Cartographic Skills Module 10

Here is the map I created for this week's lab. It includes data pertaining to the immigration from six continents to the United States in 2007.

This flow map has lines, with sizes indicative of the number of people who immigrated, pointing from the respective continents to the United States. I also added a few extra touches, included drop shadows, inner glow, and 3D effect to some of the features.

GIS 4043L: Data Search

For this lab, we were to find and download all of the data for up to three maps on our own. I was assigned Pasco County, FL. A good amount of the data was found on the FGDL website, and others came from LABINs and the Florida Department of Environmental Protection.

For the first map, I included the data for the Pasco County boundary, as well as the major roads, rivers, and cities found within the county.

For the second map, I included all of the environmental data. This included public lands, invasive species, and land cover.

The final map consisted of the DEM and the DOQQ. I also included a map of Pasco County, with a rectangle around the area featured in the Raster datasets to show where exactly in the county they were located.

Cartographic Skills: Module 7

For this week's assignment, first we were to download data about the population changes in the United States over a ten-year span into ArcMap. From there, we were to classify the data and create a basic map which included a legend, scale, and north arrow, and then save it as an .ai document to be opened in Adobe Illustrator. On my first map I used a Natural Breaks classification.

Once in AI, the assignment was to add final touches to the map and doctor it up and give it a good layout.

The second part of the assignment was to take a copy of the finished product in AI and create a different classification scheme based on data provided in an Excel document. This time I chose a Quantile classification scheme.

Someone observing both of these maps can not only see the difference in population across the United States from 1990 to 2000, but they can also see the differences between data classified by Natural Breaks and data classified by a Quantile system.

Module 6: Data Classification (Cartographic Skills)

This week's lab was pretty interesting and was fairly easy to work through. In this lab, we were to use four different data classifications in four different maps (though all included within one full map) for African-American population distributions in Escambia County, FL.

The primary new thing I learned this week was how to change the data classification, which is done simply under the Symbology tab for a given layer's properties. This had to be done four different times, using Natural Break, Equal Interval, Quantile, and Standard Deviation classification for each of the four layers. Once this was one, it was just a matter of adding all of the essential map elements to the page. Any reader of this work should be able to tell the differences between each classification and use it to help choose which one they may need for any given data.

Week 6, Intro to GIS

This one was a rough go. Due to a very busy week (and me neglecting to get an early start on this lab), I wasn't able to begin this one until the final evening. Everything in this lab went fairly smoothly until I attempted to get the X and Y coordinate data correctly downloaded and placed on the .mxd. After reading the instructions over and over, and reading just about every post in the Classroom Discussion, it still wasn't working, and I eventually ran out of time. Below is the image of what I was able to get finished for the evening.

Cartography Module 5

For this week's lab, we were introduced to spatial statistic on ArcGIS Online. In these exercises, I was able to learn how to explore the spatial distribution of any given data. The image below is the histogram of the temperatures recorded from the weather stations across Europe. It's pretty interesting to see how quickly you can generate this information on ArcMap. In just a few steps you can find out anything you want on the spatial distribution of your data.

Intro to GIS Week 5 Lab

This one was not only pretty interesting, but I was also able to finally notice how much I've learned about using ArcMap. The part that gave me the most trouble, however, was creating a legend for each of the three maps. It was just pretty time-consuming to open the attribute table, select the attribute, and make each layer for each dataframe. But here's what my finished product turned out to be: