Part of my time at Whitewater was spent working toward a GIS Certificate. I have taken GIS I, GIS II, Applied Environmental GIS, Remote Sensing of the Environment, as well as Cartography and Geovisualization. Not only did I learn how to use multiple programs, tools, and methods to get to a desired outcome, but I learned how to effectively analyze maps to determine patterns or trends in the data. Below are some of the maps that I have completed during my time at the University of Wisconsin-Whitewater.

Looking at Landscape Metrics and Bird Diversity

Using ArcGIS online and ArcGIs Pro, I was able to develop a report that looks at the relationship between the landscape in Wisconsin and the many different birds found along different BBS routes. Scrolling through this report, you will find a detailed interactive map of the 14 BBS routes studied.

Measuring Storm Rainfall Runoff Change

General Reference Map of Smith County, Tennessee

General reference maps are useful for showing an area accurately to get a general idea of the layout of the specific landscape. While creating this map, it was challenging to decide what elements to include as well as the color schemes throughout. The most satisfying about finishing this map was knowing that after all of the hours put into it, the final result is visually appealing and accurate and one of my favorite maps I have created.

Mapping Population Percent Change

Interactive Map created in Carto showing

2010-2018 Income Percent Change

Above is an interactive map I created in Carto. Interactive mapping is very easy to use and can also produce maps that are very visually appealing, sometimes with more features than a map created in ArcMap would have. While some of the color schemes they have are not suitable for certain datasets, they can be manipulated manually. This is why it is important to have a strong set of cartographic skills. While many people have access to these interactive mapping programs, they don't always have the skills required to not only create an attractive map, but a map that accurately shows patterns in the spatial data.

Bivariate maps are useful because they show multiple data sets simultaneously, allowing for conclusions to be drawn based on the patterns that are created when the datasets are overlapped. While these can be super useful for analyzing data, they are a bit tricky to produce since the color scheme is difficult to nail down and you have to manipulate multiple classification schemes in order to accurately display the patterns needed for further analysis.