<div dir="ltr"><div><div><div><div><div>Hey,<br></div>it is unclear what you want and how your data looks like.<br></div>For better answer it would be good to have better info.<br><br></div>Maybe a screen of your data, some facts, for what usage (admissible error, expected quality ..) etc etc.<br><br></div>What you are trying to do (reconstruct a network from sampled pieces) is in general a complicated problem.<br></div>It may be simpler depending on your data and hypothesis.<br><div><br>Cheers,<br>Rémi-C<br><div><div><div><div><br></div></div></div></div></div></div><div class="gmail_extra"><br><div class="gmail_quote">2015-01-26 9:28 GMT+01:00 Dave Barter <span dir="ltr"><<a href="mailto:email@example.com" target="_blank">firstname.lastname@example.org</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div style="word-wrap:break-word"><span class=""><blockquote type="cite"><span><br><br>> These points were created from a GPX file along a road journey so they crudely map to a line string
<br>"Map matching" is the term often used to describe the process of assigning noisy Gpx points to underlying road network.
<br><br></span></blockquote><br></span><div>My problem is a bit more involved.</div><div><br></div><div>The GPX points represent the national cycle network in the UK. These points cover roads/tracks/paths and all sorts and as such I cannot really snap to map. Creating line strings from the points will possibly cause errors as well as I think there will be a lot of cases where the wrong points are joined. </div><div><br></div><div>I think the safest method is to remove densely distributed points from the current set until they all have a KNN value of > X. This will not create a completely even distribution but will ensure that no points are created in the wrong place which may be the case with line interpolation. </div><div><br></div><div>Can anyone help me with a query to do this?</div></div><br>_______________________________________________<br>
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