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I recently compared result of US Census Geocoder(http://geocoding.geo.census.gov/geocoder/) with that of Google Maps. For any given address both of them are giving different set of lat, lon. Why there is a difference between both of these?

My assumption is that Google Maps are based on US Census Geography data so both should be same.

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  • Without looking, I would guess that the Census geocoder is probably range based while the Google one may be parcel based. I would assume Google has parcel level information for most of the US.
    – Branco
    Feb 19, 2015 at 17:53
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    Google Maps is originally based on TeleAtlas data for street data and TomTom for street attributes. The Census Bureau is based on Master Address File which is updated by the U.S. Postal Service. My recommendation is to another source for comparing the two. What you need is a gold standard source that undeniably has all of the characteristics you need. Both Google Maps and the TIGER files estimate the location of the address based on the position of the address range along a segment of road. My advice is to obtain parcel data with street address to truly compare the two.
    – Kotebiya
    Feb 19, 2015 at 18:28
  • I use StreetMap locators to update the Master Address File, if that fails, a lat long search of an aerial image.
    – Maksim
    Feb 19, 2015 at 18:40

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The difference is because the Census locator is based on TIGER street files, which is not as a complete a dataset as Google Streets has. So for any given road, the TIGER streets may have an address range of 1-1000 whereas in reality the range is updated with more houses, etc. Some roads may not even exist within the TIGER files.

The street segments in TIGER files may also be incomplete, so it may match halfway along the street segment associated with the address range, where in reality, and Google, the street may be much longer. So a halfway match for TIGER may be halfway along the range of addresses for this shortened segment, but in reality is located elsewhere when the segment is of actual length.

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  • This is the case. I ran many simulation, tested this data by physically going to that place with a GPS device to test the accuracy. Google is providing more accurate results compared to tiger.
    – Akhil
    Feb 28, 2015 at 22:22
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I looked up a little more after posting my comment. The Census is a range based geocoding service. They state...

The current Geocoding Services engine requires a structure address be provided. The resulting lat/long is calculated along an address range.

Google on the other hand, looks to have a variety of options in their geocoding service. I didn't find anything specific as to their data backing. However, I did find some stuff in their geocoding parameters. They have the following geocoder location types in their parameters.

location_type stores additional data about the specified location. The following values are currently supported:

google.maps.GeocoderLocationType.ROOFTOP indicates that the returned result reflects a precise geocode.

google.maps.GeocoderLocationType.RANGE_INTERPOLATED indicates that the returned result reflects an approximation (usually on a road) interpolated between two precise points (such as intersections). Interpolated results are generally returned when rooftop geocodes are unavailable for a street address.

google.maps.GeocoderLocationType.GEOMETRIC_CENTER indicates that the returned result is the geometric center of a result such as a polyline (for example, a street) or polygon (region).

google.maps.GeocoderLocationType.APPROXIMATE indicates that the returned result is approximate.

So... It looks like Google collects data related to those types, and I would guess automatically tries each of the type as going from more precise to less precise in order to get a higher match percentage. I am sure if you want more precise details than what is available through the Google Maps developers FAQ about Google's geocoding, you could send them an e-mail.

Interesting enough, if you aren't familiar with geocoding techniques, I found a paper that compares them here.

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