Cartographic Skills Lab

For this lab we worked with (or in my case....fought with) Adobe Illustrator again. The main challenge for me was getting all of the layers grouped together correctly so they can be moved and re-sized as one cohesive unit when needed. Our main goal was to create a map that displays appropriate placement of map elements and appropriate map hierarchy.

Projections Lab

In this lab we created a map which shows 3 different projected coordinate systems. Below you can see that we used a map of Florida in which 4 counties are highlighted and their area is shown in each projection's legend. This was an interesting exercise because you got to see how different  projections distort areas differently. 

 

Grouping with Adobe Illustrator

This week's map shows the location of Florida cities. It was first created using Arc Maps and was then exported into Adobe Illustrator as an ai file. Our main objective was to focus on grouping files properly in order to maintain the correct scale size. To do this, the scale bar was grouped with the counties and cities layer.

ESRI's online global account

This week we worked with ESRI's online global account. We created our own accounts, took a couple of the online courses offered, and uploaded two Map Packages  to our accounts. The First map we uploaded shows rock climbing sites in Yosemite National Park. Before uploading this MPK to our ESRI accounts we made a few small modifications. The second map we uploaded was a bit more involved. We created a map showing a study area in the Organ Mountains in N.M. Then, bundled data into two different groups showing the data at different scales. I was excited to learn the ESRI learning and sharing sites are there to utilize.  

GIS3015 Week 3

The maps below were created from data collected during the 2000 census. They show the population of black Escambia County residents by census tract. The first map shows the percentage of residents using 4 different classification methods. The second map is only depicting the Natural Breaks method which I believe to be the most accurate method for this example. Unlike the Equal Interval and Quantile methods, Natural breaks take into account how that data are distributed along the number line. Because of that, Natural breaks minimize differences of data values in the same class. This allows each data class to be better represented on the map.

 (I added a border in Arcmaps, I'm not sure why it isn't showing up on the blog)