With the sunspots down, work slow and COVID keeping me home, I had some time to
start a project that I’ve been thinking about for a while. I've always been
interested in tools to discover locations for an exceptional HF DX QTH, one
with terrain profiles that put a smile on your face when you run HFTA. So I
wrote some code to help find such locations. The code basically extracts data
from two VERY large databases created by Andrew Kirmse and the late Edward
Earl, accomplished mountaineers, mathematicians and software developers.
Andrew and Earl did the heavy lifting, writing sophisticated code to extract
key topological measures from the Shuttle Radar Topology Mission's digital
elevation data, with voids filled in by other means. The key characteristics
contained in these databases are the Topological Prominence and Topological
Isolation of a peak. Rather than try to explain these topographic functionals
here, look them up on Wikipedia if you're interested. Larger Prominence is
better. Larger Isolation is better. A combination of both can be better yet.
Are these two topographic functionals the most useful characteristics for
finding an exceptional HF DX location? They are a good start but something
called Omnidirectional Relief and Steepness (ORS) would probably be better.
But computing that functional is a project for another day.
My code (in Matlab) generates an Excel file containing hilltops (or mountain
tops) that have both Prominence and Isolation values within a given search
area, sorted in decreasing Prominence. The Prominence database has all peaks
in the world with a Prominence of 100 ft or more. The Isolation database is
even larger.
So will this data immediately point to "The Perfect Spot?" No, but it will
pare down the search. Discovered peaks may have excellent low takeoff angles
in only some directions, provided you can get close to the start of the
downslope. Then there's the aspects of soil conductivity, background noise
floor, access, neighborhood HOA's, CC&R’s, etc. As I made some trial runs, I
discovered many of the better spots already occupied by commercial towers,
which in retrospect should have been no surprise.
I can highly recommend using http://www.heywhatsthat.com/ for a more detailed
examination of a particular site of interest. On that web site, you can
generate a panorama but more importantly see the viewshed of the peak and
generate plots of the terrain profile at various azimuths around the peak.
Take some time first to read the FAQ at http://www.heywhatsthat.com/faq.html
The site has a lot of features.
My pass-fail test for the current beta version of the code was 'discovering'
the location of the legendary DX'er W3CRA (SK) in Canonsburg, PA. It does. On
Google Map’s satellite view, the remains of his Yagi can be seen 485 ft to the
northwest of the peak’s position (Hanna’s Knob) on the downslope. Frank was
well known for his booming signal into Asia when no other USA stations could be
heard.
An example of the program's output is the link below. The search area for the
example was a 20 mile box around W3CRA. Frank's location is in red font in the
spreadsheet and shown as the black square with a data tip on the map sheet.
https://www.dropbox.com/s/c3osexf6mginsm7/20%20Mile%20Box%20Around%20W3CRA.xlsx?dl=0
If anyone would like me to generate a spreadsheet and email it, please contact
me OFF-REFLECTOR. I can generate data for any US State or a country, but
that's likely too much data to be useful. You can define a smaller search area
by supplying the latitude and longitude for the vertices of a polygon
surrounding the area of interest, like a triangle, square, rectangle,
parallelogram, etc. That data should be supplied in the format below,
including the square brackets. That will make it much easier for me to cut and
paste into my input file.
Latitudes = [LAT1 LAT2 LAT3 ... LATn]
Longitudes = [LONG1 LONG2 LONG3 ...LONGn]
Where LAT1 & LONG1 are the latitude and longitude of one corner of the polygon
search area, LAT2 & LONG2 the next corner, etc. The lat/long pairs can be
supplied in any order as long as the resulting polygon is convex (doesn't
dimple in on itself). For example, the two vectors used for the rectangular box
in the W3CRA example were:
Latitudes = [40.389332 40.389332 40.099761 40.099761]
Longitudes = [-80.369059 -79.988657 -79.988657 -80.369059]
Northern hemisphere latitudes are positive. Southern hemisphere latitudes are
negative. Longitudes west of the prime meridian are negative. Longitudes east
of the prime meridian are positive.
Perhaps this tool could prove useful to someone or maybe just a curiosity to
spend a rainy day looking for the “perfect spot.”
Have fun and good DX.
N3AE
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