Hi all,
I was wondering how to filter out 'obviously wrong' points from a GPX track
log, which was recorded in heavy tree coverage. The track log was mostly good,
but had a few outlying (individual) points, which would have been hard to find
by hand given 1s data for 1 1/2 hours.
As it took me a while to work out I thought I would document it here, as it
might be of use to someone else. I did this by using GPSBabel to compute the
speed for each point and then used awk to filter out (drop) points which
exceeded a threshold.
$ gpsbabel -t -i gpx -f track.gpx -x track,speed -o unicsv -F temp.unicsv
$ head -n 1 temp.unicsv > new.unicsv
$ head -n -1 temp.unicsv | awk -F ',' '{if ($5<20) print $0;}' >> new.unicsv
$ gpsbabel -t -i unicsv -f new.unicsv -x transform,trk=wpt -o gpx -F new.gpx
The awk script could be made more complicated (ie. calculate acceleration over
several samples) to give an even better result.
The difference is clear:
$ ./wherewasi.py track.gpx --summary
WhereWasI Output
=================
Filename=track.gpx
Number of Track Segments = 1
---------------------------------------------
Start Segment / Point = 0/0
End Segment / Point = 0/5365
Start Time = 07/03/2009 17:35:20
End Time = 07/03/2009 19:04:51
Number of Track Points = 5366
---------------------------------------------
Total Time = 01:29
Total Distance = 12.03 km
Total Climb = 4761 m
---------------------------------------------
Average Speed = 8.06 km/hr
Maximum Speed = 1239.35 km/hr
---------------------------------------------
$ ./wherewasi.py new.gpx --summary
WhereWasI Output
=================
Filename=new.gpx
Number of Track Segments = 1
---------------------------------------------
Start Segment / Point = 0/0
End Segment / Point = 0/5316
Start Time = 07/03/2009 17:35:20
End Time = 07/03/2009 19:04:50
Number of Track Points = 5317
---------------------------------------------
Total Time = 01:29
Total Distance = 9.86 km
Total Climb = 3469 m
---------------------------------------------
Average Speed = 6.61 km/hr
Maximum Speed = 66.82 km/hr
---------------------------------------------
Cheers,
Mungewell.
PS. Wherewasi can be found here:
http://code.google.com/p/wherewasi/
_______________________________________________
talk mailing list
[email protected]
http://lists.openstreetmap.org/listinfo/talk
