Spatial data becomes much more valuable when it can be combined, overlaid, and compared with other data. For example, last week Michael discussed how combining disparate data sources can make it easier to understand the big picture when disaster strikes.

However, before you can compare and visualize your data, you need the ability to overlay different datasets so they overlap correctly (e.g., if a street intersection on a map corresponds to a pixel in a satellite image, they should line up when viewed together). Typically, this is accomplished by converting everything into a common coordinate system, such as lat/long WGS84. This depends on your data being georeferenced: tied, via the coordinate system, to known locations on earth. But what do you do when your data doesn’t have a coordinate system at all?

A classic example of this dilemma is the case of a building blueprint referenced only to local features or markers. If one then wants to view that blueprint in the context of nearby elevation data, roads, airport noise etc., the lack of georeferencing poses a challenge.

Mathematically, solving this problem is often relatively simple: An affine transformation (fixed offset, scale, and rotation) might maintain sufficient accuracy while converting between a local coordinate system and a georeferenced one. Or, in simpler cases, it might be enough to say that some local coordinate (x,y) corresponds to a given lat/long. The hard part is keeping track of that extra metadata in a useful way.

Given that the lack of georeferencing is a common and important challenge, a number of techniques have been developed to deal with it. For example:

Adding real-world location to your spatial data is possible, and opens the door to more context and greater collaboration. So start looking for doors to open. A simple next step might be to export your newly georeferenced data to KML and view it in Google Earth. After that? The sky’s the limit.

About Data Autodesk Coordinate Systems Data Transformation Esri Spatial Data

Paul Nalos


4 Responses to “How to Defeat Common Barriers to Georeferencing”

  1. Liked the term “Sidecar Files.” Haden’t heard that one before. Thanx for the post!

  2. Paul Nalos says:

    Hi Justin,

    Thanks for the feedback; I’m glad this was useful.

    I first heard about “sidecar files” in the context of the ESRI Shapefile. Each Shape “file” is actually a set of three or more files with a common prefix and different extensions (see I also see there’s a Wikipedia page on sidecar files (, which interestingly doesn’t mention Shapefiles at all.



  3. […] in the context of other data — say the surrounding city blocks — you’d need a way to georeference that blueprint, associating its coordinates with real-world […]

  4. Hey guys which is best ERDAS, ARCGIS or are there other software’s including open source ones?

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