GIS 1 Lab 5: Ideal Building/ Living Location in Dunn County

  What would be the most ideal location to build or to buy property in Dunn County Wisconsin? Dunn county may be indistinguishable to some people in Wisconsin and to the majority of people in the nation. To me, I see the two major lakes that are centered in Dunn county, the timber an the agriculture that would make for good duck and deer hunting. Though the ideal location I selected would be more for a ideal family settlement. In order to determine the ideal spot to live, I linked data from GIS servers. I got data regarding highways, parks, schools, and cities. For this lab my targeted audience is people who are looking to move to Dunn county, or people who are looking to buy a house in Dunn County.

  The data sets I selected started with the United States Census and Dunn County Data. Next I added major highways and cities to the county data. Before I added any other data I clipped the data so it took out all the data that was not in the county. Then I created buffers around the cities and highways. For convenience purposes I made just a two mile buffer around the highways, so that commute time would be cut down. Then I made a five mile buffer around the cities, that way shopping and other groceries and necessities would be available for easy access. Then I intersected the data sets to give a rough idea of a decent location, though this is not ideal yet, it gives me an idea. Below is the five mile buffer around the cities and the highways were just added to show what cities were also near highways.

  The next step was to bring in the schools data. At first there was a unrealistic amount of schools in Dunn county. After pulling up the attribute table I saw that schools that were no longer there were including. I then selected by attributes to narrow the schools down to only current schools. Then I added a five mile buffer around the schools. Next I intersected the schools data with the new data set that was the highways and cities intersected layer.
  The data flow model below showed my steps as I went throughout the lab. I enjoyed this lab because it gave me the opportunity to use whatever data sets that I wanted. I chose Dunn county because it is a county that I really like.

  What I concluded from the map below was that my ideal living locations were all within ten miles of Menominee. All of the orange areas highlighted below met all of the criteria from the data flow model above. I made sure that the house would be no longer than two miles off of the highway, while being within ten miles of parks. The other major criteria I had was that the house location would be no further than five miles from a city, and no further than five miles from a school.

GIS 1 Lab 4: Vector Analysis with ArcGIS

  The goal of lab 4 was to investigate vector analysis using ArcGIS with several different geoprocessing tools. The main straight forward goal of this lab was to determine the best place for bears to live. In other words we wanted to find where there ideal habitat is. The study takes place in a portion of Marquette County, Michigan, near Lake Michigan. 

  The purpose of this lab was to gain more knowledge on the use of geoprocessing tools. A large part of our lab was to be able to diagnose the situation and figure out what we wanted to geoprocess and then select the correct tool. In this lab we were given multiple data sets to work with and explore. We worked with the land covers in the county, bear locations, where rivers flow,  DNR management land and many other data sets were offered. We had to use several different join, and many geoprocessing tools to get the data sets that we were seeking to create.

  This lab was the first lab we have had that was really vague, our hands were not being held on this lab, the directions were vague which gave us the opportunity to try many things that we wanted to try. The reason this lab was given to use with minimal step by step directions was to ensure that we were understanding what we were learning. What better way to assure that we were understanding than to apply our skills to a real world setting. First we imported the county data, streams, and the land cover. Next we joined bear count with the land cover to see which three land type covers held the most bears. The three areas that held the most bears were, Evergreen Forests, Residential areas, and wetland forests. Our next step was to create a 500 meter buffer around the streams in our study area to get a sense of if bears depended on rivers or not. So we added our buffer, then went to geoprocessing and used the dissolve tool on the buffer. Our results revealed that over 70% of bears live within 500 meters of streams. When examining the map below, consider where streams are while looking at the ideal habitat because it is clear they play a very influential role in finding the best spot to relocate bears. Next we selected the top three land cover types and put borders around the land covers. We did many things in this lab to see certain things and to figure out reason for why things are how they are. Then we added the DNR management land locations, using this data I combined it with the likely areas for bears to live. Next I added the DNR and landcover bear habitat data together and we wanted to create a buffer around Urban or built up land. We wanted to create a 5 kilometer buffer around built up land, simply because we do not want to propose bear locations in areas where people are. Then we used the erase tool to get rid of the original feature class and to keep the one with the residential buffer. Finally after I found the locations that I wanted the bears to be located I changed colors on the map. I made the background color a pale yellow as to not take away from the map, I made streams blue for obvious reasons and the stream buffer I made brown. I added transparency to all of these so we could see the terrain a little beneath. Lastly I added a north arrow, a scale, my legend, a mini map showing the highlighted study area in Marquette county, and a title. 

  The results that I found after completing my lab is that the ideal area for bears is within 500 meters from streams and not inside the 5 km buffer around the urban and built up areas. 

    

   

GIS I Lab 3: Downloading GIS Data

Introduction



 

 The goal of this lab was simply to learn how to download data from the United States Census Bureau and then be able to map data in ArcMap. In this lab we were required to use Wisconsin population by county, but our next data set was our choice. I chose to map the population of citizens over 60 years of age. We were urged to pick formats and colors that were cartographically pleasing to eye and that were easily interpretable for the everyday person.

 

Methods

 

There was some background knowledge that was needed to successfully complete this lab. First and foremost we needed to know what the US Census Bureau did. Next we have to be able to clearly differentiate from Census boundaries to Statistical boundaries. Throughout the lab we were encouraged to use only 2010 SF1 100% data because that is the data that is collected every 10 years, making it the most consistent and accurate. So our first move in this project was to go to the Census website and select the total population by county. Then we had to download the file, un zip it and save it into our lab 3 folders. Next we had to format it to be usable in ArcMap. Next we went back to the website and under the Geography tab found the Wisconsin counties map and saved that to our folder. The final set in getting this set up was adding both data sets to ArcMap and join them together. Lastly we used the symbology tab in ArcMap to edit our colors and layouts. Finally for my second map I preformed all the same steps as previously described and chose the same color layout for professionalism purposes. The very last thing I did was add a legend, north arrow, title, scale, source and a grey background map that had the great lakes outlined in order to provide the viewer with a generalized sense of what they were looking at.

 

Results

 

The two maps below show total population by county and the percent of people over 60 in each county. There is a direct relationship between the percent of people over 60 and the population per county. In the Madison, Milwaukee area we see the highest populations along with 3-14% of people over 60. Whereas up north where the population is smaller we see under half a percent over 60. This is most likely because healthcare is much better in populated areas, the people over 60 feel more safe and comfortable with more resources readily at hand.

 

 

GIS I Lab 2: Virtual Campus

Virtual Campus: Getting Started with Geodatabases

GIS I Lab 1: Base Data

Eau Claire

Goal
The goal of this lab is to become familiar with different spatial referencing used in Eau Claire. We will be using different data sets to display the confluence project in Eau Claire and some surrounding area. The data sets we are using to set up these six maps vary from land use to public land management.
Background
The Confluence project was scheduled to begin in the spring of 2014. These buildings will be new housing for students and a community arts center.
Purpose
The purpose of this lab was to broaden our skills involving base maps. Also to help us become more familiar with standard uses of city data.