  • Interpolation assumes that the given parcels are evenly distributed along the length of the segment. This is almost never true in real life; it is not uncommon for a geocoded address to be off by several thousand feet.
  • Interpolation also assumes that the street is straight. If a street is curved then the geocoded location will not necessarily fit the physical location of the address.
  • Segment Information (esp. from sources such as TIGER) includes a maximum upper bound for addresses and is interpolated as though the full address range is used. For example, a segment (block) might have a listed range of 100-199, but the last address at the end of the block is 110. In this case, address 110 would be geocoded to 10% of the distance down the segment rather than near the end.
  • Most interpolation implementations will produce a point as their resulting address location. In reality, the physical address is distributed along the length of the segment, i.e. consider geocoding the address of a shopping mall - the physical lot may run a distance along the street segment (or could be thought of as a two-dimensional space-filling polygon which may front on several different streets - or worse, for cities with multi-level streets, a three-dimensional shape that meets different streets at several different levels) but the interpolation treats it as a singularity.

A very common error is to believe the accuracy ratings of a given map's geocodable attributes. Such accuracy currently touted by most vendors has no bearing on an address being attributed to the correct segment, being attributed to the correct side of the segment, nor resulting in an accurate position along that correct segment. With the geocoding process used for U.S. Census TIGER datasets, 5-7.5% of the addresses may be allocated to a different census tract, while a study of Australia's TIGER-like system found that 50% of the geocoded points were mapped to the wrong property parcel.[2] The accuracy of geocoded data can also have a bearing on the quality of research that can be done using this data. One study[3] by a group of Iowa researchers found that the common method of geocoding using TIGER datasets as described above, can cause a loss of as much as 40% of the power of a statistical analysis. An alternative is to use orthophoto or image coded data such as the Address Point data from Ordnance Survey in the UK, but such datasets are generally expensive. Because of this, it is quite important to avoid using interpolated results except for non-critical applications, such as pizza delivery. Interpolated geocoding is usually not appropriate for making authoritative decisions, for example if life safety will be affected by that decision. Emergency services, for example, do not make an authoritative decision based on their interpolations; an ambulance or fire truck will always be dispatched regardless of what the map says.[citation needed]

Point Level Geocoding[edit]

A more accurate mean of geocoding is point-level geocoding. This incorporates locating a point at the centroid (center) of a land parcel or building, thus improves the geocoding accuracy. This level of detail may not be critical for most applications, but for applications such as insurance underwriting, flood determination , and Call-Before-You-Dig uses, a few feet can make a very big difference. [4]

Other techniques[edit]

In rural areas or other places lacking high quality street network data and addressing, GPS is useful for mapping a location. For traffic accidents, geocoding to a street intersection or midpoint along a street centerline is a suitable technique. Most highways in developed countries have mile markers to aid in emergency response, maintenance, and navigation. It is also possible to use a combination of these geocoding techniques - using a particular technique for certain cases and situations and other techniques for other cases. In contrast to geocoding of structured postal address records, toponym resolution maps place names in unstructured document collections to their corresponding spatial footprints.


Recent research has introduced a new approach to the control and knowledge aspects of geocoding, by using an agent-based paradigm.[5] In addition to the new paradigm for geocoding, additional correction techniques and control algorithms have been developed.[6] The approach represents the geographic elements commonly found in addresses as individual agents. This provides a commonality and duality to control and geographic representation. In addition to scientific publication, the new approach and subsequent prototype gained national media coverage in Australia.[7] The research was conducted at Curtin University in Perth, Western Australia.[8]


Geocoded locations are useful in many GIS analysis, cartography, decision making workflow, transaction mash-up, or injected into larger business processes. On the web, geocoding is used in services like routing and local search. Geocoding, along with GPS provides location data for geotagging media, such as photographs or RSS items.

Privacy concerns[edit]

The proliferation and ease of access to geocoding (and reverse-geocoding) services raises privacy concerns. For example, in mapping crime incidents, law enforcement agencies aim to balance the privacy rights of victims and offenders, with the public's right to know. Law enforcement agencies have experimented with alternative geocoding techniques that allow them to mask a portion of the locational detail (e.g., address specifics that would lead to identifying a victim or offender). As well, in providing online crime mapping to the public, they also place disclaimers regarding the locational accuracy of points on the map, acknowledging these location masking techniques, and impose terms of use for the information.

See also[edit]


  1. ^ Google Maps
  2. ^ Ratcliffe, Jerry H. (2001). "On the accuracy of TIGER-type geocoded address data in relation to cadastral and census areal units". International Journal of Geographic Information Sciences 15 (5). 
  3. ^ Mazumdar S, Rushton G, Smith B et al.. Geocoding accuracy and the recovery of relationships between environmental exposures and health. International Journal of Health Geographics. 2008;7:1–13. doi:10.1186/1476-072X-7-13. PMID 18387189.
  4. ^ Point Level Geocoding in Group 1 Product
  5. ^ Hutchinson, Matthew J (2010). Developing an Agent-Based Framework for Intelligent Geocoding (Ph.D. thesis). Curtin University. 
  6. ^ An Agent-Based Framework to Enable Intelligent Geocoding Services
  7. ^ Jennifer Foreshew (24 November 2009). "Difficult addresses no problem for IntelliGeoLocator". The Australian. Retrieved 9 May 2011. 
  8. ^ Department of Education, Western Australia (April 2011). "X marks the spot". School Matters. Retrieved 9 May 2011. 

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