<p><div><div><div><div data-width="100" data-show-faces="false" data-send="true" data-layout="button_count" data-height="21" data-href="https://www.r-bloggers.com/map-projections-for-r-shapefiles-united-states/"></div></div><div><a data-url="https://www.r-bloggers.com/map-projections-for-r-shapefiles-united-states/" data-counturl="https://www.r-bloggers.com/map-projections-for-r-shapefiles-united-states/" data-count="horizontal" data-text="Map Projections for R Shapefiles: United States" class="twitter-share-button" data-via="rbloggers" href="https://twitter.com/share"></a></div><div></div></div><div></div></div>
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(This article was first published on <strong><a href="https://www.datascienceriot.com/map-projections-for-r-shapefiles-united-states/kris/"> R Tricks</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Someone contacted me recently about the map projections used in my <a target="_blank" rel="nofollow" href="https://github.com/keberwein/blscrapeR">blscrapeR package</a>. After a bit of web searching, I couldn’t find a really good list of map projections for the continental U.S. that could be used in R. This list is as much for my own reference as anyone else, but hope you find it useful.</p>
<p>Here’s my list of map projections that are appropriate to map the continental U.S. in R. <strong>DISCLAIMER:</strong> I have omitted many, if you like another, comment and I’ll add to the list. The full code is below in Gist form. There are many other projections <a target="_blank" rel="nofollow" href="http://spatialreference.org/ref/?search=USA">listed here</a>, I just displayed the ones I find most useful.</p>
<p><strong>The Native Map Projection</strong><br>
U-g-l-y, you ain’t got no alibi!</p>
<pre>
# Default projection of the map can be found by running the following on the SpatialPolyGonsDataFrame.
raster::crs(county)

# Then apply the result to the CRS() functions.
us.map &lt;- spTransform(state, CRS(&quot;+proj=longlat +datum=NAD83 +no_defs +ellps=GRS80 +towgs84=0,0,0&quot;))
</pre>
<p><a target="_blank" rel="nofollow" href="https://i0.wp.com/www.datascienceriot.com/wp-content/uploads/2016/11/standardproj.png?ssl=1"><img sizes="(max-width: 464px) 100vw, 464px" alt="standardproj" class="wp-image-996" src="https://i0.wp.com/www.datascienceriot.com/wp-content/uploads/2016/11/standardproj.png?resize=456%2C347&ssl=1" data-recalc-dims="1"></a></p>
<p><strong>Mercator Projection</strong></p>
<pre>
# Mercator projection.
us.map &lt;- spTransform(state, CRS(&quot;+proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0  
                                 +x_0=0.0 +y_0=0 +k=1.0 +units=m +no_defs&quot;))
</pre>
<p><a target="_blank" rel="nofollow" href="https://i0.wp.com/www.datascienceriot.com/wp-content/uploads/2016/11/Mercatorproj.png?ssl=1"><img sizes="(max-width: 464px) 100vw, 464px" alt="mercatorproj" class="wp-image-997" src="https://i0.wp.com/www.datascienceriot.com/wp-content/uploads/2016/11/Mercatorproj.png?resize=456%2C347&ssl=1" data-recalc-dims="1"></a></p>
<p><strong>Lambert Azimuthal Equal Area Projection</strong></p>
<pre>
# Lambert Azimuthal Equal Area
us.mpa &lt;- spTransform(state, CRS(&quot;+proj=laea +lat_0=52 +lon_0=10 +x_0=4321000 +y_0=3210000 
                          +ellps=GRS80 +units=m +no_defs&quot;)) 
</pre>
<p><a target="_blank" rel="nofollow" href="https://i2.wp.com/www.datascienceriot.com/wp-content/uploads/2016/11/LambertAproj.png?ssl=1"><img sizes="(max-width: 464px) 100vw, 464px" alt="lambertaproj" class="wp-image-998" src="https://i2.wp.com/www.datascienceriot.com/wp-content/uploads/2016/11/LambertAproj.png?resize=456%2C347&ssl=1" data-recalc-dims="1"></a></p>
<p>