QSO Mapping #2

Having taken inspiration from Andy’s pages at Alloutput.com I’ve been progressing the idea of generating cleaner maps of my QSOs. As mentioned in my earlier posts I’ve progressed from the rudimentary maps generated by the online adif2map type solution, through to an KML import into Google Earth.

Both of these provide nice maps which allow you to click on specific contacts for more details. The problem comes, as Andy states, when you spread your wings further or you end up with a very dense saturation of an area or country.

As of today my contact map on Google Earth looks like this

Screenshot 2015-10-25 08.26.55

Screenshot 2015-10-25 08.28.25

I must admit I like the curvature of the globe representation and when you start overlaying sunlight across the landscape animation it really becomes quite surreal, however it’s always worth exploring other options.

I had a good read of Jeff’s pages at http://n1ywb.blogspot.co.uk/ and realised rapidly that I really don’t know the first thing about Python scripts but not to be defeated I had a good play with some of the ideas which are discussed and have come up with a solution which appears to work nicely.

My notes are below for reference.

I’m still logging my contacts primarily within the Fldigi logbook and manually uploading to the usual sites to gain credit for various awards.

Fldigi has an ADIF export function which generates the required ADI file. To convert this to an XML file, rather than paying for a subscription service within QRZ.com I use a standalone package to do this.

ADIF2KML by CT1GVN http://www.qsl.net/ct1gvn/adif2kml.htm does the job nicely. Ironically it’s a Python script that someone has very kindly packaged in a ready to run format. It takes your ADIF file and produces the KML file ready to load into Google Earth and the data appears in the My Places pane on the left hand side allowing you to switch various elements on and off for analysis.

For the next step I grasped the nettle and installed QGIS http://www.qgis.org/en/site/ which is a very complex package and you could make a hobby out of playing with maps very easily.

I completely missed the “Gentle Guide to QGIS” http://docs.qgis.org/2.8/en/docs/gentle_gis_introduction/ and ended up at the “Getting Started section ” which had me playing with lakes in America for a good half an hour before I had the slightest idea as to what I was doing – http://docs.qgis.org/2.8/en/docs/user_manual/introduction/getting_started.html

I downloaded the 1:10m natural earth set from http://www.naturalearthdata.com/downloads/10m-raster-data/10m-natural-earth-1/ opting for the large size Natural Earth I with Shaded Relief, Water and Drainages detail.

I must admit that all these packages and map sets are very large and chomp up disk space, however I think the level of detail certainly adds to the finished product.

From within QGIS open the NE1_HR_LC_SR_W_DR.tif from the naturalearthdata.com dataset as a Raster layer.

Screenshot 2015-10-25 16.11.21

The detail level is very nice for what I’m trying to achieve

Screenshot 2015-10-25 16.12.46

The next step is to import the KML file generated by ADIF2KML as a Vector Layer. Thankfully there is no need to edit any of its contents to remove any extraneous data as mentioned in other blogs, which is a bonus.

Screenshot 2015-10-25 16.16.55

Screenshot 2015-10-25 16.17.11

The various elements forming the vector layer can be selected depending on what you want to map. Here I’ve selected only 40m contacts which show my recent success in bagging QSO’s in Northern Ireland and Yorkshire.

Screenshot 2015-10-25 16.29.13

The finished product for this stage is below

test2

Below is with the map skewed to show European Russian contacts.

european russia

I’ve tried repeatedly to produce a great earth projection for this data but unfortunately each time I generate my globe projection it explodes quite spectacularly when you zoom in. Zooming out does not rectify the problem either which is extremely frustrating. Unfortunately I don’t have the time or the knowledge with the QGIS software to overcome this issue, so at the moment I’ll be sticking with what we’ve got.

 

 

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