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st: Choosing the best set of longitude/latitude coordinates from three choices


From   Matthew Krauchunas <krauchunasms@mymail.vcu.edu>
To   statalist@hsphsun2.harvard.edu
Subject   st: Choosing the best set of longitude/latitude coordinates from three choices
Date   Wed, 14 Jul 2010 11:19:44 -0400

Hello,

The data management process for my dissertation is fraught with
obstacles beyond my current Stata abilities, so I am returning to the
"well" where everyone has been extremely helpful.

I have some geocoded data from three sources and I need to figure out
a way to choose the best set of coordinates.  The source of the
coordinates are Intelligentsearch GIS (intel_lat & intel_long), USC
GIS (usc_lat & usc_long), and OSHPD provided GIS (oshpd_lat &
oshpd_long).  The OSHPD GIS also has 71 missing longitudes and
latitudes.  I have calculated the difference between these three sets
of coordinates:  Intelligentsearch & USC
(intel_usc_lat_diff	intel_usc_long_diff), OSHPD & USC
(oshpd_usc_lat_diff oshpd_usc_long_diff), and OSHPD &
Intelligentsearch (oshpd_intel_lat_diff	oshpd_intel_long_diff).  I
need to keep the best coordinates (i.e., from two datasources with the
smallest difference), name the new coordinates longitude and latitude,
and use the USC coordinates as the default (i.e., use the USC
coordinates when the smallest difference is between USC and
Intelligentsearch).

Let me provide an example:  oshpd_fac_no 206194320 has a
oshpd_usc_lat_diff of -3.372433, oshpd_intel_lat_diff of -3.372299,
and a intel_usc_lat_diff of 0.000134. Obviously the OSHPD gis is the
problem and the USC latitude needs to be kept as it is my default.

Does anyone have any ideas for this?

Here is some sample data if it helps:

oshpd_fac_no	intel_usc_lat_diff	intel_usc_long_diff	oshpd_usc_lat_diff	oshpd_usc_long_diff	oshpd_intel_lat_diff	oshpd_intel_long_diff	oshpd_long	oshpd_lat	usc_lat	usc_long	intel_lat	intel_long
206271717	-2.928555	4.037598	2.928555	-4.037582	0.000000	0.000015	-121.9128	36.56206	33.63351	-117.8752	36.56206	-121.9128
206100833	-0.124664	0.399834	0.123066	-0.401627	-0.001598	-0.001793	-119.4988	37.10662	36.98355	-119.0972	37.10822	-119.497
206491017	-0.086819	0.052116	0.024086	-0.007385	-0.062733	0.044731	-122.4599	38.27798	38.25389	-122.4525	38.34071	-122.5046
206044001	-0.058876	-0.041939	0.058018	0.040482	-0.000858	-0.001457	-121.598	39.78528	39.72726	-121.6385	39.78614	-121.5965
206190123	-0.056854	-0.162796	0.054424	0.182648	-0.002430	0.019852	-118.2801	34.05378	33.99936	-118.4627	34.05621	-118.2999
206281040	-0.050270	-0.041695	0.000572	0.000282	-0.049698	-0.041412	-122.3058	38.31432	38.31374	-122.3061	38.36401	-122.2644
206040974	-0.039154	-0.023483	0.043438	0.026169	0.004284	0.002686	-121.6123	39.7707	39.72726	-121.6385	39.76641	-121.615
206070948	-0.038231	-0.044518	-0.001057	-0.000832	-0.039288	-0.045349	-122.132	37.88853	37.88959	-122.1312	37.92782	-122.0867
206374019	-0.036625	-0.008965	-0.001068	-0.000153	-0.037693	-0.009117	-116.984	32.83546	32.83652	-116.9839	32.87315	-116.9749
206301202	-0.033604	-0.016846	-0.000050	-0.001251	-0.033653	-0.018097	-117.836	33.74546	33.74551	-117.8347	33.77912	-117.8179
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