Lab 1

The purpose of this lab is the understand Coordinate Systems and Map projections.  The goal is of this lab is to understand the differences between projected and geographic coordinate systems and how to apply then to our GIS projects.  Additionally, to find and identify errors in GIS data.  Then to re-project the data to be used in GIS. 

The objective is to build data frames displaying feature data of the world in different projections.  In this exercise we will change the projection for Wisconsin and create a map using the appropriate projection. 

First, I downloaded or unzipped the data file and saved it to my personal folder in the Q drive.  Then I opened ArcMap and set up all the files to save in lab 1.  Next, I set up the world predefined projections data frame.  I then added the country and geogrid to ArcMap.  I then changed the legends for each of the shapefiles to desirable colors that made it easier to read the maps.  I then set up the Geographic Projection.  I selected the appropriate coordinate system and then saved my map.  I saved it under my lab exercises and as an mxd.

Next, I build another data frame, I followed the same path to do this but used Mercator Projection.  I also changed all the symbols again.  After this I created three more coordinate systems, Sinusoidal, Equidistant-Conic and Miller Cylindrical.  I tried using colors that are pleasing to the eye and that were easily distinguished from other colors. 

 
This is a screen shot of the map coordinates and layouts that I chose. I made the maps large enough to be readable.

Next, I created a data frame for the Wisconsin data.  I inserted a new data frame and named it UTM  and added it to the map.  I then created a new shapefile for the states layer and I selected Wisconsin and highlighted it and exported it to my map.  I then changed the symbolization and set the data frame coordinate system to UTM,NAD1983,Zone16N.

I then did some trial and error to see how the projections looked.  I changed the projected coordinate system to North American Lambert Conformal Conic. 

Next, I created a map containing all of the seven data frames I created.  I resized them to look for conformed.  I then labeled them and organized them in a landscape view.