May 5, 2017

South Poles Converging Time Zones

This was the final map of the year, we were given the freedom to do whatever we wanted to showcase our creativity, imagination, and skills.  We were given certain guidelines and parameters that had to be met, but those were just basic things.


I chose to use this map to explore all the concepts that we learned about maps the entire semester including coordinate systems and different ways a map can show distortion which are area, distance, shape, and direction.  The map shown here utilizes 2 different coordinate systems, one for the time zones and one for the inset map / main map.  The reason for this is because I wanted to show how time zones all converge on to one single point.  As we look at most wall maps, which utilize the Mercator projection, one would think that time zones are all separated by hundreds of miles up and down the globe.  The regular observer does not take time to think that the Earth is sphere so that is not possible.  I color coded each time zone in the key, and it led to the flag mast at the south pole.  I also labeled research stations per county.  Lastly I actually had contours very lightly in the background to give the map some depth and a better look / feel.

Grand Teton revisited

As part of our final project, we were to take a map from earlier in the semester and redo it using the skills we learned throughout the semester.


There are so many differences and improvements here between this map and the original map I made.  First I labeled the contours and used masks to make them show up.  Next the colors are much more vibrant and do a good job of not hiding the most important part of the map which is of course the trails and rivers.  I maintained the same color scheme throughout the map, even in the shadows and north arrow, legend, etc.  Nothing on this map falls off of the border, which looked unprofessional the first time around.  And I used the DRG properly in this map, which is lightly seen in the background.

April 30, 2017

Where did the 2017 NFL first round draft picks go to school?

This weeks assignment was to tell a story with a map.  Seeing how the NFL draft just happened, I chose to use that event to as my "story".


I worked really hard on this one, and had several different things going on here.  First I chose to go with a choropleth map, which color coded each state ranked by number of draftees per state, which varied from 0 - 4.  I also labeled that number in the middle of the state.  I then found the college helmets of each school that had a player drafted, and labeled the players name next to the helmet.  The best way to do this to make it look good was to make a white circle around the helmet. This is due to the limitations with ArcGIS.  Lastly I listed the players on a table on the map.

March 21, 2017

Cattle in Rhode Island

This weeks assignment was working with choropleth maps otherwise known as thematic maps. We also worked with different classification methods.


We were instructed to take a state of our choosing and make a choropleth map of the number of cattle in that state by county.  We had to make 5 different maps and use different classification methods for each map.  We also had to make each map a different size.  This map right here is my favorite of the 5.  I chose the state of Rhode Island because its the smallest state, and allowed me to focus in on what I was doing better.  I really like how I made the counties stick out over the color choices.  I chose to place my ranch right in the middle of the state because the cattle seemed to be mostly located at the northern end and southern end.

Lastly, look at that scale bar, I couldn't believe how tiny Rhode Island actually is!

March 5, 2017

Legends

This week we moved away from maps a bit and concentrated on strictly legends.



The assignment was to take the data set from week 1 (which was a natural park / wilderness with ranches, rivers, roads, trails, and lakes) and make 5 completely different legends based on those feature sets.  The symbols, colors, shapes, fonts, and patch (among other things) all had to be different. I had a lot of fun with this assignment and think I did a good job.

February 20, 2017

Cattle in the U.S.

This week we studied dot maps, and studied different ways to use these types of maps.


The basic idea was to see how well we could design the map and show the viewer where all the cattle are located, using dot map techniques.  The size of the dot was not how I chose to go, instead I chose a dot density map.  I really like the colors I chose for this map, and I used shadows on the inset maps, rounded corners, and made it look really professional.

February 10, 2017

Injuries in the U.S. from extreme weather

This weeks assignment we had to take 3 different data-sets of our choosing that we were to find online, and make a map on how they correlate. We were mostly studying coordinate systems and the idea was to see how different coordinate systems affected the maps themselves.


I chose to go with extreme weather patterns in the US.  The above map shows the amount of injuries sustained from the weather events differentiated by color. My favorite coordinate system to show these particular datasets was USA Contiguous Lambert Conformal Conic.

February 6, 2017

Pacific Northwest Volcanos

This weeks assignment was to create a map of the volcanoes throughout the northwest US.  We were given a dataset consisting of roads, volcanoes, counties, rivers, and cities.


The idea was to take the volcanoes and make them appear larger or smaller, depending on the known eruptions it has had.  Also each county is color coded by population.  Lastly an inset map is shown due to the fact that it isn't exactly clear where exactly we are zoomed in on, as the northwest could possibly include part of California in some peoples minds.

January 22, 2017

Grand Teton National Park, first map for Cartography

First order of business was to make a map from the skills that we already have. We were given a data set consisting of file geodatabase from the Grand Teton National Park.  This is what I came up with.


June 30, 2016

Pansharpening

This week we learned the concept of band ratios, vegetation assessment using NDVI, more false color composites, and examining more imagery from cloud cover.


These maps right here look very unimpressive, but I actually did a lot with them.  For the pansharpened false color image, I mixed the 1 meter nominal spatial resolution of LANDSAT imagery and sharpened it to 30 meters nominal spatial resolution.  The second image is normal color non-pansharpened.