Ordnance Survey Data Importer Coordinate Conversion Accuracy

Update 13 March 2013: Please see latest blog post (fix) on this here.

Thanks to a comment on my original post around my project that imports Ordnance Survey CodePoint data into SQL Server, I was made aware of a potential issue with the (awesome) third party GeoCoordConversion DLL I use to convert the Eastings/Northings coordinates supplied in the Ordnance Survey data files, into Latitude/Longitude coordinates. The issue relates to an inaccuracy in the conversion process, specifically to do with integer divisions instead of double.

So, this blog post is to document my analysis of that and try to quantify what, if any, impact there is on the accuracy of the conversion of Eastings/Northings to Latitude/Longitude. So what I’ve done is:

  1. Import the Ordnance Survey data set using the released version (1.0.0.0) of the GeoCoordConversion library (i.e. the version my project uses)
  2. Downloaded the source code for GeoCoordConversion and corrected the parts of the calculations where the raised issue noted an inaccuracy
  3. Reran the data import into a separate table using the “corrected” conversion code
  4. Ran the following query to try and quantify how much of a difference it actually makes:
;WITH CTEDiff AS   
(  
    SELECT orig.OutwardCode, orig.InwardCode,  
        orig.GeoLocation.STDistance(new.GeoLocation) Dist  
    FROM PostCodeData orig  
        JOIN PostCodeDataWithFix new ON orig.InwardCode = new.InwardCode   
            AND orig.OutwardCode = new.OutwardCode  
)  
SELECT MIN(Dist) AS MinDifferenceInMetres,   
    MAX(Dist) AS MaxDifferenceInMetres,   
    AVG(Dist) AS AverageDifferenceInMetres,   
    SUM(CASE WHEN Dist = 0 THEN 0 ELSE 1 END) AS NumberOfDifferences  
FROM CTEDiff  

Results

The MAXIMUM distance between the 2 conversions for a given postcode is: 124.9 metres.
The MINIMUM distance between the 2 conversions for a given postcode is: 0 metres.
The AVERAGE distance between the 2 conversions for a given postcode is: 2.5 metres.
The TOTAL NUMBER of differences was 1,652,458 (out of 1,705,177 conversions).

This map shows the case that had the biggest difference (postcode: NR34 8JW). Plotted points are as follows:
(A) = position from conversion process before fix
(B) = position from conversion process with fix
(C) = position Google Maps gives for location
Note (B) and (C) are in the same spot, so that’s why you can’t see both!

View Larger Map

Summary

For me, and what I see as potential uses for this data, I personally don’t see this as much of an issue especially with an average difference of 2.5 metres. I will add a comment on to the GeoCoordConversion project issue page, referencing this post. Though there doesn’t look to be any activity on the project, so whether a fix can be applied is yet to be seen. That’s my preferred route at present, to see if the author of that project is around to apply a fix as I currently don’t have full knowledge of what I changes I can make to the source code and what would be acceptable in order to distribute the amended source code as part of my project (my project is released under a different, but compatible license…but things might get murkier when it comes to amending/distributing those amendments). In a nutshell, I just don’t have time to try to make head and tail of what I can legitimately do (and I don’t want to change the license for my project)!

All feedback welcomed


See also