Laura Platchkov<

[hidden email]> :

N.B. there is no command per se, but in words: take the data with

points you want to compute minimum distance from, -merge- (not on

variables, just an unmatched merge) the data with shapes or points you

want to compute distance to, then loop over observations in the first

dataset: for each, compute distance to points in the second (if the

second is a shape file, you will be computing distance to the nearest

vertex of a polygon) and store the minimum distance to a variable you

have initialized as missing. If you later decide you want other stuff

saved, you can add commands inside the loop to save that other stuff

(e.g. ID of nearest shape, or area of nearest shape, or number of

shapes within 50 miles, or what have you).

On Fri, Sep 11, 2009 at 10:33 AM, Laura Platchkov<

[hidden email]> wrote:

> Hi Austin,

>

> Yes I know, the centroid of a water bodies is not so exact, but how could I do it differently? I mean, the shapefile that I have are polygons, and when I transform it in .dta, with the shp2dta command, then STATA automatically computes the centroid.

>

> I computed some distances with distmatch, but I am open to another more realistic solution. Maybe i could try to find a shapefile which contains the limits of the water bodies as points...???

>

> Could you explain your command in words? If I understand well, it will give me the same results as the distmatch command, isnt'it?

>

> Thanks,

>

> Laura

>

>

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