Monday, December 16, 2013

Lab 5 - Final Lab

Question: What city in the Chicago area is the best place to live? I’m moving to Chicago to pursue a GIS career and the company I work for is located in downtown Chicago. I don’t want to live in the busy city, since I’m from a small town and prefer something smaller, so I decided to find a city within the county that Chicago is located in. The county is Cook County and it contains Chicago as well as 77 other suburbs and cities. To narrow down my selections I wanted a city that meets all of the requirements below:

1.       At least two miles from a hospital, just in case of emergencies.

2.       At least three miles from a recreational area, for my free time.

3.       At least a mile away from major interstate highways, to avoid the noise.

4.       Within 15 miles of downtown Chicago.

I thought that if I could meet all of the criteria above I would find a city that would fit my wants and needs.

Introduction: My objective is to use this question as a way to showcase my skills and present the knowledge that I picked up during this course through ArcMap. My intended audience would be my future self if I chose to pursue a career in GIS in Chicago and I would use this information to make a decision on where to live given this situation. I chose this question because it was something that I might actually want to use in the future and I thought it was an interesting question to end this course with. I wanted to ask something that I would actually want to know in a real-life situation.

Data Sources: The data I needed to perform this project was, cities in Cook County, interstate highways in Cook County, hospitals in Cook County, and recreation areas in Cook County. I got all of this information from the GISOnline database in the DATA folder in UWEC’s server. Data concerns I had included: precision of data, since the database included the entire country, however the data was from 2010, so I don’t think that age of the data was a factor with these certain types of features.

Methods: First, I took all of my data for cities, hospitals, recreation areas, and interstate highways, and I narrowed the selection down to just those contained in Cook County. Then, I added the “hospitals” and “recreation areas” features to ArcMap. I buffered the hospitals two miles around (Fig 1) and the Recreation Areas three miles around (Fig 2). I then intersected the two buffer zones and created an area that was at least two miles from a hospital and at least three miles from a recreation area (Fig 3). I then added the “interstates” feature to the map and buffered around it one mile. I then used the “Erase” to get rid of the area around the interstate highways that was within a mile (Fig 4). Then made a feature class of just downtown Chicago and made a 15 mile buffer. I then used “Erase” again and got rid of the acceptable area outside of the 15 mile buffer (Fig 5). Then I had the area that met the criteria I used above. I then used a spatial query to find the cities in Cook County that were within the acceptable area.











Data Flow Model:


 

Results: There were 13 cities that met all of the criteria: Elmwood Park, River Grove, River Forest, Melrose Park, Evanston, Skokie, Berwyn, Oak Park, La Grange, Palos Heights, Oak Lawn, Evergreen Park, and Blue Island. The city that I chose was Berwyn because it is the closest city that met all of my criteria and it just happens to be my mother’s hometown!

Map of the Acceptable Cities:






































Evaluation: I really enjoyed doing this project because it showed how much I learned in this course and the skills I earned that I can use in my future professional career. If I were to do this project again I would try to find more interesting data because I was pretty bad at search through the ArcGIS Online database and couldn’t find data that I thought was exciting. I faced some challenges in the data finding part of this project but I think if I were to just spend more time getting a feel for the system, I could come up with more fascinating data sources.

Friday, December 6, 2013

Lab 4

Goal: The goal of this lab was to use geoprocessing tools from ArcMap to map out the best locations for bears to live in a study area in Marquette County, Michigan; and also to make a data flow model of the process.
Background: I was given a study area in the county of Marquette, Michigan, and I was shown bear locations, the land coverage, and also streams in the area. The data was provided from The Michigan Center for Geographic Information.
Methods: First I converted the bear location data I received in Excel format into x, y coordinate data. I mapped out the locations and found what types of land cover the bears were found in using the Join tool to combine the tables from the landcover and bear location layers. They were found in mixed forests, forested wetlands, and evergreen forests. I then performed a Buffer 500 meters around the streams to see if bears we found in these areas. They were found 500 meters from streams 72% of the time, so I used that information in finding ideal bear habitats. (see Objective #2 below)
I then did a Intersect and combine the buffer around the streams and the three landcover areas the bears were mostly found in. Then I did a dissolve and the results came out in the Suitable Bear Habitats feature you see in the map below. (see Objective #3)
I was then was asked to find areas within the DNR managemnet lands that bears could inhabit. I mapped the DNR management lands and used Intersect and Dissolve just as before to find land that was both DNR and bear habitat. (see Objective #4)
However, before approval, the DNR wanted the areas to be at least 5 kilometers away from urban or built up land. So I performed a buffer on the land cover that included urban areas and used Erase to remove the parts of the DNR bear habitat that was within the buffer and the result is shown below as DNR Approved Habitats in map. (see Objective #5)
Results: The resulting map below shows the area that bears most likely are inhabiting and also where the DNR could safely use for bear habitats away from urban areas and within the DNR management areas. Their habitats are near streams and in heavily forested areas.

Map:

Data Flow:








Sources: The Michigan Center for Geographic Information

Tuesday, October 29, 2013

Lab 2

Introduction: The goal of this lab was to learn how to download, modify, and map data from the United States Census Bureau Website. This data was collected in the 2010 Census.
 
Methods: First, I searched the US Census Bureau Website to find both population and housing unit numbers for the counties of Wisconsin. I used the 2010 US Census SF1 100% data. I then downloaded them as Microsoft Excel files and put those tables into ArcGIS. I then combined the Excel tables into county shapfiles into one shapefile so that the data downloaded had features to match the data and therefore I could map it.
I then mapped to maps, one on county population, the other on number housing units in each county; then added basemaps, scales, titles, etc.
 




























Results: The data results were expected, with Madison and Milwaukee as the centers of population and housing and a direct correlation between population and housing units. I now have the very important skill of using US Census Bureau data off of their website.
 
Sources: 2010 US Census SF1 100% data from the United States Census Bureau Website: http://factfinder2.census.gov 
               

Friday, October 25, 2013

Lab 3

Goal and Background: The goal of this lab was to learn how to create a map with shapefiles that we collected ourselves with GPS units. We chose to map the campus mall here at UWEC. The objectives of this lab included learn how to map point features, line features, and polygon features using a GPS unit.

Methods: First we mapped the polygon features by walking around the grass features of the campus mall with our GPS unit actively collecting data along the way. Next we mapped a line feature, the footbridge, much in the same way as the polygon. Finally the point features such as the light posts and trees we mapped by collecting points with the GPS while standing next to the objects. These skills I learned in this lab helped me reach the goal and become familiar with using the GPS unit. 

The next step was putting this data I collected into ArcGIS and mapping it on the computer. I plugged in the GPS unit and transferred the data from a file on the unit into a folder on the computer. Then I transported the data into ArcGIS and put it on top of a satellite photo of the area including campus buildings surrounding it.

Results: The map that I produced with this lab is shown to the left. The satellite image does not match with the GPS data because there has been construction in this area, making it much different today, and the satellite has not updated since then. The point and line features collected seem to be very accurate, however the polygon features have very noticeable glitches where there appear to be extra bits of grass where there shouldn't be and the biggest polygon does not match up from the beginning to the end. These skills I learned in the lab are valuable and useful but mapping polygons such as these would be better produced and more accurate using digitizing techniques.  

Friday, September 27, 2013

Lab 1

Goal and Background:
For our first lab we took on the task of preparing base maps for a local construction proposal called the Confluence Project in Eau Claire. Along the way we learned various skills such as understanding the Public Land Survey System (PLSS), Zoning, Civil Divisions, Censu Data, and more.
Methods:
I used the data from the City of Eau Claire and EC County to obtain all of the maps in this project and created the proposed site myself by digitizing the parcels included in the project using the same data mentioned above.
Some skills I used in making these maps include: adjusting the color and transpanecy of polygons in order to see through to the base layer satellite image, labeling certain features , and adding and adjusting legends, scales and text on top of the finished maps.





Sources:
City of Eau Claire and Eau Claire County 2013