GIS 1: Lab 4 - Suitable Cabin Locations in Northwest Wisconsin

Introduction:  Cabins in the northern parts of Minnesota and Wisconsin are a great way to vacation in the summer.  People go up there all the time to hunt, fish, and get away from the city life or to take a break from work.  Great aspects of cabins are ones located in forests, near bodies of water, and not too close to major cities.  All of these characteristics are viable to make a map for possible cabin locations in Wisconsin.  My particular areas of interest were in northwest Wisconsin.  People that are interested in this could be realtors, cabin investors, people looking to buy a cabin, or even me.  I would eventually like to have a cabin some day so I can take my family up there and have a nice 4th of July vacation.

Data Sources:  In order to make a map of these possible locations, I needed some data.  I would need: cities and counties of Wisconsin, forests, lakes and streams, census data, and DNR deer harvest information.  All the Wisconsin land data I got was from the Wisconsin Department of Natural Resources in their fire protection metadata folder, except for the deer harvest information.  I got that from ArcGis online (http://services1.arcgis.com/do3Qqawv5p1BzFow/arcgis/rest/services/DeerHarve
st2015upload/FeatureServer).  The census data about city population came from ESRI online and were downloaded onto ArcMap 10.3.1.  Some concerns I have about this data is the availability of land.  The data did have a lot of forest land available on the map, but not all of it is available for the public or to buy.  Many of it could be privately owned, which means it would not be available for cabin use.  This is okay though, because all I am showing are suitable locations for possible cabins in northwest Wisconsin.

Methods: In order to answer my question, I needed to locate the forests of Wisconsin.  I wanted the cabins to be in the forests so all I had to do was leave the forests feature class alone.  If the cabins were going to be nice for fishing, they would have to also be near a stream or a lake, so I made a 500 meter buffer around all the streams and lakes.  Hunting was my next priority.  If the land was going to have good hunting, then you would assume it would have a high deer harvest.  So I used the data from the DNR deer harvest of 2015 and found the top half of those areas.  I also did not want the cabins withing a 50 kilometer distance of a large city, so that was another buffer and an erase later on.  In the end, I used an intersect and came up with the areas that you see on the map in the results.  Below, is a picture of the data flow model suited for these steps.

Data flow model

Results:  The results of my project were to be as expected.  I was actually surprised with how much of an area the possible cabin locations took up.  I was expecting a smaller area and was quite pleased to see that their was lots of land cover.  If you look on the map below, you can see that I focused mainly on Douglas, Bayfield, Burnett, Washburn, and Sawyer counties.  The cabin areas are long and narrow, because most of them are following along the stream and lake buffer.  The cabins far to the north would also be near the border of Lake Superior as well. 

Evaluation: I really enjoyed working on this project more than working on the previous projects because this one meant a lot more to me.  It was something that I chose and was really interested in and wanted to learn about.  I thought it was fun to see possible locations for cabins in the future and really enjoyed the process of making the map.  If I were to do this project over again, I would like to find available forest land for sale and not just all forest lands.  That way, if I were to actually think about buying a cabin, it would be a more suitable map.  It would show places that could actually be occupied right away, it would make the project more real and not so spacial.  In order to do that, I would have to look at real estate places and see if they have metadata I could download.  If no data is available at all, I could enter the data in myself and then use my own geodata to make the map more accurate.  Some challenges I faced during this project were finding suitable land type.  I really wanted to find land use of all kinds and not just use forests, so I could possibly have a cabin that's near a river or stream but is not into a forest, but it was just too hard to find the data and use the pertinent information.  All in all though, it seemed to be a really good and exciting project which I really enjoyed working on. 

The map was made in ArcMap 10.3.1

Data flow model was made in PowerPoint

All data came form Wisconsin DNR or downloaded from ESRI online. 

GIS 1: Lab 3 - Vector Analysis with ArcGis

Goal:  The goal of this lab was to use geoprocessing tools and vector analysis in ArcMap 10.1 to determine suitable bear habitats and DNR management areas for bears in Marquette County, Michigan.  We want to locate and put in place DNR management areas for bears that are in suitable bear habitats but are also not near urban areas.

Methods: To start this lab, we had to add data that was obtained from the Michigan DNR about known bear locations.  This data was in X,Y format, so we needed to learn how to add that type of data onto ArcMap.  After this, we had to export the data.  Once we got the known locations of bears, we were able to find the forest type that most bears were found.  From this information we found suitable bear habitats based on land type and if that land was found near streams.  After the suitable bear habitat was found, we intersected it with DNR management areas to locate bear management areas that could possibly be used.  From these locations, we had to remove ones near urban or built up land areas.

Here is a python code for part of the process listed above

Data flow model of the whole process

Results: Shown below is a map of the suitable bear habitats, bear locations, and bear management areas.  As you can see, most of the bear habitats and management areas are located near streams.

 Sources: All of the data were downloaded from the State of Michigan Open GIS Data. http://gis.michigan.opendata.arcgis.com/.
ArcMap 10.1 was used for making the map
PowerPoint was used for the data flow model

GIS 1 Lab 2: Downloading Data

Introduction: The goal of this lab was to learn how to download data from the US Census Bureau website.  After downloading, we also had to learn how to modify, adjust, and map the data.

Methods: The first task was to search and locate information of Wisconsin on the US Census Bureau Website.  I searched for Population and Housing Units in the state of Wisconsin.  After locating the ones I wanted, I downloaded them and unzipped the files.  After unzipping them, I was able to look at the MS excel file of the metadata.  Doing this, I was able to see if the data would work well or not.  After adding the Excel table to Arcmap 10.1, and using a join with another states table, I was able to map the data.  Looking at my map then, I could change the symbology to show the data in a friendly way.  The resulting maps are shown below.

Results: As you can see from the data, Population and Housing units correlated as one would expect.  The higher the population, the more housing units you will get.  Near Milwaukee has the highest population and Eastern Wisconsin in general seems to have higher housing units and population. 

Sources: US Census Bureau Website.  Mapping done in Arcmap 10.1.  Tables edited in MS Excel. 

GIS 1 Lab 1: Base Data

      As an intern at Clear Vision Eau Claire, it was my goal to prepare base maps for the Eau Claire Confluence Project.  The Confluence Project is a new community arts center, university student housing, and commercial retail complex.  This new building is to be located at the confluence of the Chippewa and Eau Claire Rivers.  Along the way to reaching my goal, I learned about various spatial data sets that went along with land management, administration, and land use.  

    The methods I took to reaching my goal were very complex.  The first step I needed to do was get used to the data in the geodatabases.  The two geodatabases that I was working with were of the City and the County of Eau Claire.  My next step was to create my own geodatabase which would contain the proposed site for the Confluence Project.  In order to do this, I had to digitize the site and location of the project.  After digitizing, I saved the proposed site location to my new geodatabase, for easy access later on.  My next objective was to learn about how the Public Land Survey System worked.  This comes into play when I need to describe the location of the Confluence Project.  After I knew who the locating system worked, I was then able to find the legal description for the project.  In order to do this, I had to go to the City of Eau Claire Web GIS and find the parcels.  Once the parcels were found, I was able to click on them and look at the legal description.  After I knew a lot of the information on the project, it was now time to create base maps that would be relevant to the information needed on the project.  The first map was of civil divisions in Eau Claire.  The second map showed the Census boundaries of the project.  The next map showed the PLSS location of the map so it could be seen in a formal way.  The fourth map was of the parcels of Eau Claire, and the fifth map was of all the zones in the city.  The last map showed the voting districts of Eau Claire, and all the maps had the parcels where the proposed site was going to be.  

    

 Results:        

Figure 1.  Multiple base maps of the Eau Claire Confluence Project.  The proposed site is showed in two parcels of red on all the maps.  Data comes from the City and County of Eau Claire of 2013.

Results are showed on the map above.  As you can see, the project is located on the confluence of the Chippewa and the Eau Claire River.  The parcels of the project lie in the zones, divisions, voting districts, and census boundaries of Eau Claire.  

These data come from the City and County of Eau Claire Geodatabase of 2013. 

The City of Eau Claire Web GIS is found at:

http://www.eauclairewi.gov/departments/public-works/engineering/mapping-services