Sunday, October 10, 2010

Baseball at the North Pole

In my last post we saw how Greenland, which has 1/8th the land area of South America,  looks just as large or even larger on a flat map.  How can this be?  Well, ask yourself this. 



How can you take a spherical earth and represent it on a flat piece of paper?
There’s no simple way to do it.  Something has to be changed, stretched or broken to change spherical (round) coordinates of longitude and latitude (lon,lat) into planar (flat) X,Y coordinates.  One way to do this is to take the lon,lat values and plot them directly on an X,Y graph.  It looks something like this.



This seems pretty reasonable and simple.  Let’s look a little closer.  If you had a pair of magic shoes that allowed you to walk on water as well as over land, ice and snow, how far would you have to go to walk around the world following the equator? 

Well, it turns out to be about 40,075 kilometers (24,901 miles).  Now what if you followed the 30˚ north latitude line around the world?  You’d have to walk less far – about 34,706 km (21,565 mi).  And at 60˚ north latitude only 17,353 km (10,783 mi).  And at the North Pole?  Well, if you could set up a baseball diamond with the pitcher’s mound on the North Pole, you could hit a home run and literally run around the world in just 360 feet!
In fact, the crew of the nuclear submarine USS Seadragon did this on March 25, 1960.  I got this photo from a GIS user who lives on the Big Island of Hawaii.  Her father took the photo.  You can find a copy in the National Archives also.
So what does this mean about the scale of our map?  In order to plot round lon,lat on flat X,Y, we had to keep stretching out our map as we moved to the north (and to the south).  The map scale stays constant at different longitudes, but as we have seen, can vary dramatically at different latitudes.  This makes it very difficult to plot a course for navigation purposes.  Gerardus Mercator (500th birthday was on March 5, 2012) figured out a way to solve this problem.  I’ll explain his solution in my next post – hint: it’s the Mercator Projection.  For a preview, here’s a link to University of Colorado Peter H Dana’s website on map projections.
A hui ho!


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